JP4058310B2 - Sleep state determination device and bedtime monitoring system - Google Patents

Description

[0001]
BACKGROUND OF THE INVENTION
The present invention relates to a sleep state determination apparatus and a bedtime monitoring system for determining an abnormality of a subject.
[0002]
[Prior art]
Conventionally, various sleep determination devices and sleep detection devices for determining sleep of a subject have been proposed. One of them is a bedtime detection device that detects sleep on the subject in a non-contact state with the subject and determines sleep onset (see, for example, Patent Document 1). In this conventional bedtime detection device, whether to go to bed or fall asleep is determined according to the degree of body movement of the subject. However, this sleep detection device only detects the presence / absence of the subject and the state of rest / abnormality, and does not specifically determine whether the subject is abnormal.
[0003]
In addition, a sleeping state determination device that detects body movement during sleep of a subject and detects the heart rate and breathing in a non-invasive state to determine the degree of rest of the subject has also been proposed (see, for example, Patent Document 2). . In this sleeping state determination device, a resting state is determined using the amount of body movement as an index to determine whether there is a seizure, convulsions, or turning over, so the determination error is large.
[0004]
In recent years, a sleep determination device and a sleep detection device that detect and determine such unconsciously and non-invasively have been used to grasp the physical state of a cared person such as an elderly person living alone or a disabled person. For example, there is a sleeping state monitoring device that detects and measures biological data such as heartbeat, breathing, respiration rate, and snoring during sleep of a care recipient (subject) and transmits the detected data to a management center (see, for example, Patent Document 3). . In this sleeping state monitoring device, biological data detected and measured from a subject such as a care facility is monitored by a specialized management center such as a hospital. When an abnormality occurs in the subject, a report is made and a report is sent to a doctor in the hospital who has specialized knowledge.
However, in this sleeping state monitoring device, since the biometric data is data that is monitored and judged by an expert such as a doctor, it is difficult for those who do not have specialized knowledge to make a simple judgment. Furthermore, since a person who does not have specialized knowledge cannot easily determine, for example, the absence of the subject or the occurrence of abnormality cannot be reliably determined.
[0005]
On the other hand, a life monitoring system has been developed that can monitor the safety of cared persons such as elderly people living alone or physically disabled persons from a long distance. For example, there is a life monitoring system that monitors the life situation of a home obtained from operation information and operation information of electrical appliances in the home (see, for example, Patent Document 4). In this life monitoring system, operation information and operation information of electrical appliances in the home are transmitted outside the home, and information on these electrical products is accumulated and displayed. Moreover, in such a life monitoring system, each piece of information on electrical products is accumulated, date information is added to operation information and operation information of electrical products, counting is started, and these information can be browsed remotely. It is possible.
[0006]
In this conventional life monitoring system using an electrical product, the usage status of the electrical product differs depending on the user, so that only information that the electrical product is operated or not can be grasped. For this reason, it is difficult to reliably determine whether or not an abnormality has occurred in the user of the electrical product. In addition, even when living alone, it is difficult to specify the user who uses the electrical product, such as when there is a visitor. Furthermore, the frequency of use of electrical products varies greatly from person to person. Therefore, it is not possible to easily set an objective standard for comparing each subject such as “every subject goes to sleep at night”, and objective data for comparing subjects cannot be obtained. Furthermore, only information when the subject is awake when using the electrical appliance can be monitored, and the sleep state cannot be monitored.
[0007]
[Patent Document 1]
JP-A-4-272746
[Patent Document 2]
JP-A-8-317909
[Patent Document 3]
JP 2002-52010 A
[Patent Document 4]
Japanese Patent No. 3193363
[0008]
[Problems to be solved by the invention]
Thus, the conventional sleep state determination device has a problem that it is difficult to accurately determine the abnormality of the subject. Further, the conventional life monitoring system has a problem that it is difficult for a person other than the subject to easily confirm the abnormality of the subject.
[0009]
The present invention has been made to solve such problems, and is a sleep state determination device capable of accurately determining a subject's abnormality, so that a person other than the subject can easily confirm the subject's abnormality. The purpose is to provide a bedtime monitoring system.
[00010]
[Means for Solving the Problems]
The sleep state determination device according to the present invention is a sleep state determination device that determines an abnormality of a subject, and is a detection unit that detects sleep information from a device installed on the subject's bedding (for example, the living body in the present embodiment). Based on the information detection unit 31) and the sleep information of the subject detected by the detection means, occupancy information generation means (for example, generating occupancy information indicating whether the subject is in bed or out of bed) The monitoring time set in advance as the time for determining the sleep state of the subject based on the bed information generated by the data generation unit 63) of the data analysis unit 32 in the present embodiment and the bed information generation unit. Determining whether or not the subject has been in bed or left for more than a predetermined reference time, and if the subject has been in bed or left for more than the reference time Judging means for outputting a broadcast (e.g., the determination unit 65 of the data analysis unit 32 in this embodiment) is obtained and a. With such a configuration, the abnormality of the subject can be accurately determined.
In the preferred embodiment, the monitoring time is a preset fixed time.
[0011]
Also, when determining the nighttime abnormalities, the average bedtime averaged over the past number of days in the past the longest bedtime in the day as the monitoring time, when determining the daytime abnormalities, The average bed leaving time obtained by averaging the longest bed leaving times in a day for a predetermined number of past days may be used as the monitoring time. By determining the monitoring time in this way, an appropriate monitoring time can be set according to the past bedtime.
When determining a nighttime abnormality, the average bedtime is calculated assuming that a bedtime is shorter than a predetermined time, and when determining a daytime abnormality, the average The bed leaving time may be calculated assuming that a bed time shorter than a predetermined time is leaving. In this way, by calculating the average bedtime and the average bedtime, the abnormality determination is performed by eliminating the short bedtime or bedtime, so that the abnormality can be determined more accurately.
[0012]
Also, when determining nighttime abnormalities, the standard time used to determine bedout is calculated based on the average bedtime averaged over a predetermined number of days in the past to determine daytime abnormalities. In this case, it is preferable to calculate the reference time used for the determination of bed based on an average bed time obtained by averaging the bed time for a predetermined number of past days. According to such determination, since the reference time can be determined according to the actual bed leaving time or bedtime, abnormality can be determined more accurately. Furthermore, when determining an abnormality at night, the reference time used for determining a bed break is calculated based on the longest bed leaving time in the past for a predetermined number of days to determine the daytime abnormality. In some cases, it is possible to accurately determine an abnormality by calculating the reference time used for the determination of bed based on the longest bed time in the past bed time for a predetermined number of days. it can.
[0013]
In addition, when determining abnormalities at night, the reference time used to determine bed leaving is calculated without including the bed leaving time on the day when the alarm is output, and when determining daytime abnormalities, The reference time used for the determination may be calculated without including the bedtime on the day when the alarm is output. By such a determination, when an alarm is output, it is considered that an abnormal state has occurred, so since the reference time is determined by excluding the data of bed leaving time and bed time on such a day, Abnormalities can be determined more accurately.
[0014]
Furthermore, when determining an abnormality at night, if a day shorter than a reference time by a predetermined time or longer than the reference time continues for a predetermined number of days, the reference time is shortened by a predetermined time. When setting and determining abnormalities in the daytime, if the bedtime is shorter than the reference time by a predetermined time or more, the reference time is set to the predetermined time only. It is desirable to set it short. By determining the reference time in this way, the reference time can be appropriately determined according to past trends.
[0015]
Also, the reference time of the day after the alarm is output may be set longer by a predetermined time than the reference time of the day when the alarm is output. Reoccurrence of false alarm output can be prevented.
On the other hand, a sleep monitoring system according to the present invention is a sleep monitoring system including the sleep state determination device described above and a monitoring device that monitors a subject's abnormality, and the sleep state determination device at least provides an alarm for the monitoring. A monitoring unit that receives the alarm transmitted from the transmission unit; and a notification unit that notifies the alarm in response to the reception of the alarm by the receiving unit. It has. With such a configuration, it is possible to obtain accurate information regarding the occurrence of abnormality of the subject, particularly in the monitoring device.
[0016]
Furthermore, the transmission means of the sleep state determination device further transmits occupancy information to the monitoring device in addition to the alarm, and the reception device of the monitoring device receives the alarm and occupancy information transmitted from the transmission means. The informing means of the monitoring device may further be in a state in which the presence information can be browsed by a registrant's terminal registered in advance. With such a configuration, the registrant can easily acquire bed information.
[0017]
DETAILED DESCRIPTION OF THE INVENTION
Hereinafter, embodiments of the present invention will be described with reference to the drawings.
[0018]
First, a sleep state determination apparatus according to an embodiment of the present invention will be described, and then a sleep monitoring system using the sleep state determination apparatus will be described.
[0019]
First, the sleep state determination apparatus in the present embodiment will be described. The sleep state determination apparatus according to the present embodiment detects a user's bedtime and bedtime, and generates an alarm when these times are equal to or longer than a certain reference time.
[0020]
A configuration example of the sleep state determination apparatus according to the present embodiment will be described with reference to FIG. FIG. 1 is a block diagram illustrating a configuration example of a sleep state determination apparatus according to the present embodiment. As shown in FIG. 1, the sleep state determination device 11 a includes a biological information detection unit 31 and a data analysis unit 32.
[0021]
The biological information detection unit 31 detects the biological information of the subject and outputs it as a detection signal. Here, the biometric information detected by the biometric information detection unit 31 indicates a sleep state detected by the sleep state determination device 11a installed in the bedding of the subject. The data analysis unit 32 generates occupancy data indicating the presence / absence of the subject based on the detection signal detected by the biological information detection unit 31. Then, the data analysis unit 32 calculates the bedtime and bedtime from the generated bed data, compares the bedtime and bedtime with a predetermined reference time, and generates an alarm based on the comparison result. It is determined whether or not to generate.
[0022]
An example of the sleep state determination device 11a will be described with reference to FIGS. FIG. 2 is a schematic diagram illustrating a configuration example of the sleep state determination device 11a. As shown in FIG. 2, the sleep state determination device 11a includes, for example, a fluid enclosure 31a, an air tube 31b, a pressure sensor 31c, and a data analysis unit 32.
[0023]
Here, the fluid enclosure 31 a, the air tube 31 b, and the pressure sensor 31 c constitute a biological information detection unit 31. Changes in the human body can be detected by the fluid enclosure 31a, the air tube 31b, and the pressure sensor 31c.
[0024]
The fluid enclosure 31a is also called a vital mat, an air mat, or a fluid bag, and is attached to a bedclothing such as a mattress or a sheet of a subject. The fluid enclosure 31a may be directly attached to the subject. That is, when detecting biometric information, the fluid enclosure 31a directly or indirectly contacts the subject. A fluid such as water or air is enclosed in the fluid enclosure 31a. The fluid enclosure 31a may be in the form of a pad or in the form of a sheet separated into a plurality of blocks.
[0025]
The air tube 31b is for transmitting the pressure fluctuation of the fluid enclosure 31a to the pressure sensor 31c. The air tube 31b is formed in a hollow shape, and the fluid enclosed in the fluid enclosure 31a moves freely. The air tube 31b is made of, for example, vinyl.
[0026]
The pressure sensor 31c is connected to the fluid enclosure 31a via the air tube 31b. The pressure sensor 31c detects the pressure fluctuation of the fluid enclosure 31a via the air tube 31b and outputs it as an electrical signal. Moreover, it is also possible to use a displacement detector that measures a change in the outer surface shape of the fluid enclosure 31a instead of the pressure sensor 31c. Note that the pressure sensor 31c may be directly connected to the fluid enclosure 31a without using the air tube 31b.
[0027]
By using such a sleep state determination device 11a, the biological information of the subject can be detected and measured unconsciously and non-invasively by the subject. Thereby, the mental burden at the time of measuring a test subject can be reduced.
[0028]
A configuration example of the data analysis unit 32 will be described with reference to FIG. FIG. 3 is a block diagram illustrating in detail a configuration example of the data analysis unit 32 of the sleep state determination device 11a. As shown in FIG. 3, the data analysis unit 32 includes a signal input unit 61, a bandpass filtering unit 62, a data generation unit 63, a control unit 64, a determination unit 65, a storage unit 66, and an output unit 67.
[0029]
The signal input unit 61 is connected to the signal output terminal of the pressure sensor 31. The signal input unit 61 receives a detection signal from the pressure sensor 31 and executes interface processing for signal processing.
[0030]
The bandpass filtering unit 62 removes noise and the like from the detection signal input from the signal input unit 61 and separates desired measurement data. Further, the bandpass filtering unit 62 may be an analog filter, and may separate the signal by a digital filter after A / D conversion of the input signal.
[0031]
Measurement data is input from the bandpass filtering unit 62 to the data generation unit 63. The data generation unit 63 calculates an integral value, for example, every 1 minute interval based on the power of the measurement data under the control of the control unit 64. Then, the data generation unit 63 compares the calculated integral value with a predetermined value using a comparator or the like. When the integrated value is smaller than a predetermined value, the data generating unit 63 determines that the integrated signal indicates bed leaving. In addition, when the integrated value is larger than a predetermined value, the data generation unit 63 determines that the integrated signal indicates bed presence. In this way, the data generation unit 63 generates occupancy data indicating bed leaving / floating. Then, the data generation unit 63 outputs the measurement data and occupancy information to the control unit 64.
[0032]
The control unit 64 controls processing by each component, such as signal processing control, display control, and storage control in the data analysis unit 32. The control unit 64 includes an MPU, CPU, ROM, and RAM. The control unit 64 acquires measurement data from the data generation unit 63 and stores it in the storage unit 66.
[0033]
When the measurement data is input from the bandpass filtering unit 62 to the data generation unit 63, the control unit 64 causes the comparator of the data generation unit 63 to compare the amplitude of the measurement data with a threshold value. Furthermore, the control unit 64 calculates the logical sum of the measurement data whose amplitude exceeds the threshold value and the occupancy data. And the control part 64 judges that there is a body movement, when the said measurement data shows bed presence and an amplitude exceeds a threshold value. When the measurement data indicates the presence of the floor and the amplitude does not exceed the threshold value, the control unit 64 determines that the floor is “floating”. In addition, the control unit 64 determines “get out of bed” when the measurement data indicates bed removal and the amplitude does not exceed the threshold value. The control unit 64 acquires bed data indicating bed leaving / floating and body movement data indicating presence / absence of body movement, and stores these data in the storage unit 66 with reference to time. When the data indicates getting out of bed and the amplitude exceeds the threshold value, the data is deleted as erroneous data.
[0034]
The determination unit 65 inputs and outputs signals with the control unit 64. The determination unit 65 includes a circuit such as a comparator or an adder. The determination unit 65 calculates the bed time and bed leaving time based on the bed data. Then, it is determined whether the staying time and the leaving time continue for a predetermined reference time or more. The reference time is, for example, 4 hours. Further, the determination unit 65 detects the number of body movements within a predetermined time from the body movement data, and determines whether or not there is a body movement more than a predetermined number. Further, the determination unit 65 may monitor whether a signal indicating biological information such as a heart rate, a pulse rate, and a respiration rate is input based on the measurement data. An alarm may be generated when these signals are not input. The determination unit 65 may determine abnormality by comparing the measurement data at the time of abnormality and the measurement data at normal time.
[0035]
The storage unit 66 stores measurement data, bed data, and body movement data. Information stored in the storage unit 66 may be stored in an external storage medium. The information stored in the storage unit 66 may be used for treatment afterwards. Further, the storage unit 66 may temporarily store a signal from the biological information detection unit 31 or may store data generated by the data analysis unit 32.
[0036]
The output unit 67 outputs measurement data, bed data, body movement data, and alarms so that they can be perceived to the outside. The output unit 67 includes, for example, a liquid crystal panel, a plasma display panel, an organic EL panel display means, and a sounding means such as a buzzer.
[0037]
Next, measurement data, bed data, and body movement data measured by the sleep state determination device 11a will be described. FIG. 4 is a waveform diagram showing measurement data generated from a detection signal detected by the sleep state determination device 11a. The waveform diagram of FIG. 4 is a time series measurement of the vibration of the subject's body from 16:00 on that day to 8:00 on the next day.
[0038]
At the time point (a) in FIG. 4, the sleep state determination device 11a is capable of detecting minute vibrations and displacement of the bedding and the like even when the subject is getting out of bed at a time such as daytime. Detect as noise. In addition, when the subject is getting out of bed, the sleep state determination device 11a has no fluctuation or displacement of body movement by the subject, and thus the waveform has no amplitude except for noise.
[0039]
At a time point (b) in FIG. 4, a waveform having a large amplitude is sharply generated from a waveform having no amplitude other than noise. This is because the sleep state determination device 11a detects the vibration when the subject enters the bedclothes when entering the floor. In this way, when a person gets on the floor or bedding, a waveform having a large amplitude is sharply generated from a waveform having no amplitude. Also, the waveform changes in the same way when a large force or weight is applied such as when luggage is placed on the bedding.
[0040]
Between the time point (b) in FIG. 4 and the time point (c) in FIG. 4, since a force is applied to the body of the subject at awakening or the subject moves even when entering the floor, a waveform having a large amplitude appears. Yes. At time (c) in FIG. 4, a waveform having a small amplitude appears steeply. This is because the subject's body loses power or the subject's body cannot move as the subject falls asleep. Here, the waveform at the time of falling asleep is a waveform having a small amplitude because the sleep state determination device 11a detects respiration and heartbeat during sleep of the subject.
[0041]
At time (d) in FIG. 4, a waveform having the same size as the waveform from the time of going to bed to the time of falling asleep appears continuously. This is because the subject wakes up and moves in the bedding while entering the bed. At the time point (e) in FIG. 4, a waveform having a relatively smaller amplitude than the waveform at the time of sleeping after the time point (c) in FIG. 4 is generated. This is because the contact surface with the sleep state determination device 11a is reduced because the subject changes the sleeping phase and turns sideways or the user's body is only partially on the sensor mat. That is, when a waveform having a smaller amplitude than other sleep waveforms appears, the subject changes the sleep phase.
[0042]
After the time point (f) in FIG. 4 and the time point (g) in FIG. 4, a waveform having basically no amplitude similar to the waveform shown in FIG. This waveform is a waveform when the subject leaves the floor, as opposed to entering the floor from the time point (a) of FIG. 4 to the time point (b) of FIG. 4. At time (g) in FIG. I am getting out of bed. A waveform having a large amplitude before leaving the bed at the time point (f) in FIG. 4 appears when the subject wakes up and moves in the bedding while entering the bed. And the waveform which has a big amplitude after getting out of bed as shown in (i) time of Drawing 4 is a waveform generated, for example, when a subject puts an object on bedding when changing clothes.
[0043]
Further, at a plurality of time points shown in (h) of FIG. 4, the waveform changes steeply to a waveform having no amplitude, and further changes sharply from a waveform having no amplitude to a waveform having amplitude. This indicates that the subject woke up during sleep and left the bed after getting out of bed.
[0044]
FIG. 5 is a schematic diagram showing bed data and body movement data created by the sleep state determination device 11a. FIG. 5A is a waveform diagram illustrating an example of measurement data generated from the detection signal detected by the sleep state determination device 11a, as in FIG. FIG. 5B is a schematic diagram illustrating an example of bed data and body movement data created from measurement data measured by the sleep state determination device 11a.
[0045]
The occupancy data shown in FIG. 5B is created based on the presence or absence of the amplitude of the signal indicating the measurement data. For example, the data generation unit 63 of the data analysis unit 32 calculates an integral value obtained by integrating the square of the amplitude of the measurement data with respect to time every minute, and compares this integral value with a predetermined value. It is assumed that the subject is present when the integrated value is larger than the predetermined value, and the subject is out of bed when the integrated value is smaller than the predetermined value. That is, it is possible to determine whether the user is in bed or out of bed by comparing the area between the square of the measurement data and the time axis for a fixed time with the reference value.
[0046]
The body motion data shown in FIG. 5B is created based on the amplitude of the signal indicating the measurement data. For example, the data generation unit 63 of the data analysis unit 32 compares the amplitude of the measurement data with a predetermined threshold every minute. It is assumed that there is body movement when the amplitude is larger than the threshold value and the subject is in bed using the above-mentioned bed data. When the amplitude is smaller than the threshold value, it is assumed that there is no body movement. In addition, using the above-mentioned occupancy data, occupancy / exit can be determined with occupancy in the case of in-floor and no body movement, and detachment in the case of leaving and no body movement.
[0047]
The floor data indicating the presence / absence of bed and the body motion data indicating the presence / absence of body motion determined in this manner are managed and stored in the storage unit 66 of the data analysis unit 32 for each time. In the floor data of FIG. 5B, the blank portion indicates leaving the bed.
[0048]
Next, alarms output from the determination unit 65 of the data analysis unit 32 will be described with reference to FIGS. FIG. 6 is a schematic diagram illustrating an alarm transmitted from the sleep state determination device 11a. FIG. 6A shows a case where a bed leaving time that is equal to or more than a predetermined reference time is detected during the nightly monitoring time. In this example, the monitoring time is set to 8 hours from 22:00 to 6:00 the next morning. The reference time is 4 hours. In this example, getting out of bed is detected at 23:30, and an alarm is output at the point of time until 3:30. In such a case, an alarm is output because it is determined that an abnormality such as being out of bed or falling from a bed or the like and being injured has occurred because the subject cannot sleep. Such an alarm is referred to as a “long-time leaving alarm”.
[0049]
FIG. 6B shows a case where a bedtime that is equal to or greater than a predetermined reference time is detected during the daytime monitoring time. In this example, the monitoring time is set to 8 hours from 8:00 am to 16:00 in the evening. The reference time is 4 hours. In this example, the occupancy is detected at 9:40, and an alarm is output at the time when the occupancy continues until 13:40. In such a case, the subject cannot wake up from the bed due to illness or injury, and it is determined that the bedtime has become longer, so an alarm is output. Such an alarm is referred to as a “long-time in-bed alarm”. In the example shown in FIG. 6, the lengths of the monitoring time and the reference time are the same at night and in the daytime.
[0050]
Here, the occupancy data is simple data unlike the measurement data as shown in FIG. 4 or FIG. 5A, and therefore the occupancy time and the leaving time can be easily calculated. Thereby, the sleep state determination apparatus 11a can perform a determination process easily based on bedtime or bedtime.
[0051]
As shown in FIG. 6 (c), the sleep state determination device 11a assumes that the user is suffering from illness or injury when body movement continues over a predetermined number of times within a certain period of time. An alarm is output when an abnormality occurs. Conversely, the sleep state determination device 11a assumes an abnormality such that the subject cannot move due to an abnormality when the subject is present but the body movement is less than a predetermined number of times within a certain time. May output an alarm. An alarm issued based on such body motion data is referred to as a “body motion continuation alarm”. In addition, the number of body movements within a certain period of time can be calculated from the number of body movements in each daily time zone from body movement data, for example.
[0052]
Here, as shown in FIG. 6, the body movement data is simple data unlike the signal detected by the biological information detection unit 31 as shown in FIG. 4 or FIG. The number of body movements in the time zone can be easily calculated. Thereby, the sleep state determination apparatus 11a can easily determine transmission of an alarm based on body movement.
[0053]
The determination process flow of the sleep state determination device 11a will be described with reference to FIG. FIG. 7 is a flowchart illustrating an example of a determination process flow of the sleep state determination apparatus 11a.
[0054]
Here, although the case where determination is performed at night is described, when determination is performed in the daytime, an alarm is output based on whether the occupancy time is equal to or greater than the reference time. In the example illustrated in FIG. 7, a case where the monitoring time that is predetermined as the time for determining the abnormality of the subject is a fixed time will be described.
[0055]
The sleep state determination device 11a is turned on at a monitoring time such as 10 hours from 22:00 on the current day to 8:00 on the next day. The sleep state determination device 11a starts to detect the biological information of the subject from the biological information detection unit 31 when the power is turned on (S151). And the data analysis part 32 of the sleep state determination apparatus 11a produces | generates measurement data from the detected detection signal, and creates bed data and body movement data (S152).
[0056]
The measurement data, bed data, and body movement data are stored in the storage unit 66. These data stored in the storage unit 66 are read from the storage unit 66 into the control unit 64. The determining unit 65 monitors the occupancy data and determines whether or not the signal indicating getting out of bed has continued for a reference time or more (S153). When the determination unit 65 determines that the subject has left the bed for a certain time or more, it determines that an abnormality has occurred (S154), and the determination unit 65 outputs an alarm (S156).
[0057]
The determination part 65 determines whether many body movements are continuing, when the signal which shows getting out of a fixed time or more is not continuing (S155). When it is determined that many body movements continue, it is determined that an abnormality has occurred in the subject (S154), and an alarm is output (S156).
[0058]
The monitoring time may be set according to the life time of each subject by self-reporting of the subject. Thereby, optimal monitoring can be performed for each subject, and abnormality for each subject can be determined more reliably.
[0059]
Moreover, the average value of the monitoring time in each day of the test subject's past preset days can be set as the monitoring time of the day. For example, as shown in FIG. 8, the longest bed time of each subject in one day is set as the monitoring time, and the average value of the monitoring time in the past seven days is set as the monitoring time of the day. Here, in FIG. 8, ST indicates the monitoring start time, and END indicates the monitoring end time. More specifically, when determining an abnormality at night, the average bedtime obtained by averaging the longest bedtime in a day for a predetermined number of past days is set as the monitoring time. Further, when determining an abnormality during the daytime, an average bed leaving time obtained by averaging the longest bed leaving day in a day for a predetermined number of past days is set as the monitoring time.
[0060]
In this way, by calculating the monitoring time of the day from the past days and monitoring the day, it is possible to efficiently perform the monitoring of the day in consideration of the past life rhythms close to the day.
[0061]
Furthermore, as shown in FIG. 9, you may ignore bed leaving within a preset time such as 60 minutes. More specifically, when determining an abnormality at night, the average bedtime is calculated on the assumption that the bedtime is shorter than a predetermined time. When determining an abnormality in the daytime, the average bed leaving time is calculated assuming that a bed time shorter than a predetermined time is getting out of bed. This prevents the alarm from being output when there is no need to output an alarm such as going to the bathroom during sleep, and can isolate a severe abnormality and issue an alarm more efficiently. Monitoring can be performed.
[0062]
Here, the reference time is not limited to the fixed time, and can be set by various methods. As an example, it is possible to calculate and set from the bed leaving time for each day of the subject's past preset number of days. That is, the number of hours obtained by multiplying the average value of the bed leaving times in each day for the past seven days by a certain predetermined ratio (safety factor) can be set as the time from when the subject leaves the bed until the alarm is generated. More specifically, when determining an abnormality at night, the reference time used for the determination of getting out is calculated based on an average getting-off time obtained by averaging the getting-off times for a predetermined number of past days. Further, when determining an abnormality in the daytime, the reference time used for the determination of bedtime is calculated based on the average bedtime obtained by averaging the bedtime for a predetermined number of past days.
[0063]
Furthermore, it can be calculated and set from the longest bed leaving time in the past preset days. In this case, for example, the number of hours obtained by multiplying the longest bed leaving time in the past seven days by a predetermined ratio (safety factor) can be set as the reference time. More specifically, when determining an abnormality at night, the reference time used for determination of getting out is calculated based on the longest getting-off time in the past getting-off times for a predetermined number of days. Further, when determining an abnormality in the daytime, the reference time used for the determination of bedtime is calculated based on the longest bedtime in the past bedtime for a predetermined number of days.
[0064]
Furthermore, when calculating from the bed leaving time and bed staying time for each day in the past preset days of the subject, the bed leaving time and bed staying date on the day when the alarm is generated may be omitted. In other words, if an alarm occurs 3 days before the monitoring day, when calculating the average value of the bed leaving time for each day for the past 7 days, the average bed leaving time is calculated by omitting the bed leaving time 3 days ago. The reference time may be calculated by multiplying a certain predetermined ratio (safety factor).
[0065]
In this way, by setting the reference time of the day from the past days, it is possible to efficiently determine the occurrence of the alarm on the day in consideration of the life rhythm such as the past bed leaving time close to the day. Furthermore, when the safety factor is set for each subject, optimal monitoring can be performed for each subject, and abnormality for each subject can be more reliably determined.
[0066]
Then, the reference time that is currently set on the sampling day may be reviewed in comparison with the bed leaving time or the bed staying time. For example, in the case of nighttime, it is assumed that a day when the bed leaving time is shorter than a time shorter by a predetermined time such as 30 minutes from the reference time has continued for a preset number of days in the past such as the past seven days. At this time, the time from the bed leaving on the sampling day to the alarm occurrence is set to a time shorter than the time from the bed leaving to the alarm occurrence by a predetermined time. Further, for example, the time from getting out to alarm occurrence may be set by comparing the bed leaving time with a time longer than the time from getting out to alarm occurrence by a predetermined time.
[0067]
In this way, by setting the time from getting out to alarm generation in accordance with the change in bed leaving time, it is possible to efficiently set the time from getting out to alarm generation corresponding to the bed leaving time. For this reason, an alarm can be generated in accordance with the change of the test subject's bed leaving time and life rhythm, and erroneous reporting can be prevented.
[0068]
Furthermore, the subject's daytime and nighttime may be monitored all day long. In this case, for example, a distinction between daytime and nighttime is established, such as daytime from 8:00 to 16:00 and nighttime from 16:00 to 8:00, and each alarm generation time is set to the bedtime according to the distinction between daytime and nighttime. Can be set from the bed leaving time. In this way, when monitoring day and night and night at the same time, it is possible to monitor when the subject takes a nap in the daytime and provides a more detailed safety confirmation service without giving the subject a mental burden It becomes possible.
[0069]
The measurement data, bed data, and body movement data described above will be specifically described with reference to FIGS. FIG. 10 to FIG. 13 are waveform diagrams showing measurement data measured by the sleep state determination apparatus 11a, schematic diagrams showing bed data and body movement data. 10 to 13 are enlarged data of FIG.
[0070]
FIGS. 10 to 13 show data measured from 16:00 on the current day to 8:00 on the next day. However, in the daytime data from 8:00 on the previous day to 16:00 on the current day, the subject basically gets out of bed. It is omitted as it is. Even daytime data can be measured in the same way, and the subject can be monitored.
[0071]
In the safety confirmation service, the safety of the subject may be confirmed using measurement data based on the vibration of the subject, bed data or body movement data created from the measurement data.
[0072]
In addition, although biological information is not basically used, it can be used as auxiliary data to be transmitted to an emergency facility such as a hospital when an emergency occurs in a subject. Here, biometric information is basically not used, and since such biometric information can be used in the same manner as before, the description thereof is omitted.
[0073]
FIG. 10 shows data when the sleep state determination device 11a measures from 16:00 on the day to 19:50 on the day. As shown in FIG. 10, a waveform having no amplitude other than noise continues from 16:00 to around 18:50 on that day. From this, it can be seen that the subject is getting out of bed. During this time, a signal indicating the continuous presence of the subject does not appear in the presence data. Further, no noise appears in the body motion data because the amplitude of the noise is small.
[0074]
Then, a waveform having a large amplitude appears from about 18:50, and it can be read that the subject has entered the floor. At this time, a discrete signal appears partially in the occupancy data as the user enters the floor, and a discrete signal indicating the body movement from entering the bed to falling asleep appears in the body movement data. After the subject enters the floor, it can be read that the subject has fallen asleep around 19: 5, as described above with reference to FIG. As a result of this falling asleep, a signal indicating continuous sleep appears after about 19: 5 in the in-bed data, and a signal indicating body movement accompanying the falling asleep disappears in the body movement data.
[0075]
Note that a waveform having a large amplitude temporarily appears after 19:30, and a signal indicating body movement temporarily appears in the body movement data. Here, the body motion data is not discontinuous around 19:30. In addition, the waveform remains large before and after 19:30 compared to a waveform having a small amplitude as shown in FIG. Therefore, it is considered that the subject moved his / her limb during sleep without changing the sleeping phase.
[0076]
As shown in FIG. 11, from 20 o'clock to 20:50, some waveforms with large amplitude appear, but body motion data is not discontinuous at that time, and the amplitude is large. There is no change. Therefore, the subject goes to bed while moving his / her limbs with almost the same sleeping phase. Then, at about 20:50, the floor data becomes discontinuous, and a signal having no amplitude appears with a waveform having a large amplitude before and after. At this time, a signal indicating the body motion appears in the body motion data across the discontinuous portion of the bed data. Therefore, it can be seen that the subject has left the floor temporarily and has further entered the floor.
[0077]
There is a signal indicating body movement in the body movement data from about 20:55 to about 21:35 when the subject enters the floor after leaving the bed, and a waveform with a large amplitude appears. At this time, the subject can enter the bed again but cannot sleep, and can be considered to be moving in the bedding while in bed. The subject becomes discontinuous in the occupancy data from 21:35 to 21:45, and a signal having no amplitude appears with a waveform having a large amplitude before and after. At this time, a signal indicating the body motion appears in the body motion data across the discontinuous portion of the bed data. Therefore, it can be seen that the subject has left the floor temporarily and has further entered the floor.
[0078]
The subject who entered the floor again can read that the subject has fallen asleep around 21:45, as described above with reference to FIG. Along with this falling asleep, a signal indicating continuous sleep appears in the occupancy data after about 21:45, and a signal indicating body movement accompanying the falling asleep disappears in the body movement data. In addition, since a waveform having substantially the same amplitude as that of the waveform appearing from 20:00 to around 20:50 appears, the subject has the same sleeping phase as that at bedtime from 20:00 to around 20:50. Can be considered sleeping.
[0079]
At about 23:10, the floor data becomes discontinuous, and a signal having no amplitude appears along with a waveform having a large amplitude before and after. At this time, a signal indicating the body motion appears in the body motion data across the discontinuous portion of the bed data. Therefore, it can be seen that the subject has left the floor temporarily and has further entered the floor. There is no signal indicating body motion in the body motion data from 23:10 to 23:30 when the subject enters the floor after leaving the bed, but the amplitude of the waveform during sleep is large.
[0080]
Then, from 23:30 to 23:40, the occupancy data becomes discontinuous again, and a signal having no amplitude appears with a waveform having a large amplitude before and after, and the discontinuous portion of the occupancy data is displayed in the body movement data. A signal indicating body movement appears. Therefore, although the subject temporarily left the floor and entered the floor at around 23:10, he could not fall asleep well and was moving in the bedding, but it can be considered that he has left the floor again after all. Furthermore, it seems that the user has left the bed for a relatively long time because there is no signal indicating the presence of bed in the body motion data. Thereafter, the subject left the bed for about 10 minutes, but entered the bed at about 23:45 and fell asleep.
[0081]
As shown in FIG. 12, as the subject falls asleep again, a signal indicating continuous sleep appears around 23:50 in the in-bed data, and a signal indicating body movement accompanying the sleep in the body motion data. Is gone. In addition, since a waveform having substantially the same amplitude as that of the waveform appearing from 20:00 to around 20:50 appears, the subject has the same sleeping phase as that at bedtime from 20:00 to around 20:50. Is sleeping.
[0082]
At 0:30 the next day, the floor data becomes discontinuous again, and a signal with no amplitude appears along with a waveform with a large amplitude before and after the body movement data. A signal indicating that appears. Therefore, the subject temporarily left and entered the floor before 0:30. After that, from around 0:30 to around 0:50, a signal indicating body movement appears in the body movement data, and a signal with a large amplitude appears. It is thought that he was moving in the bedding. The subject who cannot fall asleep is getting out of bed from about 0:50 to after 1: 5. In this case, the occupancy data becomes discontinuous from around 0:50 to after 1: 5, and a signal having no amplitude appears with a waveform having a large amplitude before and after, and the discontinuity of the occupancy data appears in the body movement data. A signal indicating body movement appears across the part.
[0083]
At about 1: 5, a signal indicating body movement appears in the body movement data, and a waveform with a large amplitude appears, and the subject is asleep. After sleeping, the person sleeps until about 3 o'clock. For example, a waveform having a smaller amplitude than the amplitude of the waveform appearing from 20:00 to about 20:50 appears. Here, the waveform has no amplitude at the time of getting out of bed, but this waveform does not have no amplitude like the amplitude at the time of getting out of bed, but has an amplitude. As described with reference to FIG. 4, the contact surface between the subject and the sleep state determination device 11a is reduced when the sleeping phase of the subject is sideways or when the user's body is only partially on the sensor mat. It becomes impossible to detect body movement. Therefore, the amplitude of the waveform between about 1: 5 and about 3 o'clock becomes small, and it can be seen that the subject is sleeping with the sleeping phase sideways. In addition, since it becomes difficult for the sleep state determination apparatus 11a to detect a test subject's vibration during this period, bed data is mottled. However, for example, by adjusting a reference value for generating occupancy data in the data generation unit 63, it is possible to detect the biological information of the subject.
[0084]
The in-bed data again becomes discontinuous from around 3:00 to around 3:10, and a signal having no amplitude appears with a waveform having a large amplitude before and after. In addition, a signal indicating body motion appears in the body motion data across a discontinuous portion of the occupancy data. For this reason, the subject temporarily left the bed at about 3 o'clock and entered the bed at about 3:10. After that, from around 3:10 to around 3:35, a signal indicating body movement appears in the body movement data, and a signal with a large amplitude appears. It is thought that he was moving in the bedding.
[0085]
At around 3:10, the subject falls asleep after entering the bed, but the waveform after falling asleep becomes a waveform having substantially the same amplitude as that of the waveform appearing from 20:00 to around 20:50, for example. ing. Therefore, after getting out and getting in again, the subject goes to bed in the same sleep phase as when he first got in. At this time, a signal indicating continuous presence appears in the presence data, and a signal indicating body movement does not appear in the body movement data.
[0086]
As shown in FIG. 13, the subject who fell asleep around 3:10 continues to sleep until around 5:20. From about 5:20, a waveform with a large amplitude appears, and it can be read that the subject has awakened. At this time, a discrete signal appears partially in the occupancy data as the user enters the floor, and a discrete signal indicating the body movement from entering the bed to falling asleep appears in the body movement data. After the subject awakes, it can be read that the subject has left the bed at about 5:25, as described above with reference to FIG. As a result of getting out of bed, there is no signal indicating the presence of the floor after 5:25 in the presence data, and no signal indicating the movement of the body is present in the body movement data.
[0087]
Note that a waveform having a large amplitude temporarily appears around 6 o'clock, and accordingly, a signal indicating bed and a signal indicating body movement appear in the bed data temporarily. Yes. As described with reference to FIG. 4, from the waveform having a large amplitude after leaving the bed, for example, it is considered that the subject placed an object on the bedding when changing clothes.
[0088]
Using such occupancy data indicating the presence or absence of the subject, it is possible to easily know the presence or departure of the subject. Furthermore, since the body motion data simply indicates whether the subject is in bed or has left the bed, it is possible to reliably grasp the subject's bed or bed. Thereby, the sleep state determination apparatus 11a can reliably determine whether the subject is in bed or out of bed, and can generate an alarm with high accuracy. And since a subject's bed presence or bed leaving is judged simply and reliably, a reliable safety confirmation service can be provided accurately.
[0089]
Furthermore, the presence or absence of the subject's body movement can be easily known using the body movement data indicating the body movement of the subject. Therefore, it is possible to surely know the subject's bed or bed leaving using not only the bed data but also the presence or absence of body movement as an auxiliary. Furthermore, by using the measurement data measured by the sleep state determination device 11a, it is possible to know the subject's bed or bed leaving more reliably. The sleep state of the subject can be known from the amplitude of the waveform based on the measurement data measured by the sleep state measurement device 11a, and it is possible to realize a precise and reliable safety confirmation service.
[0090]
Next, a sleep monitoring system using the sleep state determination device 11a in the present embodiment will be described. Here, a safety confirmation service for confirming the safety of a user who uses the sleep monitoring system will be described. In particular, in the present embodiment, a safety confirmation service for confirming the safety of a user at night will be described, but the safety confirmation service can be similarly implemented even in the daytime.
[0091]
The details of the configuration of the bedtime monitoring system in the present embodiment will be described with reference to FIG. FIG. 14 is a block diagram illustrating a configuration example of a bedtime monitoring system according to the present embodiment.
[0092]
As shown in FIG. 14, the sleep state determination device 11 a provided in the user home 11 includes a data transmission unit 33 in addition to the biological information detection unit 31 and the data analysis unit 32. Further, as shown in FIG. 14, the user home 11 is provided with a data receiving unit 34 and a telephone line control unit 35 for transmitting data to the data receiving center 12.
[0093]
The data transmission unit 33 has a function of transmitting input data to the data reception unit 34. The data reception unit 34 has a function of inputting data received from the data transmission unit 33 to the telephone line control unit 35. The telephone line control unit 35 has a function of transmitting the input data to the telephone line control unit 45 of the management apparatus 12a via the public line 51. The telephone line control unit 35 opens and closes the telephone line for data transmission. The public line 51 is not limited to a telephone line, and may be a communication network such as the Internet or another public network.
[0094]
Next, the management device 12a of the data reception center 12 will be described. As shown in FIG. 14, the management device 12 a of the data reception center 12 includes a control unit 41, an input unit 44, a display unit 43, a telephone line control unit 45, a call unit 48, and a storage unit 42.
[0095]
Furthermore, the mail transmission / reception part 46 which transmits the evaluation determination result regarding a test subject to the external terminal 14a and the portable terminal 14c of a remote family by electronic mail etc. is provided. The storage unit 42 and the mail transmission / reception unit 46 of the data reception center 12 may be physically configured as separate devices, or may be configured as an integrated management device.
[0096]
The control unit 41 has a function of executing control on each component in the management device 12a, and is configured by a CPU, an MPU, and the like. In the management device 12a of the present embodiment, for example, the control unit 41 functions to process measurement data, process bed data or body movement data, and store the processing results in the storage unit 42 such as a memory. Have In addition, the processing result is displayed on the display unit 43.
[0097]
The input unit 44 is input means such as a keyboard and a mouse. The operator of the data reception center 12 uses the input unit 44 to request the mail transmission unit 46 to send a helper dispatch request to a helper station (not shown in FIG. 14) via the communication network. Can do. Further, the operator may directly request the helper to send a dispatch request to the mail transmitting / receiving unit 46 using the input unit 44.
[0098]
The display unit 43 is a display unit such as a liquid crystal display or a CRT. The display unit 43 may be a buzzer that outputs sound when an alarm is received, a patrol light that lights when an alarm is received, or the like. The operator can know the reception of the alarm through the display unit 43. Further, the content of the alarm may be displayed on the display unit 43.
[0099]
The telephone line control unit 45 is a modem or the like, and opens and closes a telephone line for data reception. The call unit 48 is a general communication means such as a telephone or a facsimile. The operator can make a request for helper dispatch to the helper station using the communication unit 48.
[0100]
The storage unit 42 is a storage unit such as a memory or a hard disk for storing various data and various control programs. Moreover, the memory | storage part 42 stores the data produced | generated from the processing result which processed various information, and various control programs. Based on various data stored in the storage unit 42, body temperature and pulse for each subject, respiratory rate, state of sweating, presence / absence of snoring, body movements and other health state data during sleep, bedtime, sleep A life pattern such as time may be calculated and a graph may be displayed on the display unit 43 as trend data.
[0101]
The mail transmission / reception unit 46 transmits / receives mail according to instructions from the control unit 41. Moreover, the mail transmission / reception part 46 can transmit an email automatically to the registered transmission destination according to reception of the warning from a test subject. The mail transmission / reception unit 46 may be provided as a mail server separately from the management apparatus 12a.
[0102]
As shown in FIG. 14, the data reception center 12 includes a web server 47 for the management device 12 a to connect to the communication network 52. The web server 47 is a conventional server and includes, for example, a control unit, a storage unit, and a communication control unit. Moreover, you may provide an input part and a display part. The data receiving center 12 publishes a web page to the family of the subject by the web server 47.
[0103]
The communication network 52 is a communication network such as the Internet or a public network. When connecting to the web server 47 from the outside, only a specific person such as a subject's family can be accessed by inputting a password or the like.
[0104]
The external terminal 14a of the remote family home 14 can be a conventional personal computer. Moreover, the portable terminal 14c which a family has can be used as a conventional portable terminal such as a cellular phone terminal. The external terminal 14 a and the mobile terminal 14 c can be connected to the communication network 52 and can be connected to the web server 47 of the data reception center 12 via the communication network 52.
[0105]
Although not shown in FIG. 14, the helper station is provided with a device that dispatches a helper to the user's home 11 based on a helper dispatch request from the data reception center 12. For example, the helper station is provided with a communication device that communicates with the management device 12a via a telephone or facsimile that receives a helper dispatch request, or a dedicated line or a general communication network. Furthermore, you may provide the information management apparatus which manages the information regarding a helper and the information regarding the relationship between a test subject and a helper in a helper station.
[0106]
The management device 12a may have the same function as the determination unit 65 of the sleep state determination device 11a. In this case, the management device 12a acquires the occupancy data from the sleep state determination device 11a, and determines whether an alarm should be output based on the occupancy data. Moreover, you may further have the function similar to the data generation apparatus 63 of the sleep state determination apparatus 11a. In this case, the management device 12a acquires measurement data from the sleep state determination device 11a, generates occupancy data from the measurement data, and thereafter performs the same determination.
[0107]
In addition, the operator analyzes whether there is an abnormality based on the measurement data, bed data, body movement data, information obtained from a separate questionnaire, etc. transmitted from the sleep state determination device 11a of the user's home 11. It may be judged and evaluated. In this way, when the operator makes a judgment and evaluation, the analysis result obtained by transmitting the data to the family doctor of the subject may be taken into consideration.
[0108]
Next, various data stored in the storage unit 42 of the management device 12a will be described. The information regarding the test subject stored in the memory | storage part 42 of the management apparatus 12a is demonstrated using FIG.
[0109]
As shown in FIG. 15, the storage unit 42 of the management device 12a has user attributes, family attributes, time data, presence data, body movement data, alarm data, event data, comment data, photo data, status data, A database (user DB) related to the subject such as measurement data is stored.
[0110]
“User attribute” is general information of the user such as the user's ID number, name, age, date of birth, blood type, telephone number and address of the user's house 11, and mail address. Furthermore, as “user attributes”, a history of illnesses that have occurred so far, past illnesses, contact information of helper stations in the safety confirmation service, and the like are stored.
[0111]
The “family attribute” is general information of a remote family such as a name, a telephone number and address of the family house 14, and an e-mail address. In addition, the time when the management device 12a receives data from the sleep state determination device 11a is stored as “time data”.
[0112]
The “in-bed data” is data indicating the in-bed or out-of-bed of the subject generated by the sleep state determination device 11a as described above. “Body motion data” is data indicating the body motion generated by the sleep state determination device 11a as described above.
[0113]
“Alarm data” is data relating to an alarm output from the sleep state determination device 11a as described above. For example, as “alarm data”, “power ON” issued when the sleep state determination apparatus 11a is turned on, “no alarm” when no data is received and no alarm is issued, and issued when the user is absent for a long time. "Long-term absence" warning, "Long-term bed" alarm issued when staying for a long time, "Continuation of body movement" alarm issued when constant body movement continues for a long time are stored .
[0114]
“Event data” is data relating to a method of confirming safety with respect to a received alarm. The management device 12a receives the alarm and contacts the subject by telephone or the like to confirm safety. At this time, when the safety of the subject can be confirmed, the operator inputs “callback confirmation” indicating the safety confirmation by the callback. In addition, when it is impossible to confirm the safety of the subject, the operator inputs a “helper application check” indicating the helper dispatch requested to the helper station.
[0115]
“Comment data” is data relating to a result report for safety confirmation. For example, when the subject's safety can be confirmed by "callback confirmation", the operator inputs the contents heard from the subject, and when the subject's safety can be confirmed by "calling confirmation", the operator receives from the helper Enter the contents of the report result.
[0116]
“Photo data” is a photograph of the subject that is taken when the helper confirms the safety by performing the “confirmation check”. In addition, a photo registered when receiving the safety confirmation service is also stored as “photo data”.
[0117]
“Status data” is data indicating the current state of the sleep state determination device 11a. For example, “Waiting for monitoring” is stored while waiting for reception of data and alarms, and “Checking by receiving alarms” is stored while receiving safety and confirming safety. Is done. “Measurement data” is measurement data generated from a detection signal detected by the sleep state determination device 11a as described above.
[0118]
The measurement data, bed data, and body movement data measured over a long period of time can be stored in the management device 12a, not limited to the various types of information shown in FIG. This makes it possible to analyze the characteristics of the subject (for example, snoring when entering a deep sleep, body movements exceeding a certain number of times, etc.). For example, you may make it have the function to set the threshold value judged to be abnormal for every test subject based on the correlation between sleep and a heart rate, an average respiration rate, etc. Thereby, the judgment according to the characteristic of each subject can be performed correctly.
[0119]
Next, the processing flow of the safety confirmation service performed by the sleep monitoring system will be described using FIG. 17 with reference to FIG. FIG. 17 is a flowchart illustrating an example of a processing flow of a safety confirmation service by the bedtime monitoring system.
[0120]
As shown in FIG. 17, at the user's home 11, for example, the subject switches the sleep state determination device 11 a from the OFF state to the ON state. Then, a “power ON alarm” is transmitted to the management device 12a of the data reception center 12 indicating that the subject's sleep state determination device 11a has been turned on (S100). Thereby, the management apparatus 12a of the data reception center 12 will be in the state of waiting for reception which receives the data from the sleep state determination apparatus 11a.
[0121]
When the subject turns on the power, the sleep state determination device 11a starts data detection / measurement (S101). The measurement data measured by the sleep state determination state 11a is stored in the storage unit 66 of the sleep state determination device 11a. In addition, bed data and body movement data are generated by the data generation unit 63 of the sleep state determination device 11 a and stored in the storage unit 66.
[0122]
Then, the determination unit 65 determines the occurrence of an abnormality based on the occupancy data (S102). When the determination unit 65 determines that an abnormality has occurred, an alarm is transmitted to the management device 12a of the data reception center 12 (S104). At this time, measurement data may be transmitted together with an alarm.
[0123]
If no abnormality occurs in the subject 11b, the process waits for a preset transfer time to transfer the measured data to the management device 12a (S103). When it is time to transfer data, the sleep state determination device 11a transmits measurement data, occupancy data, and body movement data from the data transmission unit 33 to the data reception unit 34, and further from the telephone line control unit 35 to the management device 12a. Transmit (S105). The data to be transmitted may be measured and generated, stored in the storage unit 66, and transferred to the management device 12a at the same time. If the preset transfer scheduled time is not reached, the sleep state determination device 11a further measures and stores data (S101).
[0124]
The management device 12a of the data reception center 12 receives data transmitted every transfer time and an alarm when an abnormality occurs (S111). The management device 12a stores the received data in the storage unit 42. At the same time, the web page of the web server 47 is automatically updated (S112).
[0125]
And when not receiving an alarm, the management apparatus 12a returns to the state of waiting for reception which receives data and an alarm from a test subject's sleep state determination apparatus 11a, and a processing flow is complete | finished (S114).
[0126]
When the management device 12a receives the warning together with the data, the management device 12a transmits a notification that the warning has been received from the subject to the family 14b of the subject who sent the warning (S115). For example, the management device 12a automatically transmits the date and time of receiving the alarm, the name of the subject, the name of the alarm, the content of the alarm, and the like to the portable terminal 14c and the external terminal 14a of the family 14b by e-mail. At this time, the management device 12a simultaneously transmits to the family 14b sleep information such as a pulse, a heartbeat, and a respiratory rate during sleep immediately before receiving the abnormality occurrence alarm.
[0127]
As described above, when the management device 12a receives an alarm, the communication is transmitted to the family 14b, so that the family 14b can know that an abnormality has occurred in the subject. Moreover, since the management apparatus 12a automatically transmits information related to reception of the alarm, the information can be quickly transmitted to the family 14b.
[0128]
In response to the alarm received by the management device 12a, the operator 12b of the data reception center 12 uses the communication unit to notify the user of whether an abnormality has occurred or what abnormality has occurred. 11a. Then, the operator 12b confirms the safety of the subject (S117).
[0129]
When the operator 12b can confirm the safety of the subject, the subject confirms the content of the alarm and the status of the abnormality that has occurred. Thereafter, the confirmation result heard by the operator 12b from the subject is input to the database of the storage unit 42. At the same time, the contents of the alarm, the confirmation result, etc. are transmitted to the subject's family 14b by e-mail, for example. These confirmation results are input to the database of the storage unit 42 and are automatically written and updated on the web page by the management device 12a (S118).
[0130]
When the operator 12b cannot confirm the safety of the subject, the operator 12b requests the helper station 13 to call out a helper for confirming the site of the user's home 11 (S120). At this time, for example, the operator 12b of the data receiving center 12 requests the helper station 13 to inform the helper station 13 that the subject's safety could not be confirmed by telephone. Upon receiving this request, the helper station 13 dispatches the helper for on-site confirmation (S131). At this time, for example, the helper station 13 confirms the helper schedule and designates the optimum helper to be rushed to. As an example of the nomination criteria for this helper, there are compatibility between the subject and the helper, the number of dispatches to the subject, requests from the subject, and the like.
[0131]
A helper arrives at the user's home 11 and confirms the site. When abnormality occurs in the subject, the occurrence of abnormality and the state of abnormality are reported to the data reception center 12 (S133). Then, the helper deals with the abnormal situation according to the abnormal situation (S134), and then reports the result to the data reception center 12 (S135). For example, the helper takes a photograph of the subject, and sends a result report together with the photograph of the subject from the helper's portable terminal to the management device 12a by e-mail. Further, this result report may be made orally by telephone or the like to the operator 12b of the data reception center 12.
[0132]
When the management device 12a of the data reception center 12 receives the result report after the on-site confirmation from the helper, it stores the result report in the storage unit 42 (S122). At this time, the management device 12a may automatically write in the database of the storage unit 42, or the operator 12b may input via the input unit 44. The result report from the helper is stored in the storage unit 42 of the management device 12a and written to the web page of the web server 47 (S122). Thereby, the web page of the web server 47 is updated.
[0133]
Then, a result report from the helper is sent to the family 14b (S122). At this time, it is transmitted by e-mail from the management device 12a to the external terminal 14a and the portable terminal 14c of the family 14b. The result report to the family 14b may be made verbally by telephone or the like. And the management apparatus 12a returns to the state of waiting for reception which receives data and a warning from a test subject's sleep state determination apparatus 11a, and a processing flow is complete | finished (S123).
[0134]
The sleep state determination device 11a may transmit each piece of data to the management device 12a of the data reception center 12 in real time, and the management device 12a and the operator 12b of the data reception center 12 may determine that an abnormality has occurred. Even in this case, the sleep state determination device 11a can determine the occurrence of abnormality together with the operator 12b of the data reception center 12. Thereby, a test subject's abnormality can be determined rapidly with sufficient accuracy.
[0135]
Finally, an example of data viewed by the family 14b on the web page will be described with reference to FIGS. FIG. 18 is a schematic diagram illustrating an example of a screen opened by the family 14b. FIG. 19 is a schematic diagram illustrating another example of a screen opened by the family 14b. The data that the family 14b browses on the web page is created based on various data stored in the management device 12a as shown in FIG.
[0136]
Corresponding to data stored in the management device 12a as data to be disclosed on the web page, for example, user designation, subject's family name, measurement data, bed data and body movement data, event data, comment data, Photo data, status data, etc. In addition, in order to protect the personal information of the subject, the family 14b accesses the web page to access the web server 47 of the data reception center 12 and browse the web page.
[0137]
As shown in FIG. 18, the family 14b can open the “sleeping data report” on the browser by connecting to the management device 12a of the data reception center 12 from the external terminal 14a or the portable terminal 14c in the family home 14. At this time, it is possible to connect via a general communication network such as the Internet, and the family 14b can connect to the web server of the management apparatus 12a using various browsers. Here, the “sleeping data report” is data in which sleeping information collected from the subject by the data reception center 12 is collectively described.
[0138]
On the “sleeping data report”, for example, personal information such as the user ID of the subject, the name of the user, the name of the contractor contracted to receive the safety service, and the address of the subject are described. These pieces of information are stored in the storage unit 42 of the management device 12a. Further, the “sleeping data report” includes data indicating the sleeping state of the subject.
[0139]
For example, in FIG. 18, sleep data indicating a sleep state obtained by synthesizing the bed data and the body movement data in FIG. 5 is described in time series. Also, in FIG. 18, events “absence alarm” and “safety confirmation” indicating the time when there was an absence alarm or safety confirmation in the sleep state are described. These events are linked, for example, as bookmarks, and can be moved to a page showing detailed information by clicking “absence alarm” or “safety confirmation”.
[0140]
FIG. 19 shows an example of an “event report page” linked to “absence alarm” and “safety confirmation”. Here, the “event report page” is a page on which details relating to an alarm, safety confirmation, etc. are described. The linked page describes the meaning of the alarm, the time of occurrence, and the like. The linked page includes the confirmed report result, comments from the subject who issued the alarm, photographs of the subject after confirming safety, etc., and the family 14b obtains detailed information on these events. be able to.
[0141]
For example, in FIG. 19, it is described that there was a “long-term bed warning”. “Report content” contains a result report after safety confirmation for the alarm. From this “report content”, the operator 12b of the data reception center 12 can confirm that the subject has “snaked in a kotatsu” and “long-term bed warning” as a result of confirmation by telephone. And the family 14b can know that a test subject's health condition is favorable and there is no abnormality.
[0142]
Further, for example, as shown in FIG. 19, a photograph of a subject who is smiling with a smile after confirming safety is posted on the “event report page”, and the family 14b can confirm that the subject has no abnormality. This photograph of the subject is taken by a person who went to the user's home 11 to confirm the safety of a helper or the like and informs the safety confirmation of the subject. In other words, when a helper or the like can confirm the safety of the subject, the photograph of the subject is posted on the “event report page”. Further, when the operator 12b of the data reception center 12 can confirm the safety by using the telephone call unit, the subject himself / herself may take a picture and transmit it to the data reception center 12. Thus, by posting the test subject's photograph on the “event report page”, the family 14b can confirm the test subject's situation and can be relieved that there was no abnormality.
[0143]
In the web page shown in FIGS. 18 and 19, for example, measurement data, bed data, and body movement data may be expressed by a bar graph, a pie chart, a table, and the like so that they can be easily understood visually. In this case, it is possible to make the information easier to see and familiar to the family 14b of the subject who does not have specialized knowledge. Furthermore, by making the information easy to see and familiar, it is possible to provide not only a detailed safety confirmation service for the subject but also a detailed safety confirmation service for the family 14b.
[0144]
As described above, in the sleep monitoring system according to the present embodiment, the sleep state determination device 11a determines the abnormality of the subject and outputs an alarm. At this time, the presence or absence of the subject can be determined easily and reliably using the in-bed data and body movement data created from the measurement data. In particular, since the subject's abnormality is determined based on whether the bedtime and the bed leaving time are equal to or longer than the reference time, the subject's abnormality can be determined accurately and easily.
[0145]
Furthermore, by using body movement data and measurement data together with the occupancy data, the subject's occupancy or getting out of bed can be known with high accuracy. In addition, when body motion data or measurement data is used, it is possible to grasp information regarding a more detailed sleep state of the subject. By using such a sleep state determination device 11a, it is possible to provide a detailed safety confirmation service simply, accurately, and with high accuracy.
[0146]
The sleep state determination device 11a detects and measures vibration and biological information within the subject's unconscious and non-invasive manner, thereby providing the safety confirmation service without mentally burdening the subject. . Therefore, since the subject automatically outputs an alarm without issuing an alarm when he / she is abnormal, he / she can always spend his / her daily life with peace of mind.
[0147]
【The invention's effect】
ADVANTAGE OF THE INVENTION According to this invention, the sleep state determination apparatus which can determine a test subject's abnormality accurately, and the bedtime monitoring system which persons other than a test subject can confirm a test subject's abnormality simply can be provided.
[Brief description of the drawings]
FIG. 1 is a block diagram illustrating a configuration example of a sleep state determination apparatus according to an embodiment of the present invention.
FIG. 2 is a schematic diagram illustrating a configuration example of a sleep state determination apparatus according to an embodiment of the present invention.
FIG. 3 is a block diagram illustrating a configuration example of a data analysis unit of the sleep state determination apparatus according to the embodiment of the present invention.
FIG. 4 is a waveform diagram showing an example of measurement data measured by the sleep state determination device according to the embodiment of the present invention.
FIG. 5 is a schematic diagram showing an example of occupancy data and body movement data created by the sleep state determination apparatus according to the embodiment of the present invention.
FIG. 6 is a schematic diagram showing an alarm transmitted from the sleep state determination device according to the embodiment of the present invention.
FIG. 7 is a flowchart illustrating an example of a processing flow in which the sleep state determination device according to the embodiment of the present invention outputs an alarm.
FIG. 8 is a schematic diagram showing an example of occupancy data generated by the sleep state determination apparatus according to the embodiment of the present invention.
FIG. 9 is a schematic diagram showing an example of occupancy data generated by the sleep state determination apparatus according to the embodiment of the present invention.
FIG. 10 is a waveform diagram showing measurement data measured by the sleep state determination apparatus according to the embodiment of the present invention, a pattern diagram showing bed data and body movement data.
FIG. 11 is a waveform diagram showing measurement data measured by the sleep state determination apparatus according to the embodiment of the present invention, a schematic diagram showing bed data and body movement data.
FIG. 12 is a waveform diagram illustrating an example of measurement data measured by the sleep state determination device according to the embodiment of the present invention, and a schematic diagram illustrating an example of bed data and body movement data.
FIG. 13 is a waveform diagram illustrating an example of measurement data measured by the sleep state determination apparatus according to the embodiment of the present invention, and a schematic diagram illustrating an example of bed data and body movement data.
FIG. 14 is a block diagram illustrating a configuration example of a bedtime monitoring system according to an embodiment of the present invention.
FIG. 15 is a schematic diagram illustrating an example of data stored in the management device according to the embodiment of the present invention.
FIG. 16 is a schematic diagram showing a processing flow of the bedtime monitoring system in the embodiment of the present invention.
FIG. 17 is a flowchart showing an example of a processing flow of the bedtime monitoring system in the embodiment of the present invention.
FIG. 18 is a schematic diagram showing an example of a screen opened by a remote family in the embodiment of the present invention.
FIG. 19 is a schematic diagram showing an example of a screen opened by a remote family in the embodiment of the present invention.
[Explanation of symbols]
11 user home, 11a sleep state determination device, 11b user, 12 data receiving center, 12a management device, 12b operator, 13 helper station, 14 family home, 14a external terminal, 14c mobile terminal, 31a fluid inclusion body, 31b air Tube, 31c Biological information detection unit, 32 Data analysis unit, 33 Data transmission unit, 34 Data reception unit, 35 Telephone line control unit, 36 Calling unit, 41 Control unit, 42 Storage unit, 43 Display unit, 44 Input unit, 45 Telephone line control unit, 46 Mail transmission / reception unit, 47 Web server, 48 Calling unit, 51 Public line, 52 Communication network, 61 Signal input unit, 62 Band pass filtering unit, 63 Control unit, 65 Storage unit, 66 Display unit

Claims (4)

A sleep state determination device for determining an abnormality of a subject,
Detecting means for detecting sleep information from a device installed in the subject's bedding;
Based on the sleep information of the subject detected by the detection means, occupancy information generating means for generating occupancy information indicating whether the subject is in bed or leaving the bed;
Body motion data generating means for creating body motion data based on the amplitude of the signal indicating the measurement data of the device installed in the subject's bedding;
In the case of nighttime as a time zone for determining the abnormality of the subject based on the bed information generated by the bed information generation means, the longest bedtime of the day is averaged for a predetermined number of days in the past. In the case of daytime, in the case of daytime, the average bedtime obtained by averaging the longest bedtime of the day for a predetermined number of past days is set as a predetermined monitoring time, and the average bedtime is Calculating that the bed leaving time shorter than the predetermined time is present, calculating the average bed leaving time as leaving the floor time shorter than the predetermined time, and the subject A determination means for determining whether or not the subject has been in bed or getting out of bed for a predetermined reference time within the monitoring time, and outputting a warning when the subject has been in bed or out of bed for more than the reference time;
A sleep state determination apparatus comprising: an output unit that outputs an alarm when body movement continues over a predetermined number of times within a predetermined time based on the body movement data generated by the body movement data generation unit. A sleep state determination device for determining an abnormality of a subject,
Detecting means for detecting sleep information from a device installed in the subject's bedding;
Based on the sleep information of the subject detected by the detection means, occupancy information generating means for generating occupancy information indicating whether the subject is in bed or leaving the bed;
Body motion data generating means for creating body motion data based on the amplitude of the signal indicating the measurement data of the device installed in the subject's bedding;
In the case of night time as the time for determining the abnormality of the subject based on the bed information generated by the bed information generating means, the reference time used for the determination of getting out is set for a predetermined past number of days. Calculated based on either the average bedtime that averaged the bedtime, the longest bedtime in the past for a predetermined number of days, or the time that does not include the bedtime on the day the alarm was output, In the case of daytime, the standard time used for the determination of bedtime is the average bedtime obtained by averaging the bedtime for a predetermined number of days in the past, and the past bedtime for a predetermined number of days. Calculated based on either the longest bedtime or the time that does not include bedtime on the day when the alarm is output, and the subject continues for a predetermined reference time or more at a predetermined monitoring time. In bed And determining means for determining whether the lifting, and outputs a warning when the subject is the bed or lifting or the reference time,
A sleep state determination apparatus comprising: an output unit that outputs an alarm when body movement continues over a predetermined number of times within a predetermined time based on the body movement data generated by the body movement data generation unit. A sleep state determination device for determining an abnormality of a subject,
Detecting means for detecting sleep information from a device installed in the subject's bedding;
Based on the sleep information of the subject detected by the detection means, occupancy information generating means for generating occupancy information indicating whether the subject is in bed or leaving the bed;
Body motion data generating means for creating body motion data based on the amplitude of the signal indicating the measurement data of the device installed in the subject's bedding;
Based on the bed information generated by the bed information generation means, in the case of night time as a time zone for determining the abnormality of the subject, a day in which the bed leaving time is shorter than the reference time by a predetermined time is determined in advance. In the case of daytime, the day when the bedtime is shorter than the reference time by a predetermined time or more is set to a predetermined number of days or more. In the case of continuous, the reference time is set shorter by a predetermined time to be a predetermined monitoring time, and the reference time of the day following the day when the alarm is output is set as the day when the alarm is output. set the predetermined time duration longer than the reference time, the subject is determined whether or not to continue to the bed or lifting predetermined reference time or longer within the monitoring time, the subject is the reference A judging means for outputting an alarm when above the bed or ambulation between,
A sleep state determination apparatus comprising: an output unit that outputs an alarm when body movement continues over a predetermined number of times within a predetermined time based on the body movement data generated by the body movement data generation unit. A sleep monitoring system comprising the sleep state determination device according to any one of claims 1 to 3 and a monitoring device that monitors a subject's abnormality,
The sleep state determination device
A transmission means for transmitting at least an alarm and occupancy information to the monitoring device;
The monitoring device comprises:
Receiving means for receiving the alarm and occupancy information transmitted from the transmitting means;
A bedtime monitoring system comprising: a registrant's terminal registered in advance, wherein the presence information can be browsed, and a notification unit that notifies the alarm in response to the reception of the alarm by the reception unit.

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