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WO1997014958A1 - Analyse typologique - Google Patents

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Publication number
WO1997014958A1
WO1997014958A1 PCT/GB1996/002490 GB9602490W WO9714958A1 WO 1997014958 A1 WO1997014958 A1 WO 1997014958A1 GB 9602490 W GB9602490 W GB 9602490W WO 9714958 A1 WO9714958 A1 WO 9714958A1
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WO
WIPO (PCT)
Prior art keywords
outputs
ofthe
sensitive method
concentration
intensity
Prior art date
Application number
PCT/GB1996/002490
Other languages
English (en)
Inventor
Krishna Chandra Persaud
Original Assignee
Aromascan Plc
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Aromascan Plc filed Critical Aromascan Plc
Priority to AU72237/96A priority Critical patent/AU7223796A/en
Publication of WO1997014958A1 publication Critical patent/WO1997014958A1/fr

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Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/0004—Gaseous mixtures, e.g. polluted air
    • G01N33/0009—General constructional details of gas analysers, e.g. portable test equipment
    • G01N33/0027—General constructional details of gas analysers, e.g. portable test equipment concerning the detector
    • G01N33/0031—General constructional details of gas analysers, e.g. portable test equipment concerning the detector comprising two or more sensors, e.g. a sensor array

Definitions

  • This invention relates to the use of cluster analysis in chemical sensing, in particular to the use of intensity data in such analyses in order to provide information regarding chemical concentrations.
  • 'gas sensing' comprises the detection of any chemical in the gas phase, including odours and volatile species].
  • One approach is to employ, within a single gas sensing device, an array of gas sensors which use semiconducting organic polymers (SOPs) as the active sensing material (see, for example, Persaud K C, Bartlett J G and Pelosi P, in 'Robots and Biological Systems : Towards a new bionics?', Eds. Darios P, Sandini G and Aebisher P, NATO ASI Series F : Computer and Systems Sciences JU22 (1993) 579). Transduction is accomplished by measuring changes in the dc resistance ofthe sensors, these changes being induced by the abso ⁇ tion of gaseous species onto the SOPs.
  • SOPs semiconducting organic polymers
  • the sensors are selected so as to exhibit differing but overlapping responses to a variety of gases, and therefore the output of an array of sensors is a pattern of response characteristic ofthe gas or gases detected. Since the number of sensors in an array is typically rather large - AromaScan pic manufacture devices having 20 and 32 sensor arrays - it can be said that these patterns are projected into multi-dimensional space of high order. Human vision is very good at recognising structural relationships within two and three dimensional space; however, in multi-dimensional space the perception of such relationships is extremely difficult. Therefore, in order for a human to examine complex multi-dimensional data, it is extremely useful to map such data from the high dimensional pattern space in which they are originally presented onto a low (two or three) dimensional pattern space.
  • Linear mapping algorithms are used frequently for reasons of simplicity and generality. Such algorithms have been used in gas and odour classification as well as in chemical data classification in order to reduce multi-dimensional pattern space to two or three dimensional space.
  • Gardner et al Gardner J W and Bartlett P N, Sensors and Actuators B 18-19 (1994) 221 and references therein
  • PC A principal component analysis
  • K-L Karhunen-Loeve
  • Ballantine Jr et al (Ballantine Jr. D S, Rose S L, Grate J W and Wohltjen H, Anal.Chem., 5_£ (1986) 3058) classified vapours using the PCA method and the (K-L) projection.
  • the K-L projection was used in odour classification by Abe et al (Abe H, Kanaya S, Takahashi Y and Sasahi S-I, Analytica Chemica Acta 215 G988) 155) and Nakamoto et al (Nakamoto T, Fukuda A, Morizumi T and Asakura Y, Sensors and Actuators B, 3_ (1991) 221) who investigated the odour of whisky data sets.
  • Kowalski and Bender (Kowalski B R and Bender C F, J Amer.Chem. Soci., 95.3 (1973) 686) employed a similar linear mapping technique, with eigenvector projection, for displaying chemical data.
  • Non-linear mapping algorithms may be used when linear mapping is unable to preserve complex data structures - which is, in fact, commonly the case with 'real life' data.
  • Non-linear techniques have complicated mathematical formulations compared to linear mapping, and are rarely used for gas classification.
  • the responses ofthe array of sensors employed in the aforementioned AromaScan systems represent non-linear, multi-dimensional pattern structures, which (when normalised) contain the concentration independent pattern data sets describing different gases.
  • non-linear mapping techniques are more applicable than linear techniques. It should be noted that truly concentration independent patterns are generated only when the concentration-response relationship is linear.
  • a particularly useful form of non-linear mapping is the algorithm of Sammon Jr.
  • prior art cluster analyses are essentially devoid of information regarding chemical concentration. This is because the cluster analysis is performed on patterns: raw sensor data - the intensity of which is related to chemical concentration - is scaled in an appropriate manner before cluster analysis. In instances where the concentration-sensor response relationship is non-linear, a pattern cluster will be skewed. In this sense the cluster analysis contains concentration information, but no direct use is made of absolute intensity data, and the effect is rather difficult to observe except at high concentrations/non-linearities.
  • the present invention overcomes the aforementioned difficulties by employing intensity information in cluster analyses in order to extract information on chemical concentration. Such fundamental information is frequently desirable, for instance, in the recognition of dangerously high levels of a toxic substance. It should be noted that whilst the invention is primarily directed towards the sensing of gaseous species, the approach is applicable to any area of chemical sensing where the sensing device produces a plurality of outputs which require some form of cluster analysis.
  • a concentration sensitive method for analysis of a plurality of outputs from a chemical sensing device comprising the steps of : normalising said plurality of outputs; calculating at least one intensity output, each intensity output being related to the absolute magnitude of at least one of said plurality of outputs; and performing a cluster analysis ofthe plurality of normalised outputs and the intensity output or outputs.
  • the intensity output, or outputs, may be weighted by a scaling factor.
  • the cluster analysis may comprise a non-linear mapping technique, and this technique may be the Sammon algorithm or a variant thereof.
  • a mathematical model of the results of the cluster analysis may be employed in order to derive quantitative concentration data.
  • intensity output which is the mean of the moduli of the plurality of outputs.
  • intensity outputs may be a plurality of intensity outputs wherein each of said intensity outputs comprises the absolute magnitude of an individual output.
  • the chemical sensing device may be a gas sensing device comprising at least one semiconducting organic polymer (SOP) based sensor, and the gas sensing device may further comprise an array of SOP based sensors wherein the outputs ofthe device correspond to changes in the dc resistance of said sensors.
  • SOP semiconducting organic polymer
  • Figure 1 is a two dimensional cluster map
  • Figure 2 is a graph of sensor response across an array often sensors.
  • the present invention is a concentration sensitive method of analysis of a plurality of outputs from a chemical sensing device comprising the steps of : normalising said plurality of outputs; calculating at least one intensity output, each intensity output being related to the absolute magnitudes of at least one of said plurality of outputs; and performing a cluster analysis ofthe plurality of normalised outputs and the intensity output, or outputs.
  • FIG. 1 A non-limiting example is provided by gas sensing devices of the type manufactured by AromaScan pic, which comprise an array of SOP sensors. Transduction is accomplished by measuring the changes in sensor dc resistances produced by exposure ofthe sensors to a gas or a mixture of gases.
  • Figure 2 depicts a generalised response of an array often such sensors to a gas, the response comprising a plurality of outputs 20-38. The outputs 20-38 are recorded as ⁇ R/R, the fractional change in resistance, where R is the base resistance of a sensor is clean air and ⁇ R is the change in resistance. It should be noted that an output may be negative.
  • the absolute magnitude of a ⁇ R/R response i.e. the modulus
  • increases with increasing concentrations of the detected gas; one embodiment of the present invention utilises this fact by introducing to the cluster analysis an 'intensity' output which is related to the absolute magnitudes of the plurality of outputs 20-38. It is convenient to calculate the absolute mean intensity ofthe response.
  • Concentration independent pattems are produced by normalising the outputs 20-38 of the sensor array.
  • the normalisation is performed by calculating the percentage fractional change in resistance for each sensor over the entire array. This given by equation (1) :
  • n 10 in the present example.
  • the normalised outputs together with the intensity output are subjected to cluster analysis, the intensity output being scaled so that it is either comparable to the normal range of number present in pattern information or greater, so that the cluster analysis is biased towards intensity rather than pattern information.
  • the scaling or weighting factor may be user determined.
  • non-linear Sammon mapping technique represents a preferred class of cluster analysis in the case of SOP based sensor arrays for gas detection.
  • other forms of cluster analysis linear or non ⁇ linear
  • principal component analysis or variants such as factor analysis may also be applied. Indeed, such forms may prove preferable in other chemical sensing applications.
  • a single intensity output representing the absolute mean intensity of output response
  • An altemative approach which is also within the scope of the invention , is to utilise a number of intensity outputs, each intensity output representing the absolute magnitude of a single selected sensor output.
  • the intensity outputs may be scaled by suitable weighting factors. It should be noted that generally when SOP based sensors of the type described above are exposed to a single gas, the concentration-response relationship is linear over a wide range of gas concentrations.
  • the concentration response relationship may be non ⁇ linear, even if the mixture composition remains constant as the concentration varies. This phenomenon is due to competition for adso ⁇ tion between compounds of differing binding affinities, since this competition is dependent on the concentrations of the compounds. At low concentrations compounds with the highest binding affinities are adsorbed onto the SOPs; and therefore the sensors are only responsive to these compounds. (The modulation of sensor resistance is due to - as yet not fully characterised - changes in SOP electronic structure and charge distribution caused by the adso ⁇ tion of gases). As concentrations increase, compounds of lower binding affinity, begin to compete for binding. Therefore, normalised response pattems recorded at different concentrations will differ in appearance.
  • cluster analysis gives rise to a streak, rather than a tight cluster.
  • the cluster analysis contains some information on chemical concentration, but any effect is difficult to observe at low concentrations.
  • intensity data in the cluster analysis results in concentration dependent mapping in which it is easy to visually distinguish one point from another on the basis of concentration.
  • a further aspect ofthe present invention is the extraction of quantitative concentration data from the results ofthe cluster analysis. Since the distances between points are proportional to concentration, it is possible to apply an appropriate mathematical model (such as a polynomial fit), to the data in order to inte ⁇ olate or extrapolate unknown pattems and thereby extract concentrations.
  • an appropriate mathematical model such as a polynomial fit
  • the plurality of outputs used in the cluster analysis need not emanate from an array of sensors.
  • UK Patent GB 2 203 553 B discloses a SOP based sensor used in conjunction with an ac transduction technique. In this instance, it may be desirable to measure changes in impedance characteristics at a plurality of ac frequencies : in this way, a single sensor may provide the plurality of outputs.
  • the outputs of arrays of chemical sensors used to monitor liquid analytes may also be amenable to the cluster analysis described herein.

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  • Chemical & Material Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Engineering & Computer Science (AREA)
  • Health & Medical Sciences (AREA)
  • Analytical Chemistry (AREA)
  • Food Science & Technology (AREA)
  • Medicinal Chemistry (AREA)
  • Physics & Mathematics (AREA)
  • Combustion & Propulsion (AREA)
  • Biochemistry (AREA)
  • General Health & Medical Sciences (AREA)
  • General Physics & Mathematics (AREA)
  • Immunology (AREA)
  • Pathology (AREA)
  • Investigating Or Analyzing Materials By The Use Of Electric Means (AREA)
  • Investigating Or Analyzing Materials By The Use Of Fluid Adsorption Or Reactions (AREA)

Abstract

Cette invention concerne un procédé de détection par concentration permettant d'analyser plusieurs sorties d'un dispositif de détection chimique. Ce procédé consiste à normaliser lesdites sorties, à calculer au moins une sortie d'intensité qui soit associée à la magnitude absolue d'au moins une desdites sorties, et à effectuer une analyse typologique desdites sorties normalisées et de la ou des sorties d'intensité.
PCT/GB1996/002490 1995-10-14 1996-10-11 Analyse typologique WO1997014958A1 (fr)

Priority Applications (1)

Application Number Priority Date Filing Date Title
AU72237/96A AU7223796A (en) 1995-10-14 1996-10-11 Cluster analysis

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
GBGB9521089.4A GB9521089D0 (en) 1995-10-14 1995-10-14 Cluster analysis
GB9521089.4 1995-10-14

Publications (1)

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WO1997014958A1 true WO1997014958A1 (fr) 1997-04-24

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WO (1) WO1997014958A1 (fr)

Cited By (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP1019536A4 (fr) * 1997-08-15 2002-08-14 Affymetrix Inc Detection des polymorphismes a l'aide de la theorie des grappes
US7034677B2 (en) 2002-07-19 2006-04-25 Smiths Detection Inc. Non-specific sensor array detectors
US7129095B2 (en) 2002-03-29 2006-10-31 Smiths Detection Inc. Method and system for using a weighted response
US9202178B2 (en) 2014-03-11 2015-12-01 Sas Institute Inc. Computerized cluster analysis framework for decorrelated cluster identification in datasets
US9424337B2 (en) 2013-07-09 2016-08-23 Sas Institute Inc. Number of clusters estimation
US9760675B2 (en) 2007-05-18 2017-09-12 Affymetrix, Inc. System, method, and computer software product for genotype determination using probe array data

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO1986001599A1 (fr) * 1984-08-21 1986-03-13 Cogent Limited Capteurs de gaz et procedes de fabrication et d'utilisation de ces capteurs
US4638443A (en) * 1983-02-21 1987-01-20 Hitachi, Ltd. Gas detecting apparatus
WO1995032420A1 (fr) * 1994-05-20 1995-11-30 Quest International B.V. Procede de classification de substrats

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US4638443A (en) * 1983-02-21 1987-01-20 Hitachi, Ltd. Gas detecting apparatus
WO1986001599A1 (fr) * 1984-08-21 1986-03-13 Cogent Limited Capteurs de gaz et procedes de fabrication et d'utilisation de ces capteurs
WO1995032420A1 (fr) * 1994-05-20 1995-11-30 Quest International B.V. Procede de classification de substrats

Non-Patent Citations (6)

* Cited by examiner, † Cited by third party
Title
B. R. KOWALSKI ET AL., JOURNAL OF THE AMERICAN CHEMICAL SOCIETY, vol. 95.3, 1973, pages 686 - 693, XP000615433 *
H. ABE ET AL., ANALYTICA CHIMICA ACTA, vol. 215, 1988, AMSTERDAM, NL, pages 155 - 168, XP002024606 *
HORNER G: "SIGNALVERARBEITUNG BEI CHEMOSENSORARRAYS", TECHNISCHES MESSEN TM 1982 - 1988 INCOMPLETE, vol. 62, no. 4, 1 April 1995 (1995-04-01), MÜNCHEN, DE, pages 166 - 172, XP000516380 *
J. R. STETTER ET AL., ANALYTICAL CHEMISTRY, vol. 58, no. 4, April 1986 (1986-04-01), WASHINGTON, DC, US, pages 860 - 866, XP002024605 *
J. W. GARDNER ET AL., SENSORS AND ACTUATORS B, vol. 18-19, 1994, LAUSANNE CH, pages 211 - 220, XP000615104 *
J. W. GARDNER, SENSORS AND ACTUATORS B, vol. 4, 1991, LAUSANNE CH, pages 109 - 115, XP002024604 *

Cited By (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP1019536A4 (fr) * 1997-08-15 2002-08-14 Affymetrix Inc Detection des polymorphismes a l'aide de la theorie des grappes
US6584410B2 (en) 1997-08-15 2003-06-24 Affymetrix, Inc. Polymorphism detection utilizing clustering analysis
US7129095B2 (en) 2002-03-29 2006-10-31 Smiths Detection Inc. Method and system for using a weighted response
US7034677B2 (en) 2002-07-19 2006-04-25 Smiths Detection Inc. Non-specific sensor array detectors
US9760675B2 (en) 2007-05-18 2017-09-12 Affymetrix, Inc. System, method, and computer software product for genotype determination using probe array data
US10832796B2 (en) 2007-05-18 2020-11-10 Affymetrix, Inc. System, method, and computer software product for genotype determination using probe array data
US9424337B2 (en) 2013-07-09 2016-08-23 Sas Institute Inc. Number of clusters estimation
US9202178B2 (en) 2014-03-11 2015-12-01 Sas Institute Inc. Computerized cluster analysis framework for decorrelated cluster identification in datasets

Also Published As

Publication number Publication date
GB9521089D0 (en) 1995-12-20
AU7223796A (en) 1997-05-07

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