Trigeminal System. uoanatomy/neuroanat/ Somatic sensory: A007 Sensory cranial: F003 Sensory cranial:
DESIGN OF SENSORY SYSTEMDESIGN OF SENSORY SYSTEM...
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DESIGN OF SENSORY SYSTEM FOR BREATH ANALYSIS DESIGN OF SENSORY SYSTEM FOR BREATH ANALYSIS DESIGN OF SENSORY SYSTEM FOR BREATH ANALYSIS DESIGN OF SENSORY SYSTEM FOR BREATH ANALYSIS 1 1 2 3 Yingkan Lin 1 Milutin Stanaćević 1 Sanford R Simon 2 and Pelagia Irene Gouma 3 Yingkan Lin 1 , Milutin Stanaćević 1 , Sanford R. Simon 2 and Pelagia‐Irene Gouma 3 Departments of Electrical & Computer Engineering 1 Biochemistry 2 Pathology 2 and Material Science & Engineering 3 Departments of Electrical & Computer Engineering , Biochemistry , Pathology and Material Science & Engineering Stony Brook University Stony Brook NY 11794 Stony Brook University, Stony Brook, NY 11794 k d d d k d d d d l d l Background and Introduction Background and Introduction Discrete Readout System Implementation Discrete Readout System Implementation Sensor baseline resistance range: 1kΩ ~ 100MΩ Background and Introduction Background and Introduction Discrete Readout System Implementation Discrete Readout System Implementation Sensor baseline resistance range: 1kΩ 100MΩ 0 05% ~ 10% of sensor resistance change detectable 0.05% ~ 10% of sensor resistance change detectable T ld i 166dB H dh ld t bl i l FENO b th l h b d i d The la k of ine pensi e sensor te hnolo that o ld dete t and monitor the on entration Total dynamic range: 166dB Handheld, portable wireless FENO breath analyzer has been designed. The lack of inexpensive sensor technology that would detect and monitor the concentration l d b l bl f db k f of a single gas with high specificity and at low trace concentrations in the presence of Power Consumption: 400 μW Signal conditioning comprises baseline compensation, variable feedback resistance for of a single gas with high specificity and at low trace concentrations, in the presence of Power Consumption: 400 μW Signal conditioning comprises baseline compensation, variable feedback resistance for l fh d i d2 nd d l fil numerous interfering compounds has presented a main obstacle in advancement of the Chip area: 1 4mm x 0 8mm control of the dynamic range and 2 nd order low‐pass filter. numerous interfering compounds, has presented a main obstacle in advancement of the Chip area: 1.4mm x 0.8mm diagnostics using breath analysis Fabricated in 0 5μm CMOS technology Proposed signal processing techniques are implemented on a micro‐controller. diagnostics using breath analysis. Fabricated in 0.5μm CMOS technology Proposed signal processing techniques are implemented on a micro controller. Sensor resistance range: 100Ω ~ 100MΩ Sensor resistance range: 100Ω 100MΩ Task: design of a sensory system for detection and discrimination of nitric oxide in exhaled Size: 7 5cm x 7 5cm Task: design of a sensory system for detection and discrimination of nitric oxide in exhaled Size: 7.5cm x 7.5cm breath and measurement of the trace concentration for affordable and noninvasive medical Power consumption 168mW (360mW when Bluetooth is on) breath and measurement of the trace concentration for affordable and noninvasive medical Power consumption: 168mW (360mW when Bluetooth is on) diagnostics technology diagnostics technology . Obj i d l d l FENO i h ld Objective: to develop a stand‐alone FENO measurement micro‐system that would operate as t b t d li bl l d i a easy to use, robust and reliable personal device. Layout of the integrated readout Layout of the integrated readout h l Challenges in the design of the system: system in 0.5μm CMOS technology Challenges in the design of the system: l l d ll / f d a simple, low cost and small area gas sensor/sensor array specific to nitric oxide a simple, low cost and small area gas sensor/sensor array specific to nitric oxide hi i th h t t d th l t t bilit f th achieving the short‐term and the long‐term stability of the sensor response Experimental Results Experimental Results hi h iti it dl d t i it Experimental Results Experimental Results high sensitivity and low power readout circuit low power heating element low power heating element Electronic package 500ppb Heater 500ppb Heater Sensor substrate 300ppb 300ppb Block diagram of the wireless prototype Discrete 200ppb Block diagram of the wireless prototype. Discrete 200ppb implementation of signal conditioning implementation of signal conditioning 100ppb top view side view 100ppb top view side view Sensor and heater assembly Sensor and heater assembly. Sensory System Overview Sensory System Overview Sensory System Overview Sensory System Overview Limits on sensitivity: Limits on sensitivity: electrical noise electrical noise T l f th NO i R f th NO i t f large baseline resistance that can be few orders of magnitude higher than the actual Temporal response of the NO sensing Response of the NO sensing system for large baseline resistance that can be few orders of magnitude higher than the actual system for different concentrations of different concentrations of NO for short sensor response system for different concentrations of different concentrations of NO for short‐ sensor response b li i ti (h t t dl t ) NO in synthetic air mixture term measurements. baseline variation (short‐term and long‐term) NO in synthetic air mixture. term measurements. l i l i Short term sensor stability: Conclusion Conclusion Short‐term sensor stability: Conclusion Conclusion variations in sensor environment (temperature flow rate humidity) h l variations in sensor environment (temperature, flow rate, humidity) The wireless FENO measurement prototype. Th d t it t th i l i t hi th t dd The proposed sensory system integrates the signal processing techniques that address Long‐term sensor stability: important challenges in the design of the FENO monitoring device with high sensitivity and I d R d S I l i I d R d S I l i Long term sensor stability: important challenges in the design of the FENO monitoring device with high sensitivity and Integrated Readout System Implementation Integrated Readout System Implementation drift due to chemical reactions reliability Integrated Readout System Implementation Integrated Readout System Implementation drift due to chemical reactions reliability . The implemented and fabricated readout ASIC that interfaces the sensor/sensor array will R i ti diff t The implemented and fabricated readout ASIC that interfaces the sensor/sensor array will Response variations across different sensors: be integrated in a nitric oxide breath analyzer for monitoring and managing airway diseases large variability of baseline resistance be integrated in a nitric oxide breath analyzer for monitoring and managing airway diseases, large variability of baseline resistance such as asthma the drift in the baseline resistance over time at a different rate such as asthma. VDAC provides adaptable current the drift in the baseline resistance over time at a different rate The proposed sensory system for monitoring FENO can be interfaced with different through a sensor for different The proposed sensory system for monitoring FENO can be interfaced with different b dd d l b dd d l through a sensor for different selective sensors and used as a coarse diagnostic tool to enable an early detection and to Embedded Signal Processing Embedded Signal Processing base resistance. selective sensors and used as a coarse diagnostic tool to enable an early detection and to Embedded Signal Processing Embedded Signal Processing base resistance. direct more complex diagnostic tools where to focus attention I SEN direct more complex diagnostic tools where to focus attention. Goal: to obtain a calibration curve that would be independent of the baseline variations over f f Goal: to obtain a calibration curve that would be independent of the baseline variations over References References both short and long time frame References References both short and long time frame. I IN Y Li P G d M S ć ić "A L P Wid D i R R d IC f B h A l S " IN Y . Lin, P . Gouma and M. Stanaćević, "A Low‐Power Wide‐Dynamic‐Range Readout IC for Breath Analyzer System", From the controlled measurements with constant gas flow we can extract the response and Proc IEEE Int Symp Circuits and Systems (ISCAS'2013) Beijing China May 2013 From the controlled measurements, with constant gas flow, we can extract the response and Proc. IEEE Int. Symp. Circuits and Systems (ISCAS 2013), Beijing, China, May 2013. P G K Kl d X Y M St ć ić d L W “N d B th A l f A i relaxation time of the sensor and obtain the calibration plots P . Gouma, K. Kalyanasundaram, X. Yun, M. Stanaćević and L. Wang, “Nanosensor and Breath Analyzer for Ammonia I DAC relaxation time of the sensor and obtain the calibration plots. Detection in Exhaled Human Breath” IEEE Sensor Journal vol 10(1) pp 49 53 2010 I DAC For the dynamic measurement we are investigating how these parameters characterize the Detection in Exhaled Human Breath , IEEE Sensor Journal, vol. 10(1), pp. 49 53, 2010. L W K Kl d M St ć ić d P G “N D i f B th A t Dt ti ” For the dynamic measurement, we are investigating how these parameters characterize the L. Wang, K. Kalyanasundaram, M. Stanaćević and P . Gouma, “Nanosensor Device for Breath Acetone Detection”, IDAC provides path for most of the response under different flow rates Sensors Letters, vol. 8, 2010. IDAC provides path for most of the response under different flow rates. Sensors Letters, vol. 8, 2010. sensor current. Acknowledgment Acknowledgment Id d l i (ICA) i df h i fh b li Acknowledgment Acknowledgment Independent component analysis (ICA) is used for the compensation of the baseline Acknowledgment Acknowledgment i ti l kd fh d d variations. Block diagram of the integrated readout circuit This work is supported by the National Science Foundation (NSF) grant IIS‐1231761.
Transcript of DESIGN OF SENSORY SYSTEMDESIGN OF SENSORY SYSTEM...
DESIGN OF SENSORY SYSTEM FOR BREATH ANALYSISDESIGN OF SENSORY SYSTEM FOR BREATH ANALYSISDESIGN OF SENSORY SYSTEM FOR BREATH ANALYSISDESIGN OF SENSORY SYSTEM FOR BREATH ANALYSIS1 1 2 3Yingkan Lin1 Milutin Stanaćević1 Sanford R Simon2 and Pelagia Irene Gouma3Yingkan Lin1, Milutin Stanaćević1, Sanford R. Simon2 and Pelagia‐Irene Gouma3g , , g
Departments of Electrical & Computer Engineering1 Biochemistry2 Pathology2 and Material Science & Engineering3Departments of Electrical & Computer Engineering , Biochemistry , Pathology and Material Science & EngineeringStony Brook University Stony Brook NY 11794Stony Brook University, Stony Brook, NY 11794y y, y ,
k d d dk d d d d ld lBackground and IntroductionBackground and Introduction Discrete Readout System ImplementationDiscrete Readout System Implementation Sensor baseline resistance range: 1kΩ ~ 100MΩBackground and IntroductionBackground and Introduction Discrete Readout System ImplementationDiscrete Readout System Implementation Sensor baseline resistance range: 1kΩ 100MΩgg y py p0 05% ~ 10% of sensor resistance change detectable0.05% ~ 10% of sensor resistance change detectableT l d i 166dBH dh ld t bl i l FENO b th l h b d i dThe la k of ine pensi e sensor te hnolo that o ld dete t and monitor the on entration Total dynamic range: 166dBHandheld, portable wireless FENO breath analyzer has been designed.The lack of inexpensive sensor technology that would detect and monitor the concentration y g, p y g
l d b l bl f db k fp gy
of a single gas with high specificity and at low trace concentrations in the presence of Power Consumption: 400 μWSignal conditioning comprises baseline compensation, variable feedback resistance forof a single gas with high specificity and at low trace concentrations, in the presence of Power Consumption: 400 μWSignal conditioning comprises baseline compensation, variable feedback resistance for l f h d i d 2nd d l filnumerous interfering compounds has presented a main obstacle in advancement of the
Chip area: 1 4mm x 0 8mmcontrol of the dynamic range and 2nd order low‐pass filter.numerous interfering compounds, has presented a main obstacle in advancement of the Chip area: 1.4mm x 0.8mmy g p
diagnostics using breath analysisFabricated in 0 5μm CMOS technologyProposed signal processing techniques are implemented on a micro‐controller.diagnostics using breath analysis. Fabricated in 0.5μm CMOS technologyProposed signal processing techniques are implemented on a micro controller.
Sensor resistance range: 100Ω ~ 100MΩSensor resistance range: 100Ω 100MΩTask: design of a sensory system for detection and discrimination of nitric oxide in exhaled
Size: 7 5cm x 7 5cmTask: design of a sensory system for detection and discrimination of nitric oxide in exhaled
Size: 7.5cm x 7.5cmbreath and measurement of the trace concentration for affordable and noninvasive medicalPower consumption 168mW (360mW when Bluetooth is on)
breath and measurement of the trace concentration for affordable and noninvasive medicalPower consumption: 168mW (360mW when Bluetooth is on)diagnostics technologydiagnostics technology.
Obj i d l d l FENO i h ldObjective: to develop a stand‐alone FENO measurement micro‐system that would operate asj p y pt b t d li bl l d ia easy to use, robust and reliable personal device.y , p
Layout of the integrated readoutLayout of the integrated readout h lChallenges in the design of the system: system in 0.5μm CMOS technologyChallenges in the design of the system:
l l d ll / f dy μ gy
a simple, low cost and small area gas sensor/sensor array specific to nitric oxidea simple, low cost and small area gas sensor/sensor array specific to nitric oxidehi i th h t t d th l t t bilit f th achieving the short‐term and the long‐term stability of the sensor response
Experimental ResultsExperimental Resultsg g y p
hi h iti it d l d t i it Experimental ResultsExperimental Results high sensitivity and low power readout circuit xperimental Resultsxperimental Resultsg y plow power heating element low power heating element
Electronic package 500ppbHeater
500ppbHeaterSensor substrate 300ppb300ppb
Block diagram of the wireless prototype Discrete 200ppbBlock diagram of the wireless prototype. Discrete 200ppb
implementation of signal conditioningimplementation of signal conditioning 100ppbtop view side view 100ppbtop view side view
Sensor and heater assemblySensor and heater assembly.
Sensory System OverviewSensory System OverviewSensory System OverviewSensory System OverviewSe so y Syste O e eSe so y Syste O e eLimits on sensitivity:Limits on sensitivity:
electrical noiseelectrical noise
T l f th NO i R f th NO i t f large baseline resistance that can be few orders of magnitude higher than the actual Temporal response of the NO sensing Response of the NO sensing system for large baseline resistance that can be few orders of magnitude higher than the actual p p gsystem for different concentrations of
gdifferent concentrations of NO for shortsensor response system for different concentrations of different concentrations of NO for short‐sensor response
b li i ti ( h t t d l t ) NO in synthetic air mixture term measurements. baseline variation (short‐term and long‐term) NO in synthetic air mixture. term measurements.( g )
l il iShort term sensor stability: ConclusionConclusionShort‐term sensor stability: ConclusionConclusionvariations in sensor environment (temperature flow rate humidity)h l
variations in sensor environment (temperature, flow rate, humidity)The wireless FENO measurement prototype.
Th d t i t t th i l i t h i th t ddp yp
The proposed sensory system integrates the signal processing techniques that addressLong‐term sensor stability: p p y y g g p g qimportant challenges in the design of the FENO monitoring device with high sensitivity andI d R d S I l iI d R d S I l i
Long term sensor stability:important challenges in the design of the FENO monitoring device with high sensitivity andIntegrated Readout System ImplementationIntegrated Readout System Implementation drift due to chemical reactionsreliabilityIntegrated Readout System ImplementationIntegrated Readout System Implementationdrift due to chemical reactionsreliability.g y pg y pThe implemented and fabricated readout ASIC that interfaces the sensor/sensor array willR i ti diff t The implemented and fabricated readout ASIC that interfaces the sensor/sensor array willResponse variations across different sensors:be integrated in a nitric oxide breath analyzer for monitoring and managing airway diseases
plarge variability of baseline resistance be integrated in a nitric oxide breath analyzer for monitoring and managing airway diseases, large variability of baseline resistance
such as asthmathe drift in the baseline resistance over time at a different rate such as asthma.VDAC provides adaptable current the drift in the baseline resistance over time at a different rateThe proposed sensory system for monitoring FENO can be interfaced with different
p pthrough a sensor for different The proposed sensory system for monitoring FENO can be interfaced with different
b dd d lb dd d lthrough a sensor for different
selective sensors and used as a coarse diagnostic tool to enable an early detection and toEmbedded Signal ProcessingEmbedded Signal Processing base resistance. selective sensors and used as a coarse diagnostic tool to enable an early detection and toEmbedded Signal ProcessingEmbedded Signal Processing base resistance.
direct more complex diagnostic tools where to focus attentiong gg g
ISEN direct more complex diagnostic tools where to focus attention.Goal: to obtain a calibration curve that would be independent of the baseline variations over
ffGoal: to obtain a calibration curve that would be independent of the baseline variations over
ReferencesReferencesboth short and long time frame ReferencesReferencesboth short and long time frame.IIN
Y Li P G d M S ć ić "A L P Wid D i R R d IC f B h A l S "IN
Y. Lin, P. Gouma and M. Stanaćević, "A Low‐Power Wide‐Dynamic‐Range Readout IC for Breath Analyzer System",From the controlled measurements with constant gas flow we can extract the response and Proc IEEE Int Symp Circuits and Systems (ISCAS'2013) Beijing China May 2013From the controlled measurements, with constant gas flow, we can extract the response and Proc. IEEE Int. Symp. Circuits and Systems (ISCAS 2013), Beijing, China, May 2013.P G K K l d X Y M St ć ić d L W “N d B th A l f A irelaxation time of the sensor and obtain the calibration plots P. Gouma, K. Kalyanasundaram, X. Yun, M. Stanaćević and L. Wang, “Nanosensor and Breath Analyzer for AmmoniaIDAC
relaxation time of the sensor and obtain the calibration plots. Detection in Exhaled Human Breath” IEEE Sensor Journal vol 10(1) pp 49 53 2010
IDAC
For the dynamic measurement we are investigating how these parameters characterize the Detection in Exhaled Human Breath , IEEE Sensor Journal, vol. 10(1), pp. 49 53, 2010.L W K K l d M St ć ić d P G “N D i f B th A t D t ti ”
For the dynamic measurement, we are investigating how these parameters characterize the L. Wang, K. Kalyanasundaram, M. Stanaćević and P. Gouma, “Nanosensor Device for Breath Acetone Detection”,IDAC provides path for most of theresponse under different flow rates Sensors Letters, vol. 8, 2010.
IDAC provides path for most of the response under different flow rates. Sensors Letters, vol. 8, 2010.sensor current.
AcknowledgmentAcknowledgmentI d d l i (ICA) i d f h i f h b li AcknowledgmentAcknowledgmentIndependent component analysis (ICA) is used for the compensation of the baseline AcknowledgmentAcknowledgmentp p y ( ) pi ti
l k d f h d dvariations.
Block diagram of the integrated readout circuit This work is supported by the National Science Foundation (NSF) grant IIS‐1231761.g g pp y ( ) g
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