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April 3 rd, 2008. WIRELESS AUTONOMOUS TRANSDUCER SYSTEMS Sywert H. Brongersma.

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Presentation on theme: "April 3 rd, 2008. WIRELESS AUTONOMOUS TRANSDUCER SYSTEMS Sywert H. Brongersma."— Presentation transcript:

1 April 3 rd, 2008

2 WIRELESS AUTONOMOUS TRANSDUCER SYSTEMS Sywert H. Brongersma

3 © Holst Centre Unither Nanomedical & Telemedical Technology April 3 rd, 2008 < 3< 3 Holst Centre open innovation Wireless Autonomous Transducer Solutions IMEC System-in-Foil Products and Production TNO Technology Integration

4 © Holst Centre Unither Nanomedical & Telemedical Technology April 3 rd, 2008 < 4< 4 Medical & Lifestyle as an application driver Wearability Connectivity Intelligence Functionality Autonomy Implantability

5 © Holst Centre Unither Nanomedical & Telemedical Technology April 3 rd, 2008 < 5< 5 Optimizing energy scavenging Camel Fridge: medicine transportation 2mW  0.03mW/cm2 S 10W A 10W Front End 20W DSP 20W Radio 20W Micropower System - 100W P 20W Thermal, Vibrational, RF, Light Non Electrical World

6 © Holst Centre Unither Nanomedical & Telemedical Technology April 3 rd, 2008 < 6< 6 Physical sensing or actuating mechanism Transducer design & physics Device physics inside nanowire,MEMS,… Signal preconditioning: Amplification, buffering, actuator driving, … Typically analog electronics Interface between sensor and signal processing unit Typically ADC, DAC, or counter, pulse generator Low-level signal processing Sensor data calibration, data correction, compression Transducer feedback and control loop Algorithms for data interpretation Pattern matching, sensor data fusion, classification Data interpretation Application software, diagnosis, … Underlying technology to fabricate transducers MEMS, nanowire deposition, micro-optics, … Application layer Algorithmic layer Processing layer Interfacing layer Signal conditioning layer Physical layer Technology layer Picture: P. Nair (Purdue Univ.) An Integrated Approach is Key…

7 © Holst Centre Unither Nanomedical & Telemedical Technology April 3 rd, 2008 < 7< 7 www.continuaalliance.org

8 © Holst Centre Unither Nanomedical & Telemedical Technology April 3 rd, 2008 < 8< 8 2002: Portable they say… Progress in ambulatory EEG… 2008 ULP biopotential read-out ASIC 3D-SiP layer integration Formfactor 300  1 cm 3 Low power <10mW

9 © Holst Centre Unither Nanomedical & Telemedical Technology April 3 rd, 2008 < 9< 9 [ MIT Technology Review ] Feature Extractor Feature Extractor EEG Channel 1 EEG Channel 21 Support- Vector Machine EEG Channel 2 Classification Temporal Constraint Feature Extractor X 1,1 X 1,2 X 1,3 X 1,4 X 2,1 X 2,2 X 2,3 X 2,4 X 21,1 X 21,2 X 21,3 X 21,4 … to enable automated epileptic seizure detection

10 © Holst Centre Unither Nanomedical & Telemedical Technology April 3 rd, 2008 < 10 Power Consumption of 8-Channel EEG 256 Hz 8 channels Further reduction towards 100  W Radio technology Local processing to reduce transmission  DSP w. > 500 MOPs/mW required

11 © Holst Centre Unither Nanomedical & Telemedical Technology April 3 rd, 2008 < 11 In parallel: wireless ECG patch Hybrid integration Electronics integration on flex substrate Textile integration for stretchability Flexible core part ULP bio-potential read-out front end Low-power digital signal processing: TI MSP430 f1611 Low-power radio link: Built on Nordic nRF24L01 175mAh Li-ion battery Band-aid integration Wire-free and easy to set-up Fits any body shapes and electrode placement

12 © Holst Centre Unither Nanomedical & Telemedical Technology April 3 rd, 2008 < 12 Towards automated arrhythmia detection For 90 nm technology: DSP Active power consumption 6mW + Duty cycle 1%  Average power consumption 60  W

13 © Holst Centre Unither Nanomedical & Telemedical Technology April 3 rd, 2008 < 13 And also: body temperature… on flex & SpO 2 autonomously Commercial SpO 2 sensor integrated with WATS sensor node

14 © Holst Centre Unither Nanomedical & Telemedical Technology April 3 rd, 2008 < 14 Multi sensor node approach very powerful ECG, respiration EMG EEG, EOG SpO 2 Temperature Activity monitoring

15 © Holst Centre Unither Nanomedical & Telemedical Technology April 3 rd, 2008 < 15 Multi-sensor body area network for complex health issues Star network with 3 slaves 2 channels EEG (F2/A1 and C2/A1) 2 channels EOG 1 channel EMG TDMA MAC protocol

16 © Holst Centre Unither Nanomedical & Telemedical Technology April 3 rd, 2008 < 16 Wireless Sleep Monitoring Sleep apnea prevalence Europe: 4% male population, 2% female population USA: 10% population Narcolepsy prevalence 1 in 1359 Dramatic socio-economic consequences Current sleep monitoring systems Expensive, non-natural environment Wired systems: cumbersome, noisy, hinder mobility Wireless sleep staging system Pre-screening in home environment Ambulatory and comfort

17 © Holst Centre Unither Nanomedical & Telemedical Technology April 3 rd, 2008 < 17 Preliminary clinical evaluation

18 © Holst Centre Unither Nanomedical & Telemedical Technology April 3 rd, 2008 < 18 Monitoring emotions  psycho-physiological response to external stimuli Emotional response ANS Homeostasis … CNS Control behavior Info processing … Vocal system Speech … Emotional response is one of many reasons for changes in ANS, CNS and vocal system Need for integration of multi-modalities Need to isolate emotion response Ultra-low-power wireless sensor network as enabling technology Test environment

19 © Holst Centre Unither Nanomedical & Telemedical Technology April 3 rd, 2008 < 19 Application 1: Biofeedback and emotion control ECG, Respiration Temperature, GSR Back muscle stiffness Emotion classification Feedback Visual Auditive Pharmaceutical

20 © Holst Centre Unither Nanomedical & Telemedical Technology April 3 rd, 2008 < 20 Application 2: monitoring acceptance of drug treatment Hospital analysis WBAN: ULP UWB for 15.14a standard Network (security, privacy, reliability) Continuous monitoring from home

21 © Holst Centre Unither Nanomedical & Telemedical Technology April 3 rd, 2008 < 21 First prototype of emotion monitor Fisher mapping: Clustering of emosion Error rate: ~40% Interpretation Error rate estimated using leave-one-out cross-validation on a very reduced data set Risk of over-fitting  Check on new data set !

22 © Holst Centre Unither Nanomedical & Telemedical Technology April 3 rd, 2008 < 22 Trend towards the future: Truly Unobtrusive Monitoring Solutions with ever increasing sensor functionality On-board power scavenging Low power  sensors & actuators * Sweat, Saliva, Breath Lactate, Urea, Glucose, Oxygen, Acetone * Polerized dipole molecules NO 2, CO, Ethanol, Amines * Redox molecules Ammonia, NO 2, H 2 S, CO x ) * Volatile organic compounds Benzene, Alkanes, Ethanol  read-out circuitry  radio  dsp


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