WIRELESS AUTONOMOUS TRANSDUCER SYSTEMS Sywert H. Brongersma
description
Transcript of WIRELESS AUTONOMOUS TRANSDUCER SYSTEMS Sywert H. Brongersma
April 3rd, 2008
April 3rd, 2008
WIRELESS AUTONOMOUS TRANSDUCER SYSTEMS
Sywert H. Brongersma
Unither Nanomedical & Telemedical Technology
April 3rd, 2008
3© Holst Centre
Holst Centre open innovation
Wireless Autonomous Transducer Solutions
IMEC
System-in-Foil Products and Production
TNO
Technology Integration
Unither Nanomedical & Telemedical Technology
April 3rd, 2008
4© Holst Centre
Medical & Lifestyle as an application driver
Wearability
Connectivity
Intelligence
Functionality
Autonomy
Implantability
Unither Nanomedical & Telemedical Technology
April 3rd, 2008
5© Holst Centre
Optimizing energy scavenging
Camel Fridge: medicine transportation
2mW 0.03mW/cm2
S10W
A10W
FrontEnd
20WDSP
20W
Radio20W
Micropower System - 100W
P20W
Thermal, Vibrational, RF, Light
NonElectrical
World
Unither Nanomedical & Telemedical Technology
April 3rd, 2008
6© Holst Centre
Physical sensing or actuating mechanismTransducer design & physics
Device physics inside nanowire,MEMS,…
Signal preconditioning: Amplification, buffering, actuator driving, …
Typically analog electronics
Interface between sensor and signal processing unitTypically ADC, DAC, or counter, pulse generator
Low-level signal processingSensor data calibration, data correction, compression
Transducer feedback and control loop
Algorithms for data interpretationPattern matching, sensor data fusion, classification
Data interpretationApplication software, diagnosis, …
Underlying technology to fabricate transducersMEMS, nanowire deposition, micro-optics, …
Application layer
Algorithmic layer
Processing layer
Interfacing layer
Signal conditioninglayer
Physical layer
Technology layer
Picture: P. Nair (Purdue Univ.)
An Integrated Approach is Key…
Unither Nanomedical & Telemedical Technology
April 3rd, 2008
7© Holst Centre
www.continuaalliance.org
Unither Nanomedical & Telemedical Technology
April 3rd, 2008
8© Holst Centre
2002: Portable they say…
Progress in ambulatory EEG…
2008
ULP biopotential read-out ASIC
3D-SiP layer integration
Formfactor 300 1 cm3
Low power <10mW
Unither Nanomedical & Telemedical Technology
April 3rd, 2008
9© Holst Centre
[ MIT Technology Review ]
0
10
20
30
40
50
60
70
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17
Patient Number
Se
con
ds
Aft
er E
lect
rog
rap
hic
O
ns
et
Automatic Detections" "Patient/Caregiver Pushbutton"Feature
Extractor
FeatureExtractor
EEG Channel 1
EEG Channel 21
Support-Vector
Machine
EEG Channel 2 ClassificationTemporalConstraint
FeatureExtractor
X1,1
X1,2
X1,3
X1,4
X2,1
X2,2
X2,3
X2,4
X21,1
X21,2
X21,3
X21,4
… to enable automated epileptic seizure detection
Unither Nanomedical & Telemedical Technology
April 3rd, 2008
10© Holst Centre
Power Consumption of 8-Channel EEG
Micro0.81mW
Radio2.40mW
EEG0.30mW
Total power consumption: 3.51mW
256 Hz
8 channels
Further reduction towards 100 W
Radio technology
Local processing to reduce transmission
DSP w. > 500 MOPs/mW required
Unither Nanomedical & Telemedical Technology
April 3rd, 2008
11© Holst Centre
In parallel: wireless ECG patch
Hybrid integrationElectronics integration on flex substrateTextile integration for stretchability
Flexible core partULP bio-potential read-out front endLow-power digital signal processing: TI MSP430 f1611Low-power radio link: Built on Nordic nRF24L01175mAh Li-ion battery
Band-aid integrationWire-free and easy to set-upFits any body shapes and electrode placement
Unither Nanomedical & Telemedical Technology
April 3rd, 2008
12© Holst Centre
Towards automated arrhythmia detection
99.5499.5410010099.9099.9099.90Se(% )
7.903.98-1.18-1.416.4510.8312.06Me (samples)
22.9719.4813.214.4413.9622.6132.33Sd (samples)
3542354236233623319431943194# annotations
TendTpeakQRSendQRSonPendPpeakPonParameters
99.5499.5410010099.9099.9099.90Se(% )
7.903.98-1.18-1.416.4510.8312.06Me (samples)
22.9719.4813.214.4413.9622.6132.33Sd (samples)
3542354236233623319431943194# annotations
TendTpeakQRSendQRSonPendPpeakPonParameters
For 90 nm technology:
DSP Active power consumption 6mW + Duty cycle 1%
Average power consumption 60W
Unither Nanomedical & Telemedical Technology
April 3rd, 2008
13© Holst Centre
And also: body temperature… on flex & SpO2 autonomously
Commercial SpO2 sensor integrated
with WATS sensor node
Unither Nanomedical & Telemedical Technology
April 3rd, 2008
14© Holst Centre
Multi sensor node approach very powerful
ECG, respiration
EMG
EEG, EOG
SpO2
Temperature
Activity monitoring
Unither Nanomedical & Telemedical Technology
April 3rd, 2008
15© Holst Centre
Multi-sensor body area network for complex health issues
Star network with 3 slaves2 channels EEG (F2/A1 and C2/A1)2 channels EOG1 channel EMG
TDMA MAC protocol
Unither Nanomedical & Telemedical Technology
April 3rd, 2008
16© Holst Centre
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
Unither Nanomedical & Telemedical Technology
April 3rd, 2008
17© Holst Centre
Preliminary clinical evaluation
Unither Nanomedical & Telemedical Technology
April 3rd, 2008
18© Holst Centre
Monitoring emotions
psycho-physiological response to external stimuli
Emotional response
ANS
Homeostasis…
CNS
Control behaviorInfo 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
Unither Nanomedical & Telemedical Technology
April 3rd, 2008
19© Holst Centre
Application 1: Biofeedback and emotion control
ECG, Respiration
Temperature, GSR
Back muscle stiffness
Emotionclassification
FeedbackVisualAuditivePharmaceutical
Unither Nanomedical & Telemedical Technology
April 3rd, 2008
20© Holst Centre
Application 2: monitoring acceptance of drug treatment
Hospital analysis
WB
AN
: U
LP U
WB
for
15.
14a
stan
dard
Net
wor
k (s
ecur
ity,
priv
acy,
rel
iabi
lity)
Continuous monitoring from home
Unither Nanomedical & Telemedical Technology
April 3rd, 2008
21© Holst Centre
-0.5 0 0.5
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
Feature 1
Fea
ture
2
First prototype of emotion monitor
Emotion
Cla
ssifi
er
ECG
GSR
Temp
Respiration
MeanMean 1st diff
MeanMean 1st diff
Mean
MeanMean 1st diff
Emotion
HR + filter
analysis
Filter
Filter
RR + filter
FFT
Cla
ssifi
er
ECG
GSR
Temp
Respiration
MeanMean 1st diff
MeanMean 1st diff
Mean
MeanMean 1st diff
Emotion
HR + filter
analysis
Filter
Filter
RR + filter
FFT
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 !
Unither Nanomedical & Telemedical Technology
April 3rd, 2008
22© Holst Centre
Trend towards the future:
Truly Unobtrusive Monitoring Solutions
with ever increasing sensor functionality
On-board power scavengingLow power sensors & actuators
* Sweat, Saliva, Breath Lactate, Urea, Glucose, Oxygen, Acetone
* Polerized dipole moleculesNO2, CO, Ethanol, Amines
* Redox moleculesAmmonia, NO2, H2S, COx)
* Volatile organic compounds Benzene, Alkanes, Ethanol
read-out circuitry radio dsp