04/28/2023

Schekeb Fateh, Integrated Systems Laboratory, ETH Zürich

Nano-Tera Annual Plenary Meeting, May 4th, 2015

WearMeSoCMulti Functional Wearable Wireless Medical Monitoring Based on a Multi Channel Data Acquisition and Communication Management System on a Chip

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Introduction

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Challenges Opportunities

Aging Population Growing need of the elderly Silent Suffering

Wireless Revolution

Advent of M2M and IoT

Smartphones and Tablets

Nano Electronics Integration

Potentially Benefiting Healthcare

WearMeSoC Objective: Develop technologies essential to miniaturize wireless monitoring, and

demonstrate its effectiveness in real medical use cases

Introduction

[Source: Swiss Federal Statistical Office]

Escalating Medical Costs

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Clinic & point-of-care devices: Uncompromised biosignals acquisition

and processing quality required High cost and power consumption Not portable

Wearable devices: Need to trade off medical-grade signal

quality with: Minimal dimensions Ultra-low power consumption & low

cost Multi-sensor support with limited on-

board signal processing resources

Wearable Devices

Introduction

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Biomedical data acquisition ASIC supporting: ECG/ EMG/ EEG/ EOG … 3.2kHz signal bandwidth DC signal tracking

Device based on this ASIC Portable Medium size Wireless connection to monitoring display

Current Wearable Device with Wireless Link

Introduction

[P. Schonle et al., Modular multi-sensor platform for portable and wireless medical instrumentation , BioCAS, 2014]

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Modular Biomedical Data Acquisition Platform

Introduction

Development platform: Modular Flexible Programmable

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VivoSoc: Intelligent Sensor Front-end with Wireless Link

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VivoSoc: System-On-Chip Architecture

VivoSoc

Dual core PULP (Parallel processing Ultra-Low Power platform) Provides computing resources to also run communication protocol stack

[F. Conti et al., Energy-efficient vision on the PULP platform for ultra-low power parallel computing , SiPS 2014]

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Area: 3.8 mm x 2.8 mm

Technology: 130 nm CMOS(tape-out: April 2015)

Architecture: Dual core RISC with DMA, 2 kByte Cache, 32 kByte L2, 16 kByte TCDM

Front-end: 8 analog channels with 108 dB CMRR, 3.2 kHz bandwidth

Peripherals: • 2 quad SPI masters• 1 SPI slave• 8 GPIO, 1 JTAG• 1 UART

VivoSoC: Biomedical Data Acquisition System-on-Chip

VivoSoc

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Vision of VivoSoC

Potential Application: Build intelligent biomedical platform with only 3 ASICs including RF capability

VivoSoc

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Long-Distance Wireless Link

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Ultra Low Power Cellular Data Modem (GSM/EDGE/E-EDGE)

[Kröll2014] H. Kröll et al. An Evolved EDGE PHY ASIC Supporting Soft-Output Equalization and Rx Diversity, ESSCIRC 2014[Kröll2015] H. Kröll et al. An Evolved GSM/EDGE baseband ASIC Supporting Rx Diversity, JSSC 2015

Wireless Link

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Dual Antenna Cellular Data Modem Testbed with ML605 and Zedboard

-113.4 dBm sensitivity of Rx-diversity

Wireless Link

Processing of a single 32-QAM EGPRS2-A time slot consumes 5.5 mW

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Field of Applications

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Electrocardiography (ECG) and Pulse Oximetry

USZ Pulmonary Department

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Pulse Oximetry Hardware

First experiments based on discrete hardware

Test of algorithms for motion artifact and ambient light suppression

Crucial intermediate step towards an integrated solution Specification

First Oximetry ASIC: still

verticalmovement

horizontalmovement

arm swinging

Oscillatingfinger

wal

king

and

arm

sw

ingi

ng

Oximetry module for the WearMeSoC development platform based on discrete components

Raw data of a test recording showing heavy motion artifacts for different movements

Pulse Oximetry

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Ambulatory Respiratory Monitoring with Lung Disease 40 patients with chronic obstructive pulmonary disease

performed several 6MWT in Zurich (490m), Davos Clavadel (1650m) and Davos Jakobshorn (2590m)

Hypothesis: SpotSpO2 differs from values derived at the end of 6MWT by analysis of SpO2 trends (TrendSpO2) downloaded from pulse oximetry memory after 6MWT

Altitude had no influence on agreement Visual spot readings and graphical analysis of SpO2

recordings at end of 6MWT agree well on average

Pulse Oximetry

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Electrooculography (EOG)Fitness-to-Drive Test for the ElderlyUSZ Neurology Department

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Mobile Eye Tracking

Vertical EOG channel

Horizontal EOG channel

Scene camera with synchronization LED

Live view of channels

EOG

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Achievements

EOG

Sophisticated synchronization method

Optimal-polynomial 9-point calibration procedure

System linearity over +/-15deg

Robust event detection (blinks, fast eye movements, fixations)

2°

TargetEyeMean

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Electroencephalography (EEG)

USZ Sleep Analysis Lab

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Automatic Artifact Detection in Long-Term EEG Recordings

EEG

Implemented algorithms for automatic artifact detection Identify artifact free segments for further analysis Best to combine several algorithms

[A. Wierzbicka et al.: Sleep Disorders Center, Institute of Psychiatry and Neurology Warsaw, Poland]

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Microsleep episodes are characterized by a change in oscillatory activity Microsleep episodes mostly associated with a lack of eye movements, and often

occurred after brief episodes of alpha activity (~10 Hz) Future work: Develop a method for (semi-)automatic detection of microsleep

episodes

Identification of Microsleep Episodes

EEG

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Electromyography (EMG)

Universita di Bologna Micrel Lab

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Platform for Evaluation of EMG Signals and Hand Gesture Recognition using Cerebro

• Cerebro interfaced with the ARM Cortex M4 to process EMG signals

• Data is transferred using Bluetooth to a mobile device

http://www.touchbionics.com/

EMG

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Hand Gesture Recognition

92% accuracy in estimation of 7 gestures

Digitally-controlled AFE

EMG Controlled Hand Prosthesis

EMG

[S. Benatti et al. EMG-Based Hand Gesture Recognition with Flexible Analog Front End, BioCAS 2014 ]

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Ultra Low Power and Implantable Biomedical DeviceGlaxoSmithKline (GSK)

[Center for Neuroprosthetics, EPFL | STI | IMT/IBI | LSBI]

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Ultra Miniaturized and Implantable Device

Size of miniaturized and folded device around 0.8 cm3

Future Goal: use VivoSoC and target a size below 0.5 cm3

Implantable Devices

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Modular Device versus Implantable Device

Size: 0.8 cm3

Size: 312 cm3

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Implantable Device Interfacing Nerves

Electrodes

Implantable Devices

Implantable Device

Interfacing nerves

[Center for Neuroprosthetics, EPFL | STI | IMT/IBI | LSBI]

First recording of nerve activity expected in June

Feedback including stimulation Miniaturized device in fabrication Electrodes already in test phase

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Conclusions

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Successful tests of portable device through medical research partners

System-on-Chip for biomedical platform called VivoSoC realized

ASIC implementation of Pulse Oximetry Hardware

Ultra low power cellular modem implemented by industry partner

Additional promising applications gained: EMG based gesture recognition Ultra-low power implantable devices

First implantable system with size of 0.8 cm3

Conclusions

Conclusions

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Questions

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Supplementary Slides

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Wireless Portable Medical Devices Market

Introduction

WEARMESOC Objective:

Develop technologies essential to miniaturize wireless monitoring, and demonstrate its effectiveness in real medical use cases

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User friendly Minimum size,

wearable platform

Low power Multi purpose Programmable Storage

capability

Healthcare Platform

VivoSoc

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Multichannel low power analog frontend

Data conversion Signal processing Various interfaces Cascade-able Software defined Short time-to-

market

VivoSoc: Realization of the Biomedical Platform

VivoSoc

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Clinical Use Cases Post Operative Monitoring

A Research Focus at USZ IT in Medicine Department Both Size and Functionality Matters!

Eye Position Monitoring USZ Neurology Department Important topic for safe driving by the elderly Challenges for miniaturization

Study of Altitude Disorder USZ Pulmonary Department Swiss spend much time in mountains Important for safety in some workplaces

Applications

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Clinical Use Cases Sleep Disorder Research

Sleep Analysis Lab (USZ) Both Size and Functionality Matters! What would we give to get a good night’s sleep?

EMG Controlled Hand Prosthesis Micrel Lab (Universita’ di Bologna) Classifier based gesture recognition Performing of daily living movements

Ultra Low Power Implantable Devices Centre Hospitalier Universitaire Vaudois Centre Neuroprosthetics EPFL GlaxoSmithKline (GSK)

Applications

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Today, EEG electrodes are connected to an amplifier beside the bed

The wiring leads to an unnatural sleep situation

A small wireless device would improve the experimental setup

EEG in Sleep Research

EEG

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Test of Prototype of Wearable Bio-Monitoring Device (Sleep Recording)

EEG

Four-channel recording of EEG for 9 hours SWA: EEG power in 0.75-4.5 Hz range EMG power in 10-40 Hz range Subject awake for 1.5 h engaged in activity and then went to bed

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Next Steps & Challenges

EOG

Implementation of MIMO-mirror projector for head-centered target display

Removal of physiological baseline drift Implementation of photodiode for

luminance measurements

Driving Test for Elderly Drivers

Bluebox EOG Video-basedSampling rate 1000Hz 30 - 250HzInfluence of eye physiology None HighOperator expertise Low Medium - HighPricing Low HighModularity High NoneSpatial resolution ~2deg <1deg

EOG: Comparison to other systems

Application

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Head-centered calibrationMiniature laser projector for target display

Removal of physiological drift Photodiode for luminance measurements

Fitness-to-drive testDevelop and test the elderly

EOG: Next steps & challenges

www.hamamatsu.com/sp/hc/osh/osh_05a_image01.jpg

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Elderly license holder’s fitness to drive need to be tested regularly

Current : Purely medical exam

Does not reflect exact demand of driving

Time consuming

No medical parameter can unambiguously determine the fitness to drive

Proposal: Computer-assisted evaluated on-road driving test

Reflects the exact demand of driving

One single test

Saccade eye movementEasy to measureIndicates diseases like dementiaNot typically examined in common neuropsychological tests

Eye movements & Fitness-to-Drive testmodified from: Yishu Liu – Electrooculography Based Fitness to Drive Test

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Comparison to Head-Mounted Video-Based Eye TrackingMETHODS Cereblue EOG Video-basedSampling rate 1000Hz 30-250Hz: dynamic eye movement

parameters may be degradedInfluence of eye physiology

None High: droopy eye lids cause data loss Problematic in the elderly

Operator expertise Low: Electrode placement High: Eye detection parameters

Pricing Low High: up to 10.000$

Modularity High: only 3/8 channels used Additional components can easily be added (gyroscope, ECG,…)

None

Spatial resolution Low: ~2deg High: <1deg

EOG

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Eye movements

Compensatory (reflexive) Goal-directed (voluntary)

Saccade network

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Electrooculograpy

Corneo-retinal potential

Verticalelectrodes

Horizontalelectrodes

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8 4 08 4 08 5 16 9 17 9 1......

ch1 ch2 sync.

EOG-Video Synchronizationmodified from: Yishu Liu – Electrooculography Based Fitness to Drive Test

• Generate random sync. signal with the Bluebox ; stored as pulse sequence

• Control LED in video with this sequence

• 8-bit sync. sequence every 2 seconds

• Synchronize by finding same sync. sequence

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Test ASIC:Transimpedance Medical Amplifier for Oximetry (TMA-O)

3 channel TIA Full swing: Max. ENOB:

6 channel LED driver

Partially parallel On-chip calibration

TIA + ADC digital circ. LED driver Highly configurable

Arbitrary selection of input and output channels for up to 5 program sequences. Synchronization for parallel multi-chip operation

Future: Integration of the TMA-O front-end in VivoSoC

Pulse Oximetry

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TMA-O: TIA front-end

3 differential inputs Full swing: Max. ENOB:

Correlated double sampling (CDS) for ambient light suppression.

Front-end can be used in resistive and capacitive TIA modes. Enhanced input range

Schematic of the TIA

Ambient light filtering performance dependent on the pulse width.

Frequency (Hz)

Pulse Oximetry

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TMA-O: LED driver

6 channel LED driver

resolution

On-chip current calibration

LED duty-cycle can be adapted at the signal condition for optimum power saving

Schematic of the LED driver

Pulse Oximetry

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PassiveProsthesis

- Cosmetic- Low Functionality

ActiveProsthesis

- 1 or 2 DOF- EMG controlled

MultifingerProsthesis

- High number of DOF- EMG controlled- Daily living movements

EMG Controlled Hand ProsthesisEMG

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Comparison to MYO Armband

• Cerebro has similar performance as the MYO system

EMG

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Top Layer of MicroDevice

Rigid 11mm Rigid 11mm4-LayerFlex 3mm

11m

m

PCB: 6 Layer Rigid-Flex, thickness 0.8mm

Implantable Devices

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Side View (Folded) of MicroDevice

≈ 12.5 mm

≈ 5.

5 m

mImplantable Devices

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Comparison to Existing Holter ECG System

Mortara H3+ 3 channel ECG 48h recording

WearMeSoC Platform 8 channel ECG/EEG/… Real time monitoring Size: about 1 cm3

IMEC Holst Center single channel ECG 7d recording

Supplementary Slides

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VivoSoc in Operation