Wearmesoc

Page 1

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

Schekeb Fateh, Integrated Systems Laboratory, ETH Z端rich Nano-Tera Annual Plenary Meeting, May 4th, 2015 04/06/15


Introduction

04/06/15


Introduction

Challenges

Opportunities

Escalating Medical Costs

§  Wireless Revolution §  Advent of M2M and IoT §  Smartphones and Tablets §  Nano Electronics Integration [Source: Swiss Federal Statistical Office]

§  Aging Population §  Growing need of the elderly §  Silent Suffering

§  Potentially Benefiting Healthcare

WearMeSoC Objective: Develop technologies essential to miniaturize wireless monitoring, and demonstrate its effectiveness in real medical use cases 04/06/15


Introduction

Wearable Devices §  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 onboard signal processing resources

04/06/15


Introduction

Current Wearable Device with Wireless Link §  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

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

04/06/15


Introduction

Modular Biomedical Data Acquisition Platform

§  Development platform: §  Modular §  Flexible §  Programmable

04/06/15


VivoSoc: Intelligent Sensor Front-end with Wireless Link 04/06/15


VivoSoc

VivoSoC: Biomedical Data Acquisition System-on-Chip 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

04/06/15


VivoSoc

Vision of VivoSoC §  Potential Application: Build intelligent biomedical platform with only 3 ASICs including RF capability

Flash Mem

Electrodes Connector

VivoSoC

RF Modem

04/06/15


Field of Applications

04/06/15


Electrocardiography (ECG) and Pulse Oximetry USZ Pulmonary Department 04/06/15


Pulse Oximetry

Pulse Oximetry Hardware

Oximetry module for the WearMeSoC development platform based on discrete components

walking and arm swinging

§  First experiments based on discrete hardware §  Test of algorithms for motion artifact and ambient light suppression §  Crucial intermediate step towards an integrated solution

arm swinging

§  Specification

§  First Oximetry ASIC:

still vertical movement

horizontal movement

Oscillating finger

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

04/06/15


Pulse Oximetry

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

04/06/15


Electrooculography (EOG) Fitness-to-Drive Test for the Elderly USZ Neurology Department 04/06/15


EOG

Mobile Eye Tracking Scene camera with synchronization LED

Vertical EOG channel

Horizontal EOG channel Live view of channels

04/06/15


EOG

Achievements §  Sophisticated synchronization method §  Optimal-polynomial 9point calibration procedure §  System linearity over +/-15deg §  Robust event detection (blinks, fast eye movements, fixations)

Target Eye Mean

04/06/15


Electroencephalography (EEG) USZ Sleep Analysis Lab 04/06/15


EEG

Automatic Artifact Detection in Long-Term EEG Recordings [A. Wierzbicka et al.: Sleep Disorders Center, Institute of Psychiatry and Neurology Warsaw, Poland]

§  Implemented algorithms for automatic artifact detection §  Identify artifact free segments for further analysis §  Best to combine several algorithms 04/06/15


EEG

Identification of Microsleep Episodes

§  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 04/06/15


Electromyography (EMG) Universita di Bologna Micrel Lab 04/06/15


EMG

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

SD CARD BLUETOOTH MODULE BLUETOOTH REGULATOR

BATTERY

ANALOG

USART PRESSURE SENSOR I2C

SENSORS REGULATOR

JTAG

SPI

IMU

USB

DIGITAL

ARM Cortex M4 MCU

MCU REGULATOR

SPI

CEREBRO

ELECTRODES CONNECTOR

CEREBRO DIGITAL CEREBRO ANALOG REGULATOR REGULATOR

POWER MANAGEMENT

•  Cerebro interfaced with the ARM Cortex M4 to process EMG signals •  Data is transferred using Bluetooth to a mobile device http://www.touchbionics.com/ 04/06/15


EMG

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

92% accuracy in estimation of 7 gestures

Digitally-controlled AFE

04/06/15


Conclusions

04/06/15


Conclusions

Conclusions §  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 04/06/15


Turn static files into dynamic content formats.

Create a flipbook
Issuu converts static files into: digital portfolios, online yearbooks, online catalogs, digital photo albums and more. Sign up and create your flipbook.