Integrated Circuits and Systems Lab 612

Human++ from technology to emerging health monitoring concepts

Advisor:Robert Chen-Hao Chang Student:Shiue Ru Chen Date:2010/06/04

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Outline

Overview of the BAN set Different biopotential signal sensing Micro-power generation Emerging health monitoring concepts

A. Wireless sleep staging

B. Wireless ECG patch Reference

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Overview of the BAN set up

Sensor : processing the bio-signals

Base station : collecting and managing the data-flow

The incoming signal are amplified and filtered and the BAN is a typical star topology networks with TDMA

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Different biopotential signals

Amplitude and frequency characteristics of different biopotential signals

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Sensor node

• 1 EEG sensor node that can acquire, process and transmit 1 to 24 EEG signals.

• 1 ECG sensor node that can acquire, process and transmit ECG signals.

• 1 EMG sensor node that can acquire, process and transmit EMG signals.

• 1 base-station that collects the information from the 3 sensor nodes.

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Functional diagram

Signals are sampled at 1024Hz with a 12-bit resolution and transmitted over a wireless link operation in the 2.4GHz ISM band

1.Listen : the sensors receive their parameter from the base station

2.Processing : the biopotentical signals are monitored and processed

3.Transmit : the sensors send their data to the base station

4.Sleep : power save mode ,most of the electronics are switched off

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Ultra-low-power wireless

Another system can deliver a pulse rate up to 40MHz with a measured power consumption of 2mW, or 50pJ per pulse ,1nJ/bit.

The Nordic nRF24L01 achieves less than 20nJ/bit

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Ultra-low-power sensing

EEG, ECG, EMG and EOG signals, presents an interesting challenge as these signals differ in amplitude and frequency characteristics

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UWB-IR

The transmitted signal consists in pulses of short duration (~1-2 ns) that are separated by longer silent periods (~20 ns or more).

Feature:

1.High speed (400 Mbps)

2.Low power

3.Wireless transformation

4.Impulse signal

5.Range of 10m

1.bandwidth larger than 500 MHz 2.Communications between 3.1GHz and 10.6GHz 3.Power spectral density(PSD)limit of -41dbm/MHz

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Architecture of the pulse generator

Ring oscillator has fast startuptime

It been implemented in a logic 0.18um CMOS technologyAnd it can deliver a pulse rate up to 40MHz with a measured power consumption of 2mW, or 50pJ per pulse ,1nJ/bit.

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Example for EMG

Listen and transmit mode consume about 90% of the power and the overall power less than 1mW if the measurement interval is longer than 1s

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Comparing

(up) UWB-IR signal , there are idle time that can save power

(down) narrowband radio signal , there are always active time

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Power breakdown for benchmarking example

Active : optimizing the processing algorithm , reducing data memory sizes, decreasing processor complexity and cycle count

Idle : clock gating control

Leakage : using high threshold voltage cell

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Micro-power generation

2/ cmmW

Heat flow generates a power density of about 20 A thermoelectric generator (TEG) output voltage of 0.7V at matched load

At 22°C, wrist-watch type of TEG provide 0.2-0.3 mW density varying from 8 to 25

EEG monitoring

Provide pulse-oximeter power

2/ cmuW

micromachined thermoelectric generator, which is expected to generate up to 30 μW/cm2 at a voltage exceeding 4.0 V

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Seebeck effect

The thermal emf is not define as temperature(T1 － T2) .

T2 base point

T1 measure

point

A (+)

B(-)T1>T2

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Schematic of a thermoelectric

Typically based on Bi2Te3, the pillars have a lateral size of 0.3 – 1 μm and a height of 1 – 3 μm. A TEG optimized to obtain themaximum power will have a thermal resistance of about 200cm2K/W per cm2 of surface

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Performance of the watch-like TEG

1.No physical activity 2.Working in office 3.Walking man

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Battery-less electronics

Wireless body-powered pulse oximeter , a prototype of the battery-less electronics and the application running on a laptop.

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Emerging health monitoring concepts

A. Wireless sleep staging

2-channel EEG, 2-channel EOG and 1-channel EMG

Each node achieves a power consumption of 15 mW, for a sampling rate of 200 Hz

Featuring:Reconfigurable gain and bandwidth, the read-out ASIC can be used to monitor EEG, EOG and EMG

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Comparing

a. Now in hospital b. optimized

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Emerging health monitoring concepts

B. Wireless ECG patch

Feature:A fork-antenna and a snap-on connector, for connection to one electrode

Maintain the overall power consumption around 10 mWfor more than 5 days autonomy with a battery of size 20x20x5 3mm

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Comparing

a. Holter device b. optimized

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3D SiP

3D SiP Wireless autonomous sensor node

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References

1.Julien Penders, Bert Gyselinckx, Ruud Vullers, Michael De Nil, Subbu Nimmala, Jef van de Molengraft, Firat Yazicioglu, Tom Torfs, Vladimir Leonov, Patrick Merken, Chris Van Hoof, “Human++: from technology to emerging health monitoring concepts “2008

2.Penders, J., Gyselinckx, B., Vullers, R., Rousseaux, O., Berekovic, M., De Nil, M., Van Hoof, C., Ryckaert, J.,Yazicioglu, R.F., Fiorini, P. and Leonov, V., 2007, in IFIP International Federation for Information Processing,Volume 249, VLSI-SoC: Research Trends in VLSI and Systems on Chip, eds. De Micheli, G., Mir, S., Reis, R.,(Boston: Springer), pp. 377–397