winston h. wu, maxim a. batalin, lawrence k. au, alex a. t. bui, and william j. kaiser

Winston H. Wu, Maxim A. Batalin, Lawrence K. Au, Alex A. T. Bui, and William J. Kaiser

Purpose-Low power consuming physiological sensors implementation

Energy use decreased by enabling & disabling the sensors to real time measurement demand

Use low cost sensors to schedule high cost sensors like ECG sensors

Commercially Available PDA with Wifi capabilities

Bluetooth modules 3 Sensorso ECG sensoro Pulse Oximetero 3 Axis Accelerometer-2 sets

Inference Engine GUI Local Data Logger Device Server Device Driver

Pulse oximeter used to detect start of the exercise

2 Accelerometers used to detect end of the exercise

1 on right ankle and 1 on left hip Inference engine on the wearable

system computes when to activate ECG sensor

Data collected is streamed to a central server via Wifi Network

Each data point accompanied by tracking sequence number to check for errors

PDA is the master node over bluetooth network

Feature Extraction Pulse rate and SpO2 value-rate of decline of

oxygen saturation Accelerometer• Since cyclical movements are involved• Features from spectral domain are used• In general case features from time domain

may be used• 512 data points window-100 points entered

every second• 2 spectral feature values extracted from

each axis -f peak and f energy

P(C/F) Where C is the patient states of interest F is the feature vector

Pulse classification as Low , Medium, High When high Accelerometer activated Accelerometer classifies as Rest , Walk, Jog, Run If Jog or Run ECG sensor not activated Else it is activated

ResultsResults