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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