1 / 12

Context-aware Sensing of Physiological Signals

Context-aware Sensing of Physiological Signals. Winston H. Wu, Maxim A. Batalin, Lawrence K. Au, Alex A. T. Bui, and William J. Kaiser. Introduction. Purpose-Low power consuming physiological sensors implementation

thaddeus-powers
Télécharger la présentation

Context-aware Sensing of Physiological Signals

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Context-aware Sensing of Physiological Signals Winston H. Wu, Maxim A. Batalin, Lawrence K. Au, Alex A. T. Bui, and William J. Kaiser

  2. Introduction 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

  3. Hardware Used • Commercially Available PDA with Wifi capabilities • Bluetooth modules • 3 Sensors • ECG sensor • Pulse Oximeter • 3 Axis Accelerometer-2 sets

  4. Software Inference Engine GUI Local Data Logger Device Server Device Driver

  5. Software Arcitecture

  6. Motion detection 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

  7. Communication Via Bluetooth Each data point accompanied by tracking sequence number to check for errors PDA is the master node over bluetooth network

  8. Context Aware Sensing • 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

  9. Context Aware Sensing Algorithm of an ECG signal

  10. Naïve Bayes Classifier 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

  11. Results

  12. THANK YOU

More Related