Engineering Commons^™

Recognition Of Smoking Gesture Using Smart Watch Technology, Casey A. Cole, Bethany Janos, Dien Anshari, James Thrasher, Scott Strayer, Homayoun Valafar

Faculty Publications

Diseases resulting from prolonged smoking are the most common preventable causes of death in the world today. In this report we investigate the success of utilizing accelerometer sensors in smart watches to identify smoking gestures. Early identification of smoking gestures can help to initiate the appropriate intervention method and prevent relapses in smoking. Our experiments indicate 85%-95% success rates in identification of smoking gesture among other similar gestures using Artificial Neural Networks (ANNs). Our investigations concluded that information obtained from the x-dimension of accelerometers is the best means of identifying the smoking gesture, while y and z dimensions are helpful …