The LifeMinder wearable healthcare support system algorithms recognized user movement and detected the beginning of a meal with an accuracy of about 90%.
A prototype wearable system, LifeMinder, achieved approximately 90% accuracy in detecting user movement and meal initiation for lifestyle monitoring.
Introduces a prototype of wearable healthcare support system 'LifeMinder', which consists of a wristwatch-shaped wearable sensor module and a personal digital assistant (PDA). The wearable sensor module, equipped with sensors of accelerometer, pulse meter thermometer galvanic skin reflex (GSR) electrodes and Bluetooth module to communicate with the PDA, monitors the user context: health conditions, movements and behaviors. The system uses this information to guide the user in daily self-care in real time. Diet care and exercise care are especially significant to prevent the "lifestyle-related disease". The authors developed algorithms to recognize the user movement from wrist motion and to detect the beginning of a meal from pulse rates and GSR values. The accuracy of both algorithms is about 90%.
Ouchi et al. (Wed,) conducted a other in Lifestyle-related disease prevention. LifeMinder wearable healthcare support system was evaluated on Accuracy of algorithms to recognize user movement and detect the beginning of a meal. The LifeMinder wearable healthcare support system algorithms recognized user movement and detected the beginning of a meal with an accuracy of about 90%.