关键词: 疲劳评估, 键盘鼠标事件, 社交网络, 健康促进, 随机森林

Abstract: Long-term continuous use of computers would bring negative effects on users' health. In order to detect users fatigue level in a non-invasive manner, an approach that is able to measure fatigue level on hand muscle based on the keyboard and mouse events was proposed. The proposed method integrated keying action match, data noise filtering, and feature vector extraction/classification together to collect and analyze the delay characteristics of both keying and hitting actions, upon which the detection of fatigue level on hand muscle could be enabled. With the detected fatigue level, friends belonging to the same virtual community on current social networks could be, in real-time, alerted and persuaded to take a health-conscious way in their daily use of computers. Particularly, an interesting conclusion has been made that there is an obvious negative correlation between keying (hitting) delay and fatigue level of hand muscle. The experimental validation conducted on two-week data collected from 15 participants shows that the proposed method is effective in detecting users fatigue level and distributing fatigue-related health information on social network platform.

Key words: fatigue evaluation, keyboard and mouse event, social network, health promotion, random forest