Abstract
Sleep analysis is pivotal in maintaining physical and mental health, as well as enhancing the quality of life, particularly for the elderly. Despite significant advancements in wearable sleep analysis devices in recent years, their intrusive nature often causes discomfort and reduces their acceptability among older adults. This study introduces a non-invasive method for sleep analysis utilizing tactile sensors, termed the uSkin pillow. By integrating uSkin sensors into a standard pillow, we collected data on the user’s movements during sleep. This data was processed using a Savitzky-Golay digital filter and algorithmic analysis, resulting in comprehensive sleep-related information, including movement, sleep duration, respiratory rate, and sleep positions. The study also conducted experiments to evaluate both the satisfaction of elderly users with the uSkin pillow and the accuracy of its sleep analysis capabilities. The findings confirmed that the uSkin pillow is not only user-friendly but also capable of delivering sleep analysis results that are comparable to those obtained from commercially available smart bracelets. This suggests that the uSkin pillow holds significant potential as a comfortable and effective alternative for non-invasive sleep monitoring, particularly suited for the elderly population.
Yegang Du
Assistant Professor
My research interests include intelligent system, HCI, AIoT, and pervasive computing.