In-home monitoring technologies deployed in personal living spaces are increasingly used for the assessment of health status in older adults, through the measurement of relevant at-tributes ranging from vital parameters to activities and behaviors including mobility, gait velocity, movements in bed, and so on. Several studies agree that unobtrusive monitoring (with the exception of video-recording) is generally well accepted by older adults, especially if non-intrusive technologies are adopted (e.g., not need to wear any device) which do not interfere with daily life (e.g., not need to learn new technical skills, no change in routines, etc.). In order to address the problem of in-home automatic fall detection by continuous unobtrusive monitoring, this study investigates the use of a promising ambient technology, that is the ultra-wideband (UWB) radar sensing, which provides rich information but outside the human sensory capabilities (i.e., not directly usable for obtaining privacy-sensitive information) and thus well acceptable by end-users. Moreover, the problem of performance under real-life conditions has been addressed by suggesting an unsupervised approach not requiring fall-based training but only a subject-specific calibration phase based on observation of daily activities. Preliminary results are very encouraging, showing the effectiveness to achieve good detection performance under real-life conditions through unobtrusive monitoring.
Unobtrusive technology for in-home monitoring: Preliminary results on fall detection
Diraco Giovanni;Leone Alessandro;Siciliano Pietro
2017
Abstract
In-home monitoring technologies deployed in personal living spaces are increasingly used for the assessment of health status in older adults, through the measurement of relevant at-tributes ranging from vital parameters to activities and behaviors including mobility, gait velocity, movements in bed, and so on. Several studies agree that unobtrusive monitoring (with the exception of video-recording) is generally well accepted by older adults, especially if non-intrusive technologies are adopted (e.g., not need to wear any device) which do not interfere with daily life (e.g., not need to learn new technical skills, no change in routines, etc.). In order to address the problem of in-home automatic fall detection by continuous unobtrusive monitoring, this study investigates the use of a promising ambient technology, that is the ultra-wideband (UWB) radar sensing, which provides rich information but outside the human sensory capabilities (i.e., not directly usable for obtaining privacy-sensitive information) and thus well acceptable by end-users. Moreover, the problem of performance under real-life conditions has been addressed by suggesting an unsupervised approach not requiring fall-based training but only a subject-specific calibration phase based on observation of daily activities. Preliminary results are very encouraging, showing the effectiveness to achieve good detection performance under real-life conditions through unobtrusive monitoring.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.