Non-intrusive sleep pattern recognition with ubiquitous sensing in elderly assistive environment

Abstract

The quality of sleep may be a reflection of an elderly individual's health state and sleep pattern is an important measurement. Recognition of sleep pattern by itself is a challenge issue, especially for elderly-care community, due to both privacy concerns and technical limitations. We propose a novel multi-parametric sensing system called sleep pattern recognition system (SPRS). This system, equipped with a combination of various non-invasive sensors, can monitor an elderly user's sleep behavior. It accumulates the detecting data from a pressure sensor matrix and ultra wide band (UWB) tags. Based on these two types of complementary sensing data, SPRS can assess the user's sleep pattern automatically via machine learning algorithms. Compared to existing systems, SPRS operates without disrupting the users' sleep. It can be used in normal households with minimal deployment. Results of tests in our real assistive apartment at the Smart Elder-care Lab are also presented in this paper.

Elderly Perception on the Internet of Things-Based Integrated Smart-Home System

“…In this regard, elderly participants often suggested taking off the sensors when sleeping because they experienced discomfort from interruption to their normal behavior patterns. However, because elderly individuals are prone to critical health conditions during sleep [ 114 ], it is important to continuously monitor physiological levels even during sleep. Therefore, we suggest an alternate smart home sensor that can continuously monitor the physiological levels of the elderly while generating no discomfort from wearable sensors.…”