Sleep Analysis for Elderly Care Using a Low-Resolution Visual Sensor Network

Abstract

Abstract. Nearly half of the senior citizens report difficulty initiating and maintaining sleep. Frequent visits to the bathroom in the middle of the night is considered as one of the major reasons for sleep disorder. This leads to serious diseases such as depression and diabetes. In this paper, we propose to use a network of cheap low-resolution visual sensors (30 × 30 pixels) for long-term activity analysis of a senior citizen in a service flat. The main focus of our research is on elderly behaviour analysis to detect health deterioration. Specifically, this paper treats the analysis of sleep patterns. Firstly, motion patterns are detected. Then, a rule-based approach on the motion patterns is proposed to determine the wake up time and sleep time. The nightly bathroom visit is identified using a classification-based model. In our evaluation, we performed experiments on 10 months of real-life data. The ground truth is collected from the diaries in which the senior citizen wrote down his sleep time and wake up time. The results show accurate extraction of the sleep durations with an overall Mean Absolute Error (MAE) of 22.91 minutes and Spearman correlation coefficient of 0.69. Finally, the nightly bathroom visits analysis indicate sleep disorder in several nights.

A Behaviour Monitoring System (BMS) for Ambient Assisted Living

“…Monitoring ADLs of the older adults allows healthcare providers to continuously monitor the functional status of the elderly, increases their ability to live independently, and allows for early detection of diseases such as Alzheimer’s [ 6 , 7 ], dementia [ 8 , 9 , 10 ] and urinary tract infection [ 11 ]. ADLs also can be used to learn daily behaviour patterns such as sleeping habits [ 12 ] or movement patterns [ 13 ].…”

Behavior Analysis for Elderly

“…In another work performed under the SONOPA project, Eldib et al propose the use of a network of visual sensors installed in an AAL environment to monitor the activities of an elderly over a long time [10]. The system is used to detect sleep patterns and bathroom visits, and subsequently can be used to find out about sleeping disorders.…”

“…Behavior analysis for the elder may require long periods of testing for reliable and robust assessment of performance. For instance in [10], the camera-based classification of sleep patterns shows distinct seasonal trends, as the amount of light in the home environment is different during winter and summer. Shorter amounts of testing, or testing in lab-conditions may produce over-confident estimates of the system's accuracy.…”