Sleeping patterns observation for bedsores and bed-side falls prevention

Abstract

Disabled or cognition impaired elderly may lie in the bed most of their time. It is important to monitor their health conditions and look out for life threatening events in and around the bed continuously. Abrupt unassisted movements may lead to falls whereas the lack of desirable movements may cause bedsores. In order to alleviate these problems, we propose automated means of continuous and unobtrusive sleeping pattern observation through pressure sensing bed. By understanding of subjects' states from observed pressure evidences, timely intervention and nursing care can be provided to subjects immediately. This enables provision of high quality care to frail and dependent elderly, and also enhances their quality of life in a cost-effective and resource-efficient manner.

Exploring needs and challenges for AI in nursing care – results of an explorative sequential mixed methods study

“…While findings and R&D on application scenarios targeting nursing-relevant phenomena and problems such as prevention of pressure ulcers or falls already exist [38][39][40][41][42][43][44][45][46][47], a lot of nursing-related health problems that are addressed by international nursing guidelines and expert standards, such as management of nutrition or pain and specific nursing assessments to identify risks and care needs seem to have hardly been taken up by R&D so far. It is striking that while expert systems for nursing care are already being reported in the literature to some extend [4], they did not play a prominent role in the online workshop or the expert interviews.…”