Personalization of monitoring system parameters to support ambulatory care for dementia patients

Dementia affected 47 million people worldwide in 2016, which caused $ 818 billions of estimated costs in total. Due to high costs and inadequate governmental support, over 90 % of people with dementia in low- and middle-income countries need to be cared for at home. However, the multitude of implications overburdens both the people affected as well as their caregivers. Existing health monitoring systems for ambulatory care only offer dementia-specific support functions in combination with a variety of sensors, applications and administration efforts. Therefore, we present a method to support ambulatory care with simple ambient sensor settings. Our approach is intended to model the behaviour of the resident to derive habits and possible anomalies regarding dementia. To support planning of care measures and detect dementia onset, we start with day-night rhythm and night-time activity as relevant parameters, since they are associated with dementia and are beneficial for the implementation of care. Our primary objective is to automate the personalization of existing monitoring systems with as few ambient sensors as possible. The challenge of this work is to learn these parameters from a brief sensor data history about people who are living alone, are unable to handle wearable devices and cannot give autonomous feedback on their activities of daily living.

I. Introduction

According to the World Health Organization (WHO), dementia is among the main causes for disability and dependency of elderly people worldwide [1]. The western biomedical perception of dementia defines it as clinical syndrome. It is characterized as an occurrence of symptoms, which can be linked to the impairment in cognitive functions e.g. memory, learning capacity or language and their steady decline that cannot be traced back to normal age-related restrictions. These symptoms are often accompanied or preceded by a lack of motivation, decreasing emotional control and altered social behaviour [2]. But there are not only physical, psychological or social implications. Due to medical costs and care also economic consequences should be considered [1]. In 2016, 47 million people worldwide suffered from dementia, which causes $ 818 billions of costs in total and will become a trillion-dollar disease by 2018. The number of people suffering from dementia is estimated to increase up to 131 million by 2050 [3]. It is assumed that 94 % of people with dementia in low-and middle-income countries are cared for at home because the cost of care in a nursing home is too high or the health care systems offer insufficient support for people with dementia and their families [4]. As the most significant problem and reason for the placement of dependent persons in nursing homes, caregivers report sleep disruptions. People with dementia can have sleep disturbance up to a change of the day-night rhythm, which also affects caregivers and their environment. Also, 40 % of injuries occuring at night time are reported as a result of night falls [5]. The association of dementia with the disturbance of circadian rhythms like rest or activity cycles has been documented by several studies, too [6]–[10].