1 Introduction
This thesis proposes methods of human behaviour modelling (HBM), which is used to model the behaviours of older people who live alone. This section presents the study’s aim, research questions, background, contributions, and structure.
1.1 Aim and Research Questions
This research sought to model the behaviours of older people living alone in order to detect abnormal behaviours and alert family members or caretakers when assistance was required. A person-centred approach is also considered by investigating the use of HBM in older people health care. This thesis is therefore comprised of two parts: a main technical part (Part I) a health care part (Part II).
The main research question (Part I) is as follows:
Is it possible to develop a model that can learn, recognise and predict an individual’s behaviour patterns in order to detect abnormal behaviours?
Two sub-questions were formulated regarding the health care applications of such a model (Part II):
a. What are the ethical and legal implications of applying such a model to health care?
b. What are potential users’ attitudes towards such a model?
These questions are investigated in a total of four Journal Articles and four Conference Articles, as shown in Figure 1. The main research question is examined in Journal Articles 1 [1] and 2 [2] and Conference Articles 1 [3] and 2 [4]. The sub-questions from part II are explored in Journal Articles 3 [5] and 4 [6] and Conference Article 3 [7]. Finally, Conference Article 4 [8] integrates both parts of this research.
Is it possible to develop a model that can learn, recognise and predict an individual’s behaviour patterns in order to detect abnormal behaviours?
a. What are the ethical and legal implications of applying such a model to health care?
b. What are potential users’ attitudes towards such a model?
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Figure 1. Overview of the Journal and Conference Articles.
HBM refers to Human Behaviour Modelling. HMM refers to Hidden Markov Models. HSMM refers to Hidden semi-Markov Models
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1.2 Background and Purpose
Mortality rates among older populations have greatly decreased in recent decades in developed countries [9]. In the European Union, people aged 80 or older represented 5.5% of the population in 2017, and by 2080 this is expected to more than double, to 12.7% [10]. Although this represents successes in medical advances and health care, it is also associated with increasing health expenses in ageing societies [9].
Norwegian municipalities are responsible for providing care services to all residents, as regulated by the Norwegian Municipal Health and Care Service Act of 2011. Among the care services provided by municipalities are home health care, practical assistance with daily tasks and places in nursing homes for those who need it. However, only 50% of applications for nursing homes are handled within 15 days, with residents of big cities often having to wait longer to receive care than those living in less populated areas [11], and wait times can be a burden for an individual’s family. In addition, there was a 2%
reduction of available places in nursing and retirement homes between 2015 and 2018 [12].
In 2019, 38.5% of individuals aged 65 and older live alone in Norway [13], and in 2017, 32% of people aged 80 and over used home health care–based services [14]. The average cost of these home care services was approximately 227,000 kr (approximately €23,553) per person per year in 2013, while the cost of living in a nursing home was estimated at 900,000 kr per person per year (€93,393)[7], [15]. Moreover, 77% of applications for home health care were typically handled within 15 days [11]. These numbers suggest that while nursing homes are not able to cope with increased demand in Norway, home health care is still relatively accessible and cost-effective.
The sustainability of future health care services therefore requires that governments invest in welfare technology that can help older people remain in their homes for as long as they wish to and are able to take care of themselves [16]. Welfare technology, more often referred to as ambient assisted living outside of Scandinavia, is defined as
‘technology used for environmental control, safety and well-being in particular for elderly
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and disabled people’ [17, p. 335]. Moreover, with longer lives come greater expectations of maintaining good health while ageing [18]. Welfare technology therefore also seeks to improve the quality of life of those who use it. The opportunity for older people to stay in their own homes – i.e. to age in place – is not only a cost-effective way of coping with shortages of health care facilities and professionals, but also promotes independence, by allowing individuals to remain in familiar environments, and furthermore decreases individuals’ risks of contracting infectious diseases [19], [20].
The main risks that older people face when living alone are safety-related, such as falls and dizziness [20], and welfare technology should therefore be able to mitigate these risks. Technology that can detect changes in a person’s behaviour, such as falls, can support the creation of a safer environment for that person. The work presented here is based on the theory that people’s daily activities and behaviours have discernible patterns [21], [22] that can allow for the detection of anomalies (i.e, patterns in the data that deviate from normal or expected individual behaviours) [23]. In this thesis, this type of welfare technology is referred to as HBM.
1.3 Contribution
This thesis contributes to the development of a model that can detect changes in the behaviours of a person living alone. Although several previous studies have sought to categorise human activities and behaviours [24]–[27], the identification of individual behaviours to detect abnormalities remains a largely unexplored topic. This thesis applies novel technical research to health care and reviews the ethical and legal implications of implementing welfare technology. Despite the potential advantages of applying welfare technology to ageing in place, several risks must be considered. The attitudes of older people towards welfare technology were also qualitatively explored, with the primary intention of taking older people’s opinions into consideration at all stages of research and development, thus trying to maintain a person-centred approach.
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1.4 Thesis Structure
The structure of this thesis is as follows. Chapter 2 provides an overview of the existing research on HBM and its legal and ethical implications. Chapter 3 introduces the theory underlying the research. Chapter 5 presents the dataset used in this thesis. Chapters 6 and chapter 7 summarise and discuss, respectively, the results of each Journal and Conference Article. Chapter 8 describes this research strengths and limitations, while Chapter 9 provides conclusions and directions for future work. Finally, the four Journal Articles and four Conference Articles are attached at the end of this thesis.
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