Sound of Daily Living Identification Based on Hierarchical Situation Audition.

One of the key objectives in developing IoT applications is to automatically detect and identify human activities of daily living (ADLs). Mobile phone users are becoming more accepting of sharing data captured by various built-in sensors. Sounds detected by smartphones are processed in this work. We present a hierarchical identification system to recognize ADLs by detecting and identifying certain sounds taking place in a complex audio situation (AS). Three major categories of sound are discriminated in terms of signal duration. These are persistent background noise (PBN), non-impulsive long sounds (NILS), and impulsive sound (IS). We first analyze audio signals in a situation-aware manner and then map the sounds of daily living (SDLs) to ADLs. A new hierarchical audible event (AE) recognition approach is proposed that classifies atomic audible actions (AAs), then computes pre-classified portions of atomic AAs energy in one AE session, and finally marks the maximum-likelihood ADL label as the outcome. Our experiments demonstrate that the proposed hierarchical methodology is effective in recognizing SDLs and, thus, also in detecting ADLs with a remarkable performance for other known baseline systems.

Perceptions of technology among older adults.

Changes and advancements in technology have the potential to benefit older adults by promoting independence and increasing the ability to age in place. However, older adults are less likely to adopt new technology unless they see benefits to themselves. This study assessed the perceptions of 30 older adults in the Midwest concerning technology via three separate focus groups (i.e., independent apartment complex, a rural community, exercise program participants), which addressed a need in the literature (i.e., inclusion of oldest-old and rural individuals). The focus group questions included items such as what technology older adults currently used, desired improvements in technology, and the greatest challenges participants were facing or would face in the future. Overall, older adults were enthusiastic about learning new forms of technology that could help them maintain their independence and quality of life. Five themes emerged from all three focus groups: (a) Frustrations, Limitations, and Usability Concerns; (b) Transportation; (c) Help and Assistance; (d) Self-Monitoring; and (e) Gaming. The themes have important implications for future technology developed for older adults; in particular, older adults were willing and eager to adopt new technology when usefulness and usability outweighed feelings of inadequacy.

In-Home Monitoring Technology for Aging in Place: Scoping Review.

BACKGROUND: For successful aging-in-place strategy development, in-home monitoring technology is necessary as a new home modification strategy. Monitoring an older adult's daily physical activity at home can positively impact their health and well-being by providing valuable information about functional, cognitive, and social health status. However, it is questionable how these in-home monitoring technologies have changed the traditional residential environment. A comprehensive review of existing research findings should be utilized to characterize recent relative technologies and to inform design considerations. OBJECTIVE: The main purpose of this study was to classify recent smart home technologies that monitor older adults' health and to architecturally describe these technologies as they are used in older adults' homes. METHODS: The scoping review method was employed to identify key characteristics of in-home monitoring technologies for older adults. In June 2021, four databases, including Web of Science, IEEE Xplore, ACM Digital Library, and Scopus, were searched for peer-reviewed articles pertaining to smart home technologies used to monitor older adults' health in their homes. We used two search strings to retrieve articles: types of technology and types of users. For the title, abstract, and full-text screening, the inclusion criteria were original and peer-reviewed research written in English, and research on monitoring, detecting, recognizing, analyzing, or tracking human physical, emotional, and social behavior. The exclusion criteria included theoretical, conceptual, or review papers; studies on wearable systems; and qualitative research. RESULTS: This scoping review identified 30 studies published between June 2016 and 2021 providing overviews of in-home monitoring technologies, including (1) features of smart home technologies and (2) sensor locations and sensor data. First, we found six functions of in-home monitoring technology among the reviewed papers: daily activities, abnormal behaviors, cognitive impairment, falls, indoor person positioning, and sleep quality. Most of the research (n=27 articles) focused on functional monitoring and analysis, such as activities of daily living, instrumental activities of daily living, or falls among older adults; a few studies (n=3) covered social interaction monitoring. Second, this scoping review also found 16 types of sensor technologies. The most common data types encountered were passive infrared motion sensors (n=21) and contact sensors (n=19), which were used to monitor human behaviors such as bodily presence and time spent on activities. Specific locations for each sensor were also identified. CONCLUSIONS: This wide-ranging synthesis demonstrates that in-home monitoring technologies within older adults' homes play an essential role in aging in place, in that the technology monitors older adults' daily activities and identifies various health-related issues. This research provides a key summarization of in-home monitoring technologies that can be applied in senior housing for successful aging in place. These findings will be significant when developing home modification strategies or new senior housing.