Abstract
Sensor technologies make it possible to monitor older people’s homes and activities and to detect human perfor-mance 24/7. A promising application in the field is the detection of decreasing functional and cognitive perfor-mance. Sensor technology, paired with adequate monitoring and assessment systems, can enable the monitoring of such parameters and detect symptoms and minor problems in cognitive functioning earlier than was previously possible. Instead of intervening only when the signs of cognitive decline are obvious, data generated by multiple sensors make it possible to detect minor changes in a person’s daily activities. Early recognition of chronic illness-es or memory disorder, for example, can pave the way for more accurate treatment and have a remarkable influ-ence on people’s lives, and even let them remain active and independent for longer.
In the Bewell Happy-project, the team analysed the ‘forms of life’ of a cohort of volunteer end users to identify the daily routines and activities they typically carry out. They also clarified why the volunteers did these activities, what value was associated with them and how they were structured, guided by the principles of human-technology interaction design as set out by Life Based Design approach. The created model also referenced the World Health Organization’s International Classification of Functioning, Disability and Health (ICF) – the frame-work for measuring health and disability at both individual and population levels.
Sensor technology placed in senior citizens’ homes to create an intelligent ambient environment gathered infor-mation about how well senior citizens were performing their usual activities and revealed possible changes in their daily habits. This information enables any variations in their activity levels to be discovered and visualised. The data complements traditional health-related information, leading to integrated understanding of the person’s daily performance. These technologies also reveal acute or gradual changes that indicate a need for professional inter-vention.
In BeWell Happy pilot study, home tracking systems were installed in the homes of 14 volunteer participants aged between 74 and 91. The tracking systems consisted of three motion sensors and two door sensors placed in lo-cations that were significant in the participants’ usual routines. The results of the study highlight the value of col-lecting objective data about older people’s activities over a long-term period.
In the Bewell Happy-project, the team analysed the ‘forms of life’ of a cohort of volunteer end users to identify the daily routines and activities they typically carry out. They also clarified why the volunteers did these activities, what value was associated with them and how they were structured, guided by the principles of human-technology interaction design as set out by Life Based Design approach. The created model also referenced the World Health Organization’s International Classification of Functioning, Disability and Health (ICF) – the frame-work for measuring health and disability at both individual and population levels.
Sensor technology placed in senior citizens’ homes to create an intelligent ambient environment gathered infor-mation about how well senior citizens were performing their usual activities and revealed possible changes in their daily habits. This information enables any variations in their activity levels to be discovered and visualised. The data complements traditional health-related information, leading to integrated understanding of the person’s daily performance. These technologies also reveal acute or gradual changes that indicate a need for professional inter-vention.
In BeWell Happy pilot study, home tracking systems were installed in the homes of 14 volunteer participants aged between 74 and 91. The tracking systems consisted of three motion sensors and two door sensors placed in lo-cations that were significant in the participants’ usual routines. The results of the study highlight the value of col-lecting objective data about older people’s activities over a long-term period.
| Translated title of the contribution | Ambient detection of and adaptation to emerging cognitive disorders |
|---|---|
| Original language | Finnish |
| Title of host publication | Ikääntyminen ja teknologia |
| Publisher | VTT Technical Research Centre of Finland |
| Pages | 18-23 |
| ISBN (Electronic) | 978-951-38-8613-4 |
| ISBN (Print) | 978-951-38-8612-7 |
| Publication status | Published - 2017 |
| MoE publication type | D2 Article in professional manuals or guides or professional information systems or text book material |
Publication series
| Series | VTT Research Highlights |
|---|---|
| Number | 14 |
| ISSN | 2242-1173 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- sensor technologies
- ageing
- ethics
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Ikääntyminen ja teknologia
Leikas, J. (Editor), 2017, VTT Technical Research Centre of Finland. 192 p. (VTT Research Highlights; No. 14).Translated title of the contribution :Ageing and technology Research output: Book/Report › Report
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