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Record Nr. |
UNINA9910869164603321 |
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Autore |
Friedrich Bjö |
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Titolo |
Empowering Independent Living using the ICF : An Unobtrusive Home Monitoring Sensor System for Older Adults / / by Björn Friedrich |
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Pubbl/distr/stampa |
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Wiesbaden : , : Springer Fachmedien Wiesbaden : , : Imprint : Springer Vieweg, , 2024 |
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ISBN |
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Edizione |
[1st ed. 2024.] |
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Descrizione fisica |
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1 online resource (141 pages) |
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Collana |
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Medicine (German Language) Series |
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Disciplina |
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Soggetti |
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Engineering mathematics |
Engineering - Data processing |
Mathematical and Computational Engineering Applications |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di bibliografia |
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Includes bibliographical references. |
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Nota di contenuto |
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Introduction -- A Deep Learning Approach for TUG and SPPB Score Prediction of (Pre–) Frail Older Adults on Real–Life IMU Data -- Detecting Impending Malnutrition of (Pre–) Frail Older Adults in Domestic Smart Home Environments -- Using Sensor Graphs for Monitoring the Effect on the Performance of the OTAGO Exercise Program in Older Adults -- Unsupervised Statistical Concept Drift Detection for Behaviour Abnormality Detection -- A System for Monitoring the Functional Status of Older Adults in Daily Life -- General Discussion. |
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Sommario/riassunto |
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Functional decline in older adults can lead to an increased need of assistance or even moving to a nursing home. Utilising home automation, power and wearable sensors, the system developed by the author continuously keeps track of the functional status of older adults through monitoring their daily life and allows health care professionals to create individualised rehabilitation programmes based on the changes in the older adult’s functional capacity and performance in daily life. The system uses the taxonomy of the International Classification of Functioning, Disability and Health (ICF) by the World Health Organization (WHO). It links sensor data to fve ICF items from three ICF categories and measures their change over time. The system successfully passed the first pre-clinical validation step on the real- |
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