Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.791109
Title: Innovative intelligent sensors to objectively understand exercise interventions for older adults
Author: Ma, Jianjia
ISNI:       0000 0004 8500 8422
Awarding Body: Loughborough University
Current Institution: Loughborough University
Date of Award: 2019
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Abstract:
The population of most western countries is ageing and, therefore, the ageing issue now matters more than ever. According to the reports of the United Nations in 2017, there were a total of 15.8 million (26.9%) people over 60 years of age in the United Kindom, and the numbers are projected to reach 23.5 million (31.5%) by 2050. Spending on medical treatment and healthcare for older adults accounts for two-fifths of the UK National Health Service (NHS) budget. Keeping older people healthy is a challenge. In general, exercise is believed to benefit both mental and physical health. Specifically, resistance band exercises are proven by many studies that they have potentially positive effects on both mental and physical health. However, treatment using resistance band exercise is usually done in unmonitored environments, such as at home or in a rehabilitation centre; therefore, the exercise cannot be measured and/or quantified accurately. Despite many years of research, the true effectiveness of resistance band exercises remains unclear.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.791109  DOI:
Keywords: sensor network ; Machine Intelligence ; Sensor
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