Hoogland, J.F. (2012) Sit-to-stand performance derived from a sensor based approach during a home based exerciseprogram in older adults: a pilot study. thesis, Human Movement Sciences.
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Abstract
Background and objective: Up to now, no appropriate methods exist for the evaluation of a home based exercise program. Currently used methods can only be performed in laboratory settings, are subjective or provide a small number of outcome measures. Wearable sensors, such as the Mobility Monitor (MM) and the PiN ode system, can be used to overcome these limitations. This study aimed to contribute to the development of a sensor based approach for monitoring change in STS performance during a 1 0-week home based exercise program in older adults. Methods: Twelve older adults (80.1 ± 3.6 years) performed strengthening and balance exercises three times a week and additional physical activity twice a week. Selfassessments, consisting of the Timed Up and Go test (TUG) and Five Time Sit to Stand test (FTSS), were performed in week 5, 8 and 10. For self-assessments STS performance was based upon MM data. For pre- and post-assessments STS performance was based upon Ml1 and PiNode data. Results: The intervention significantly improved TUG and FTSS durations, Berg Balance Scale and PiNode and l1M based STS performance. Sensor outcome measures had a similar sensitivity to change as clinical outcome measures. No absolute agreement was found, but a substantial to excellent relative agreement was found between l1M and PiNode based STS duration and STS peak power. A moderate to excellent relative agreement was found between standardized assessments and self-assessments, except for maximal velocity. The practical feasibility of the TUG as a self-assessment was sufficient. Conclusion: This study demonstrated that a sensor based approach can be used for the evaluation of a home based exercise program. The MM seems a suitable sensor to apply as a self-assessment tool in older adults and can be used to evaluate STS duration and STS peak power. Further development of the data analysis of the MM is required.
Item Type: | Thesis (Thesis) |
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Supervisor name: | Supervisors: and Zijlstra, Prof. Dr. W. and Geraedts, H.A.E. MSc. & and Regterschot, G. R. H. MSc. and Center for Human Movement Sciences, University Medical Cente |
Faculty: | Medical Sciences |
Date Deposited: | 25 Jun 2020 10:54 |
Last Modified: | 25 Jun 2020 10:54 |
URI: | https://umcg.studenttheses.ub.rug.nl/id/eprint/1487 |
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