The Assessment Of In-Bed Mobility Using Pressure Sensitive Mats
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Clinical mobility tools have been shown to predict adverse outcomes in elderly patients, yet aren’t used often enough to inform hospital staff on patient health. Integrated computing has therefore become increasingly important and is predicted to improve traditional healthcare. This thesis details the design of an algorithmic system to partially automate a mobility tool. Three pressure sensitive mats were set-up on a hospital bed frame, underneath a mattress. Thirty volunteers enacted five movements on the hospital bed; each movement representative of a different mobility score. These movements generated pressure data, and a system of algorithms was constructed in a decision tree to automatically classify data. The overall system yielded 96% accuracy, where the misclassifications were due largely to inconsistencies in volunteer performance. These results suggest that this algorithmic system is effective in distinguishing between the mobility enactments examined here, and emphasizes the potential for integrated computing to improve traditional healthcare.
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Copyright © 2014 the author(s). Theses may be used for non-commercial research, educational, or related academic purposes only. Such uses include personal study, research, scholarship, and teaching. Theses may only be shared by linking to Carleton University Institutional Repository and no part may be used without proper attribution to the author. No part may be used for commercial purposes directly or indirectly via a for-profit platform; no adaptation or derivative works are permitted without consent from the copyright owner.
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- 2014
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bennett-theassessmentofinbedmobilityusingpressure.pdf | 2023-05-04 | Public | Download |