Autonomous patient monitoring with a pressure sensor array
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Unobtrusively monitoring older adults in their homes could reduce the physical and cognitive impacts of aging. The problem of autonomous extraction of nocturnal movement times and respiratory rates using a pressure sensor array in bed was investigated.Four segmentation methods were assessed for movement localization. A new movement detection segmentation algorithm accurately identified over 85% of movements. Six methods were evaluated for the extraction of breathing signals, including a recommended cascade that increased signal to noise ratio by 4.45 decibels. A proposed weighted voting algorithm was compared to two existing methods of data fusion. Finally, a reliability metric for validity evaluation was also presented.Through use of the proposed methods, respiratory rates and movement times were reliably estimated from participants who slept with a pressure sensor array below their mattress. With these parameters available, decision algorithms could be developed to alert a caregiver when intervention is necessary.
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Copyright © 2006 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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- 2006
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howelljones-autonomouspatientmonitoringwithapressuresensor.pdf | 2023-05-03 | Public | Download |