Autonomous patient monitoring with a pressure sensor array

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Howell Jones, Megan




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.


Patient monitoring -- Data processing.
Signal processing -- Digital techniques -- Computer simulation.
Biomedical engineering.




Carleton University

Thesis Degree Name: 

Master of Applied Science: 

Thesis Degree Level: 


Thesis Degree Discipline: 

Engineering, Systems and Computer

Parent Collection: 

Theses and Dissertations

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