Autonomous patient monitoring with a pressure sensor array

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Creator: 

Howell Jones, Megan

Date: 

2006

Abstract: 

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.

Subject: 

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

Language: 

English

Publisher: 

Carleton University

Thesis Degree Name: 

Master of Applied Science: 
M.App.Sc.

Thesis Degree Level: 

Master's

Thesis Degree Discipline: 

Engineering, Systems and Computer

Parent Collection: 

Theses and Dissertations

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