Methods for Gait Analysis in a Supportive Smart Home

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Creator: 

Agarwal, Ashi

Date: 

2022

Abstract: 

According to study, the elderly's mobility habits are closely tied to cognitive decline and other age-related health problems. Regular gait analysis may help with the early detection of various disorders, but the gathering of daily ambient data is difficult with current technology. The potential of ambient sensors on the market for estimating gait speed is examined in this thesis. The thesis's first section analyses data gathered from four motion sensors that were arranged in a straight line on the ceiling as used in some wide scale studies. The findings of this work indicate that the communications protocol limits the accuracy of gait speed estimation, which prompted the investigation of AI-enabled privacy-respecting cameras. Initial results showed the camera performance was limited by low and asynchronous frame rate, which led to significant error margins. A method is proposed that reduces this to 6% using techniques based on regression and interpolation.

Subject: 

System Science
Engineering - Biomedical

Language: 

English

Publisher: 

Carleton University

Thesis Degree Name: 

Master of Applied Science: 
M.App.Sc.

Thesis Degree Level: 

Master's

Thesis Degree Discipline: 

Engineering, Electrical and Computer

Parent Collection: 

Theses and Dissertations

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