Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/135865
Title: INERTIA SENSOR-BASED MOBILITY ANALYSIS FOR PARKINSON'S DISEASE
Authors: ZHU SHENGGAO
Keywords: wearable sensors, IMU, gait analysis, PD classification
Issue Date: 17-Apr-2017
Citation: ZHU SHENGGAO (2017-04-17). INERTIA SENSOR-BASED MOBILITY ANALYSIS FOR PARKINSON'S DISEASE. ScholarBank@NUS Repository.
Abstract: Movement disorders such as Parkinson’s disease (PD) will affect a rapidly growing segment of the population as society continues to age. Without a known cure, PD is causing tremendous financial and logistical challenges for patients and society. The early diagnosis of PD and accurate assessment of PD severity stage is crucial for prompt and proper treatment. However, it currently requires a skilled doctor and specialized equipment, and it is expensive, non-scalable and prone to human error. In this thesis, we developed a cost-effective, scalable, objective and accurate system for mobility analysis and PD diagnosis. The system uses custom-built wearable inertial sensors to monitor a person’s movement such as walking and hand tremor. Novel algorithms were developed to quantify movement parameters (e.g., step time and step length) and classify the severity stage of PD. The practicality and accuracy of the system has been validated in clinical studies involving more than 80 PD patients and control subjects.
URI: http://scholarbank.nus.edu.sg/handle/10635/135865
Appears in Collections:Ph.D Theses (Open)

Show full item record
Files in This Item:
File Description SizeFormatAccess SettingsVersion 
ZhuSG.pdf7.1 MBAdobe PDF

OPEN

NoneView/Download

Page view(s)

87
checked on Dec 14, 2018

Download(s)

143
checked on Dec 14, 2018

Google ScholarTM

Check


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.