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A Wearable Real-Time Auditory Feedback System to Improve Gait and Posture in Parkinson's Disease.

Record Type:	Electronic resources : Monograph/item
Title/Author:	A Wearable Real-Time Auditory Feedback System to Improve Gait and Posture in Parkinson's Disease./
Author:	Muthukrishnan, Niveditha.
Description:	1 online resource (170 pages)
Notes:	Source: Dissertations Abstracts International, Volume: 84-06, Section: B.
Contained By:	Dissertations Abstracts International84-06B.
Subject:	Biomedical engineering. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=29999952click for full text (PQDT)
ISBN:	9798363510731

A Wearable Real-Time Auditory Feedback System to Improve Gait and Posture in Parkinson's Disease.
Muthukrishnan, Niveditha.

A Wearable Real-Time Auditory Feedback System to Improve Gait and Posture in Parkinson's Disease. - 1 online resource (170 pages)

Source: Dissertations Abstracts International, Volume: 84-06, Section: B.

Thesis (Ph.D.)--Arizona State University, 2022.

Includes bibliographical references

Nearly one percent of the population over 65 years of age is living with Parkinson's disease (PD) and this population worldwide is projected to be approximately nine million by 2030. PD is a progressive neurological disease characterized by both motor and cognitive impairments. One of the most serious challenges for an individual as the disease progresses is the increasing severity of gait and posture impairments since they result in debilitating conditions such as freezing of gait, increased likelihood of falls, and poor quality of life. Although dopaminergic therapy and deep brain stimulation are generally effective, they often fail to improve gait and posture deficits. Several recent studies have employed real-time feedback (RTF) of gait parameters to improve walking patterns in PD. In earlier work, results from the investigation of the effects of RTF of step length and back angle during treadmill walking demonstrated that people with PD could follow the feedback and utilize it to modulate movements favorably in a manner that transferred, at least acutely, to overground walking. In this work, recent advances in wearable technologies were leveraged to develop a wearable real-time feedback (WRTF) system that can monitor and evaluate movements and provide feedback during daily activities that involve overground walking. Specifically, this work addressed the challenges of obtaining accurate gait and posture measures from wearable sensors in real-time and providing auditory feedback on the calculated real-time measures for rehabilitation. An algorithm was developed to calculate gait and posture variables from wearable sensor measurements, which were then validated against gold-standard measurements. The WRTF system calculates these measures and provides auditory feedback in real-time. The WRTF system was evaluated as a potential rehabilitation tool for use by people with mild to moderate PD. Results from the study indicated that the system can accurately measure step length and back angle, and that subjects could respond to real-time auditory feedback in a manner that improved their step length and uprightness. These improvements were exhibited while using the system that provided feedback and were sustained in subsequent trials immediately thereafter in which subjects walked without receiving feedback from the system.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2023

Mode of access: World Wide Web

ISBN: 9798363510731Subjects--Topical Terms:

535387
Biomedical engineering.
Subjects--Index Terms:

Parkinson's diseaseIndex Terms--Genre/Form:

542853
Electronic books.

A Wearable Real-Time Auditory Feedback System to Improve Gait and Posture in Parkinson's Disease.
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520 $a Nearly one percent of the population over 65 years of age is living with Parkinson's disease (PD) and this population worldwide is projected to be approximately nine million by 2030. PD is a progressive neurological disease characterized by both motor and cognitive impairments. One of the most serious challenges for an individual as the disease progresses is the increasing severity of gait and posture impairments since they result in debilitating conditions such as freezing of gait, increased likelihood of falls, and poor quality of life. Although dopaminergic therapy and deep brain stimulation are generally effective, they often fail to improve gait and posture deficits. Several recent studies have employed real-time feedback (RTF) of gait parameters to improve walking patterns in PD. In earlier work, results from the investigation of the effects of RTF of step length and back angle during treadmill walking demonstrated that people with PD could follow the feedback and utilize it to modulate movements favorably in a manner that transferred, at least acutely, to overground walking. In this work, recent advances in wearable technologies were leveraged to develop a wearable real-time feedback (WRTF) system that can monitor and evaluate movements and provide feedback during daily activities that involve overground walking. Specifically, this work addressed the challenges of obtaining accurate gait and posture measures from wearable sensors in real-time and providing auditory feedback on the calculated real-time measures for rehabilitation. An algorithm was developed to calculate gait and posture variables from wearable sensor measurements, which were then validated against gold-standard measurements. The WRTF system calculates these measures and provides auditory feedback in real-time. The WRTF system was evaluated as a potential rehabilitation tool for use by people with mild to moderate PD. Results from the study indicated that the system can accurately measure step length and back angle, and that subjects could respond to real-time auditory feedback in a manner that improved their step length and uprightness. These improvements were exhibited while using the system that provided feedback and were sustained in subsequent trials immediately thereafter in which subjects walked without receiving feedback from the system.
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