Dasgupta, Pritika
(2021)
Acceleration Signals In Determining Gait-Related Difficulties And The Motor Skill Of Walking In Older Adults.
Doctoral Dissertation, University of Pittsburgh.
(Unpublished)
Abstract
In adults 65 years or older, falls or other neuromotor dysfunctions are often framed as walking-related declines in motor skill; the frequent occurrence of such decline in walking-related motor skill motivates the need for an improved understanding of motor skill in walking. Simple gait measurements, such as speed, do not provide adequate information about the quality of the translation of the body motion during walking. Furthermore, there is a great need in the clinical literature and clinical practice for more accurate measures of the loss of the motor skill of walking, so that clinical practice can provide better therapeutic interventions to improve the motor skill of walking. This dissertation suggests a consensus on what the motor skill of walking is and dissects it into seven interrelated characteristics and traits. Subsequently, we purport that these characteristics of the motor skill of walking cannot be represented by simple gait measurements or raw sensor measurements alone. Gait measures from accelerometers placed on the lower trunk, or trunk-acceleration gait measures, can enrich measurements of walking and motor performance. To support our claim, we will map these acceleration gait measures (AGMs) to the various aspects of the motor skill of walking. Additionally, influential AGMs will be elected through feature selection methods. Various machine learning algorithms ranging from logistic regression, non-linear regression, evolutionary algorithms, and ensemble methods will be used to make predictions on age-related gait-related difficulty outcomes (such as fall risk). Overall, we hope to find that the combination of high-fidelity artificial intelligence algorithms and acceleration gait measures derived from low-cost sensors can fulfill the severe and crucial need for the clinical measurement of the motor skill of walking in older adults.
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Details
| Item Type: |
University of Pittsburgh ETD
|
| Status: |
Unpublished |
| Creators/Authors: |
|
| ETD Committee: |
| Title | Member | Email Address | Pitt Username | ORCID |
|---|
| Committee Chair | Sejdić, Ervin | | | | | Committee Member | Lu, Xinghua | | | | | Committee Member | VanSwearingen, Jessie | | | | | Committee Member | Redfern, Mark | | | | | Committee Member | Triantafillou, Sofia | | | |
|
| Date: |
16 June 2021 |
| Date Type: |
Publication |
| Defense Date: |
23 April 2021 |
| Approval Date: |
16 June 2021 |
| Submission Date: |
12 May 2021 |
| Access Restriction: |
1 year -- Restrict access to University of Pittsburgh for a period of 1 year. |
| Number of Pages: |
165 |
| Institution: |
University of Pittsburgh |
| Schools and Programs: |
School of Medicine > Biomedical Informatics |
| Degree: |
PhD - Doctor of Philosophy |
| Thesis Type: |
Doctoral Dissertation |
| Refereed: |
Yes |
| Uncontrolled Keywords: |
motor control, motor skill, movement control, acceleration, wearables, gait, clinical informatics, machine learning, feature specifi�cation |
| Date Deposited: |
16 Jun 2021 16:51 |
| Last Modified: |
16 Jun 2022 05:15 |
| URI: |
http://d-scholarship.pitt.edu/id/eprint/41076 |
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