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A Review of Artificial Intelligence-Based Gait Evaluation and Rehabilitation in Parkinson’s Disease

Parkinson's disease (PD) is a long-term degenerative disease of the central nervous system that affects both motor and non-motor functions. In most cases, symptoms develop gradually, with non-motor symptoms increasing in frequency as the condition progresses. Tremors, stiffness, slow movements,...

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Autores principales: Jadhwani, Purvi L, Harjpal, Pallavi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cureus 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10648061/
https://www.ncbi.nlm.nih.gov/pubmed/38021909
http://dx.doi.org/10.7759/cureus.47118
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author Jadhwani, Purvi L
Harjpal, Pallavi
author_facet Jadhwani, Purvi L
Harjpal, Pallavi
author_sort Jadhwani, Purvi L
collection PubMed
description Parkinson's disease (PD) is a long-term degenerative disease of the central nervous system that affects both motor and non-motor functions. In most cases, symptoms develop gradually, with non-motor symptoms increasing in frequency as the condition progresses. Tremors, stiffness, slow movements, and difficulty walking are some of the early symptoms. There may be problems with cognition, behavior, sleep, and thinking. Dementia caused by PD becomes more common as the disease progresses. The development of PD is linked to certain sequences of motion that eventually contribute to diminished function. Patients with Parkinson's disease (PWPD) have a sluggish, scattered gait that is accompanied by intermittent freezing of gait (FOG), in which efficient heading briefly pauses. In individuals with severe PD, FOG is a neurological deficit that is related to falls and has an unfavorable impact on the patient's standard of living. Artificial intelligence (AI) and ambient intelligence (AmI) are inextricably linked as intelligence is the ability to gain new information and employ it in novel contexts. The ambience is what accompanies us, while artificial represents something developed by humans. Wearable technologies are being designed to recognize FOG and support patients in the beginning to walk again via periodic cueing. The article proposes a unique automated approach for action description that utilizes AI to carry out a non-intrusive, markerless evaluation in real-time and with full robotics. This computerized method accelerates detection and safeguards from human error. Despite significant improvements brought about by the advent of novel technologies, the available assessment platforms still fail to strike the ideal equilibrium among expenditure, diagnostic precision, velocity, and simplicity. The value of the recommended approach can be seen through a comparison of the gait parameters collected by each of the motion-tracking gadgets.
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spelling pubmed-106480612023-10-16 A Review of Artificial Intelligence-Based Gait Evaluation and Rehabilitation in Parkinson’s Disease Jadhwani, Purvi L Harjpal, Pallavi Cureus Neurology Parkinson's disease (PD) is a long-term degenerative disease of the central nervous system that affects both motor and non-motor functions. In most cases, symptoms develop gradually, with non-motor symptoms increasing in frequency as the condition progresses. Tremors, stiffness, slow movements, and difficulty walking are some of the early symptoms. There may be problems with cognition, behavior, sleep, and thinking. Dementia caused by PD becomes more common as the disease progresses. The development of PD is linked to certain sequences of motion that eventually contribute to diminished function. Patients with Parkinson's disease (PWPD) have a sluggish, scattered gait that is accompanied by intermittent freezing of gait (FOG), in which efficient heading briefly pauses. In individuals with severe PD, FOG is a neurological deficit that is related to falls and has an unfavorable impact on the patient's standard of living. Artificial intelligence (AI) and ambient intelligence (AmI) are inextricably linked as intelligence is the ability to gain new information and employ it in novel contexts. The ambience is what accompanies us, while artificial represents something developed by humans. Wearable technologies are being designed to recognize FOG and support patients in the beginning to walk again via periodic cueing. The article proposes a unique automated approach for action description that utilizes AI to carry out a non-intrusive, markerless evaluation in real-time and with full robotics. This computerized method accelerates detection and safeguards from human error. Despite significant improvements brought about by the advent of novel technologies, the available assessment platforms still fail to strike the ideal equilibrium among expenditure, diagnostic precision, velocity, and simplicity. The value of the recommended approach can be seen through a comparison of the gait parameters collected by each of the motion-tracking gadgets. Cureus 2023-10-16 /pmc/articles/PMC10648061/ /pubmed/38021909 http://dx.doi.org/10.7759/cureus.47118 Text en Copyright © 2023, Jadhwani et al. https://creativecommons.org/licenses/by/3.0/This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Neurology
Jadhwani, Purvi L
Harjpal, Pallavi
A Review of Artificial Intelligence-Based Gait Evaluation and Rehabilitation in Parkinson’s Disease
title A Review of Artificial Intelligence-Based Gait Evaluation and Rehabilitation in Parkinson’s Disease
title_full A Review of Artificial Intelligence-Based Gait Evaluation and Rehabilitation in Parkinson’s Disease
title_fullStr A Review of Artificial Intelligence-Based Gait Evaluation and Rehabilitation in Parkinson’s Disease
title_full_unstemmed A Review of Artificial Intelligence-Based Gait Evaluation and Rehabilitation in Parkinson’s Disease
title_short A Review of Artificial Intelligence-Based Gait Evaluation and Rehabilitation in Parkinson’s Disease
title_sort review of artificial intelligence-based gait evaluation and rehabilitation in parkinson’s disease
topic Neurology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10648061/
https://www.ncbi.nlm.nih.gov/pubmed/38021909
http://dx.doi.org/10.7759/cureus.47118
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