A Paradigm Shift in the Management of Patients with Parkinson's Disease
Tsamis, Konstantinos I. ; Odin, Per LU
; Antonini, Angelo
; Reichmann, Heinz
and Konitsiotis, Spyridon
(2023)
In Neurodegenerative Diseases
23(1-2).
p.13-19
- Abstract
Background: Technological evolution leads to the constant enhancement of monitoring systems and recording symptoms of diverse disorders. Summary: For Parkinson's disease, wearable devices empowered with machine learning analysis are the main modules for objective measurements. Software and hardware improvements have led to the development of reliable systems that can detect symptoms accurately and be implicated in the follow-up and treatment decisions. Key Messages: Among many different devices developed so far, the most promising ones are those that can record symptoms from all extremities and the trunk, in the home environment during the activities of daily living, assess gait impairment accurately, and be suitable for a long-term... (More)
Background: Technological evolution leads to the constant enhancement of monitoring systems and recording symptoms of diverse disorders. Summary: For Parkinson's disease, wearable devices empowered with machine learning analysis are the main modules for objective measurements. Software and hardware improvements have led to the development of reliable systems that can detect symptoms accurately and be implicated in the follow-up and treatment decisions. Key Messages: Among many different devices developed so far, the most promising ones are those that can record symptoms from all extremities and the trunk, in the home environment during the activities of daily living, assess gait impairment accurately, and be suitable for a long-term follow-up of the patients. Such wearable systems pave the way for a paradigm shift in the management of patients with Parkinson's disease.
(Less)
- author
- Tsamis, Konstantinos I.
; Odin, Per
LU
; Antonini, Angelo
; Reichmann, Heinz
and Konitsiotis, Spyridon
- organization
- publishing date
- 2023-12-01
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Decision-making, Follow-up, Movement disorders, Parkinson's disease, Symptom detection, Wearables
- in
- Neurodegenerative Diseases
- volume
- 23
- issue
- 1-2
- pages
- 7 pages
- publisher
- Karger
- external identifiers
-
- pmid:37913759
- scopus:85178144928
- ISSN
- 1660-2854
- DOI
- 10.1159/000533798
- language
- English
- LU publication?
- yes
- id
- ee4a4c99-6bff-4e35-849c-6ec1654a19f7
- date added to LUP
- 2024-01-09 12:09:17
- date last changed
- 2024-04-24 08:04:42
@article{ee4a4c99-6bff-4e35-849c-6ec1654a19f7,
abstract = {{<p>Background: Technological evolution leads to the constant enhancement of monitoring systems and recording symptoms of diverse disorders. Summary: For Parkinson's disease, wearable devices empowered with machine learning analysis are the main modules for objective measurements. Software and hardware improvements have led to the development of reliable systems that can detect symptoms accurately and be implicated in the follow-up and treatment decisions. Key Messages: Among many different devices developed so far, the most promising ones are those that can record symptoms from all extremities and the trunk, in the home environment during the activities of daily living, assess gait impairment accurately, and be suitable for a long-term follow-up of the patients. Such wearable systems pave the way for a paradigm shift in the management of patients with Parkinson's disease.</p>}},
author = {{Tsamis, Konstantinos I. and Odin, Per and Antonini, Angelo and Reichmann, Heinz and Konitsiotis, Spyridon}},
issn = {{1660-2854}},
keywords = {{Decision-making; Follow-up; Movement disorders; Parkinson's disease; Symptom detection; Wearables}},
language = {{eng}},
month = {{12}},
number = {{1-2}},
pages = {{13--19}},
publisher = {{Karger}},
series = {{Neurodegenerative Diseases}},
title = {{A Paradigm Shift in the Management of Patients with Parkinson's Disease}},
url = {{http://dx.doi.org/10.1159/000533798}},
doi = {{10.1159/000533798}},
volume = {{23}},
year = {{2023}},
}