Quantification of Hand Motor Symptoms in Parkinson’s Disease: A Proof-of-Principle Study Using Inertial and Force Sensors

This proof-of-principle study describes the methodology and explores and demonstrates the applicability of a system, existing of miniature inertial sensors on the hand and a separate force sensor, to objectively quantify hand motor symptoms in patients with Parkinson’s disease (PD) in a clinical set...

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Published in:Annals of biomedical engineering Vol. 45; no. 10; pp. 2423 - 2436
Main Authors: van den Noort, Josien C., Verhagen, Rens, van Dijk, Kees J., Veltink, Peter H., Vos, Michelle C. P. M., de Bie, Rob M. A., Bour, Lo J., Heida, Ciska T.
Format: Journal Article
Language:English
Published: New York Springer US 01-10-2017
Springer Nature B.V
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Abstract This proof-of-principle study describes the methodology and explores and demonstrates the applicability of a system, existing of miniature inertial sensors on the hand and a separate force sensor, to objectively quantify hand motor symptoms in patients with Parkinson’s disease (PD) in a clinical setting (off- and on-medication condition). Four PD patients were measured in off- and on- dopaminergic medication condition. Finger tapping, rapid hand opening/closing, hand pro/supination, tremor during rest, mental task and kinetic task, and wrist rigidity movements were measured with the system (called the PowerGlove). To demonstrate applicability, various outcome parameters of measured hand motor symptoms of the patients in off- vs. on-medication condition are presented. The methodology described and results presented show applicability of the PowerGlove in a clinical research setting, to objectively quantify hand bradykinesia, tremor and rigidity in PD patients, using a single system. The PowerGlove measured a difference in off- vs. on-medication condition in all tasks in the presented patients with most of its outcome parameters. Further study into the validity and reliability of the outcome parameters is required in a larger cohort of patients, to arrive at an optimal set of parameters that can assist in clinical evaluation and decision-making.
AbstractList This proof-of-principle study describes the methodology and explores and demonstrates the applicability of a system, existing of miniature inertial sensors on the hand and a separate force sensor, to objectively quantify hand motor symptoms in patients with Parkinson's disease (PD) in a clinical setting (off- and on-medication condition). Four PD patients were measured in off- and on- dopaminergic medication condition. Finger tapping, rapid hand opening/closing, hand pro/supination, tremor during rest, mental task and kinetic task, and wrist rigidity movements were measured with the system (called the PowerGlove). To demonstrate applicability, various outcome parameters of measured hand motor symptoms of the patients in off- vs. on-medication condition are presented. The methodology described and results presented show applicability of the PowerGlove in a clinical research setting, to objectively quantify hand bradykinesia, tremor and rigidity in PD patients, using a single system. The PowerGlove measured a difference in off- vs. on-medication condition in all tasks in the presented patients with most of its outcome parameters. Further study into the validity and reliability of the outcome parameters is required in a larger cohort of patients, to arrive at an optimal set of parameters that can assist in clinical evaluation and decision-making.
Author Veltink, Peter H.
Verhagen, Rens
Bour, Lo J.
Heida, Ciska T.
Vos, Michelle C. P. M.
van den Noort, Josien C.
van Dijk, Kees J.
de Bie, Rob M. A.
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  givenname: Josien C.
  surname: van den Noort
  fullname: van den Noort, Josien C.
  email: j.vandennoort@vumc.nl, j.c.vandennoort@amc.uva.nl
  organization: Biomedical Signals and Systems Group, MIRA Research Institute for Biomedical Technology and Technical Medicine, University of Twente, Department of Rehabilitation Medicine, VU University Medical Center, Amsterdam Movement Sciences, Department of Radiology and Nuclear Medicine, Musculoskeletal Imaging Quantification Center, Academic Medical Center, Amsterdam Movement Sciences
– sequence: 2
  givenname: Rens
  surname: Verhagen
  fullname: Verhagen, Rens
  organization: Department of Neurology and Clinical Neurophysiology, Academic Medical Center
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  givenname: Kees J.
  surname: van Dijk
  fullname: van Dijk, Kees J.
  organization: Biomedical Signals and Systems Group, MIRA Research Institute for Biomedical Technology and Technical Medicine, University of Twente
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  givenname: Peter H.
  surname: Veltink
  fullname: Veltink, Peter H.
  organization: Biomedical Signals and Systems Group, MIRA Research Institute for Biomedical Technology and Technical Medicine, University of Twente
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  givenname: Michelle C. P. M.
  surname: Vos
  fullname: Vos, Michelle C. P. M.
  organization: Biomedical Signals and Systems Group, MIRA Research Institute for Biomedical Technology and Technical Medicine, University of Twente
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  givenname: Rob M. A.
  surname: de Bie
  fullname: de Bie, Rob M. A.
  organization: Department of Neurology and Clinical Neurophysiology, Academic Medical Center
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  givenname: Lo J.
  surname: Bour
  fullname: Bour, Lo J.
  organization: Department of Neurology and Clinical Neurophysiology, Academic Medical Center
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  givenname: Ciska T.
  surname: Heida
  fullname: Heida, Ciska T.
  organization: Biomedical Signals and Systems Group, MIRA Research Institute for Biomedical Technology and Technical Medicine, University of Twente
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Issue 10
Keywords Inertial sensors
Tremor
Fingers
Bradykinesia
Movement analysis
Rigidity
Hand
Parkinson’s disease
Language English
License Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
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Snippet This proof-of-principle study describes the methodology and explores and demonstrates the applicability of a system, existing of miniature inertial sensors on...
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StartPage 2423
SubjectTerms Adult
Biochemistry
Biological and Medical Physics
Biomedical and Life Sciences
Biomedical Engineering and Bioengineering
Biomedicine
Biophysics
Classical Mechanics
Decision making
Dopamine receptors
Drugs
Female
Fingers - pathology
Fingers - physiopathology
Hand
Hand Strength
Humans
Hypokinesia - diagnosis
Hypokinesia - pathology
Hypokinesia - physiopathology
Inertial sensing devices
Male
Middle Aged
Motor task performance
Movement disorders
Neurodegenerative diseases
Parkinson Disease - diagnosis
Parkinson Disease - pathology
Parkinson Disease - physiopathology
Parkinson's disease
Patients
Proof of Concept Study
Rigidity
Sensors
Tremor
Tremor - diagnosis
Tremor - pathology
Tremor - physiopathology
Wrist
Title Quantification of Hand Motor Symptoms in Parkinson’s Disease: A Proof-of-Principle Study Using Inertial and Force Sensors
URI https://link.springer.com/article/10.1007/s10439-017-1881-x
https://www.ncbi.nlm.nih.gov/pubmed/28726022
https://www.proquest.com/docview/1944517899
https://search.proquest.com/docview/1921126378
https://pubmed.ncbi.nlm.nih.gov/PMC5622175
Volume 45
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