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

Josien C. van den Noort, Rens Verhagen, Kees J. van Dijk, Peter H. Veltink, Michelle C.P.M. Vos, Rob M.A. de Bie, Lo J. Bour, Ciska T. Heida

    Research output: Contribution to journalArticleAcademicpeer-review

    14 Citations (Scopus)
    65 Downloads (Pure)

    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.
    Original languageEnglish
    Pages (from-to)2423-2436
    Number of pages14
    JournalAnnals of biomedical engineering
    Volume45
    Issue number10
    DOIs
    Publication statusPublished - 1 Oct 2017

    Keywords

    • Bradykinesia
    • Fingers
    • Hand
    • Inertial sensors
    • Movement analysis
    • Parkinson’s disease
    • Rigidity
    • Tremor

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