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

Annals of Biomedical Engineering, Jul 2017

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.

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

Quantification of Hand Motor Symptoms in Parkinson's Disease: A Proof-of-Principle Study Using Inertial and Force Sensors JOSIEN C. VAN DEN NOORT 0 1 3 4 5 RENS VERHAGEN 1 2 3 KEES J. VAN DIJK 1 3 4 PETER H. VELTINK 1 3 4 MICHELLE C. P. M. VOS 1 3 4 ROB M. A. DE BIE 1 2 3 LO J. BOUR 1 2 3 CISKA T. HEIDA 1 3 4 0 Department of Rehabilitation Medicine, VU University Medical Center, Amsterdam Movement Sciences , Amsterdam , The Netherlands 1 Signals and Systems Group, MIRA Research Institute for Biomedical Technology and Technical Medicine, University of Twente , P.O. Box 217, 7500 AE Enschede , The Netherlands. Electronic mails: 2 Department of Neurology and Clinical Neurophysiology, Academic Medical Center , Amsterdam , The Netherlands 3 sia , Tremor, Rigidity, Inertial sensors, Movement analysis 4 Biomedical Signals and Systems Group, MIRA Research Institute for Biomedical Technology and Technical Medicine, University of Twente , P.O. Box 217, 7500 AE Enschede , The Netherlands 5 Department of Radiology and Nuclear Medicine, Musculoskeletal Imaging Quantification Center, Academic Medical Center, Amsterdam Movement Sciences , Amsterdam , The Netherlands -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. Parkinson's disease; Hand; Fingers; Bradykine- INTRODUCTION Parkinson’s disease (PD) is an age-related neurodegenerative disorder, second in prevalence to Alzheimer’s disease.4 In current practice, the severity of the motor symptoms that partially defines the clinical condition of a PD patient is scored during a standardized neurological examination, using the motor examination part of the unified Parkinson’s disease rating scale (UPDRS-ME).9,14 Assessment of hand movements is an important part of the UPDRS-ME and includes items for bradykinesia, hand tremor and wrist rigidity.8–10,19,27 These are symptoms that strongly respond to dopaminergic medication and deep brain stimulation (DBS) and are therefore often used to judge the effects of these therapies. However, the assessment of the corresponding movements may often vary between clinicians and depends on the level of experience of the neurologist or movement disorder nurse. This subjective nature introduces extra variability to the UPDRS-ME.27,28,30,31,34 Furthermore, the current clinical exam may not be able to detect small changes as all items are scored on a five-point scale.8,27,30,31 A single scoring may be dependent on multiple measures such as speed, amplitude, decrease in amplitude over time, and occurrence of hesitations. To adequately study the PD motor symptoms including the effects of medication or DBS and the fluctuations over a period of time, it is worthwhile to find an objective and quantified measure of (the specific components of) these symptoms. 2017 The Author(s). This article is an open access publication Objective quantification of PD hand motor symptoms has been the subject of several studies (examples are given in Table 1). However, previous studies had some limitations since their systems were either very complex (e.g. Ref. 26,29), unable to measure all hand motor symptoms in one assessment (e.g. Ref. 11,12,16,24,31), or not applied in patients (e.g. Ref. 3). Therefore, these systems are not easily available and/or often clinically not applicable. In this study, an alternative system to obtain accurate hand and finger kinematics in PD patients is proposed, called the PowerGlove system, which is a combination of miniature inertial and magnetic sensors on each finger segment and the back of the hand.21 Combination of these sensors enables a 3D reconstruction of the movements of all finger joints and the orientation of the hand. In comb (...truncated)


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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. Quantification of Hand Motor Symptoms in Parkinson’s Disease: A Proof-of-Principle Study Using Inertial and Force Sensors, Annals of Biomedical Engineering, 2017, pp. 1-14, DOI: 10.1007/s10439-017-1881-x