Validation of Inertial Sensing-Based Wearable Device for Tremor and Bradykinesia Quantification
- 15 July 2020
- journal article
- research article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Journal of Biomedical and Health Informatics
- Vol. 25 (4), 997-1005
- https://doi.org/10.1109/jbhi.2020.3009319
Abstract
Neurologists judge the severity of Parkinsonian motor symptoms according to clinical scales, and their judgments exist inconsistent because of differences in clinical experience. Correspondingly, inertial sensing-based wearable devices (ISWDs) produce objective and standardized quantifications. However, ISWDs indirectly quantify symptoms by parametric modeling of angular velocities and linear accelerations and trained by the judgments of several neurologists through supervised learning algorithms. Hence, the ISWD outputs are biased along with the scores provided by neurologists. To investigate the effectiveness ISWDs for Parkinsonian symptoms quantification, technical verification and clinical validation of both tremor and bradykinesia quantification methods were carried out. A total of 45 Parkinson's disease patients and 30 healthy controls performed the tremor and finger-tapping tasks, which were tracked simultaneously by an ISWD and a 6-axis high-precision electromagnetic tracking system (EMTS). The Unified Parkinson's Disease Rating Scale (UPDRS) prescribed parameters obtained from the EMTS, which directly provides linear and rotational displacements, were compared with the scores provided by both the ISWD and seven neurologists. EMTS-based parameters were regarded as the ground truth and were employed to train several common machine learning (ML) algorithms, i.e., support vector machine (SVM), k-nearest neighbors (KNN), and random forest (RF) algorithms. Inconsistency among the scores provided by the neurologists was proven. Besides, the quantification performance (sensitivity, specificity, and accuracy) of the ISWD employed with ML algorithms were better than that of the neurologists. Furthermore, EMTS can be utilized to both modify the quantification algorithms of ISWDs and improve the assessment skills of young neurologists.Keywords
Funding Information
- National Natural Science Foundation of China (61973293)
- Joint Funds for the Innovation of Science and Technology of Fujian Province (2017Y9010)
- Key Project of Foreign Cooperation for the International Partner Program of the Chinese Academy of Sciences (121835KYSB20190069)
- Quanzhou Science and Technology (2019STS06/2019C012R)
- Science and technology program of Fujian Province (2018H2001)
- Fujian Provincial Science and Technology Guiding Project (2018Y0033)
This publication has 38 references indexed in Scilit:
- Hand Pose Estimation by Fusion of Inertial and Magnetic Sensing Aided by a Permanent MagnetIEEE Transactions on Neural Systems and Rehabilitation Engineering, 2014
- Dynamical Learning and Tracking of Tremor and Dyskinesia From Wearable SensorsIEEE Transactions on Neural Systems and Rehabilitation Engineering, 2014
- Unified Parkinson’s Disease Rating Scale‐Motor Exam: inter‐rater reliability of advanced practice nurse and neurologist assessmentsJournal of Advanced Nursing, 2010
- Testing objective measures of motor impairment in early Parkinson's disease: Feasibility study of an at‐home testing deviceMovement Disorders, 2009
- The Wilcoxon–Mann–Whitney test under scrutinyStatistics in Medicine, 2009
- Clinically deployable Kinesia™ technology for automated tremor assessmentMovement Disorders, 2009
- Movement Disorder Society‐sponsored revision of the Unified Parkinson's Disease Rating Scale (MDS‐UPDRS): Scale presentation and clinimetric testing resultsMovement Disorders, 2008
- Species associations: the Kendall coefficient of concordance revisitedJournal of Agricultural, Biological and Environmental Statistics, 2005
- The Unified Parkinson's Disease Rating Scale (UPDRS): Status and recommendationsMovement Disorders, 2003
- Interrater reliability of the unified Parkinson's disease rating scale motor examinationMovement Disorders, 1994