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Article

Hand Pronation–Supination Movement as a Proxy for Remotely Monitoring Gait and Posture Stability in Parkinson’s Disease

1
Department of Anatomy, School of Biomedical Sciences, University of Otago, Dunedin 9054, New Zealand
2
Medical Technologies Centre of Research Excellence, Auckland 1142, New Zealand
3
Centre for Health Systems and Technology, Dunedin 9054, New Zealand
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Centre for Bioengineering and Nanotechnology, Point-of-Care Technologies, Dunedin 9054, New Zealand
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Department of Health Informatics, Middle East Technical University, Ankara 06800, Turkey
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Global Dynamic Systems ARGE, Teknopark Istanbul, Istanbul 34906, Turkey
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Department of Neurology, Cerrahpasa Medical Faculty, Istanbul University-Cerrahpasa, Istanbul 34098, Turkey
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Department of Neurology, School of Medicine, Koç University, Istanbul 34010, Turkey
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Research Centre for Translational Medicine (KUTTAM), Koç University, Istanbul 34010, Turkey
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Academic Editor: Giuseppe Lacidogna
Sensors 2022, 22(5), 1827; https://doi.org/10.3390/s22051827
Received: 15 November 2021 / Revised: 11 February 2022 / Accepted: 14 February 2022 / Published: 25 February 2022
(This article belongs to the Topic Recent Advances in Structural Health Monitoring)
The Unified Parkinson’s Disease Rating Scale (UPDRS) is a subjective Parkinson’s Disease (PD) physician scoring/monitoring system. To date, there is no single upper limb wearable/non-contact system that can be used objectively to assess all UPDRS-III motor system subgroups (i.e., tremor (T), rigidity (R), bradykinesia (B), gait and posture (GP), and bulbar anomalies (BA)). We evaluated the use of a non-contact hand motion tracking system for potential extraction of GP information using forearm pronation–supination (P/S) motion parameters (speed, acceleration, and frequency). Twenty-four patients with idiopathic PD participated, and their UPDRS data were recorded bilaterally by physicians. Pearson’s correlation, regression analyses, and Monte Carlo validation was conducted for all combinations of UPDRS subgroups versus motion parameters. In the 262,125 regression models that were trained and tested, the models within 1% of the lowest error showed that the frequency of P/S contributes to approximately one third of all models; while speed and acceleration also contribute significantly to the prediction of GP from the left-hand motion of right handed patients. In short, the P/S better indicated GP when performed with the non-dominant hand. There was also a significant negative correlation (with medium to large effect size, range: 0.3–0.58) between the P/S speed and the single BA score for both forearms and combined UPDRS score for the dominant hand. This study highlights the potential use of wearable or non-contact systems for forearm P/S to remotely monitor and predict the GP information in PD. View Full-Text
Keywords: gait; posture; Parkinson’s disease; pronation; supination; bulbar anomalies gait; posture; Parkinson’s disease; pronation; supination; bulbar anomalies
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MDPI and ACS Style

Cakmak, Y.O.; Olcek, C.; Ozsoy, B.; Khwaounjoo, P.; Kiziltan, G.; Apaydin, H.; Günduz, A.; Oztop Cakmak, O.; Ertan, S.; Gursoy-Ozdemir, Y.; Gokcay, D. Hand Pronation–Supination Movement as a Proxy for Remotely Monitoring Gait and Posture Stability in Parkinson’s Disease. Sensors 2022, 22, 1827. https://doi.org/10.3390/s22051827

AMA Style

Cakmak YO, Olcek C, Ozsoy B, Khwaounjoo P, Kiziltan G, Apaydin H, Günduz A, Oztop Cakmak O, Ertan S, Gursoy-Ozdemir Y, Gokcay D. Hand Pronation–Supination Movement as a Proxy for Remotely Monitoring Gait and Posture Stability in Parkinson’s Disease. Sensors. 2022; 22(5):1827. https://doi.org/10.3390/s22051827

Chicago/Turabian Style

Cakmak, Yusuf O., Can Olcek, Burak Ozsoy, Prashanna Khwaounjoo, Gunes Kiziltan, Hulya Apaydin, Aysegul Günduz, Ozgur Oztop Cakmak, Sibel Ertan, Yasemin Gursoy-Ozdemir, and Didem Gokcay. 2022. "Hand Pronation–Supination Movement as a Proxy for Remotely Monitoring Gait and Posture Stability in Parkinson’s Disease" Sensors 22, no. 5: 1827. https://doi.org/10.3390/s22051827

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