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      Continuous tremor monitoring in Parkinson’s disease: A wristwatch-inspired triboelectric sensor approach

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          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Summary

          Parkinson’s disease (PD) prevalence is projected to reach 12 million by 2040. Wearable sensors offer a promising approach for comfortable, continuous tremor monitoring to optimize treatment strategies. Here, we present a wristwatch-like triboelectric sensor (WW-TES) inspired by automatic watches for unobtrusive PD tremor assessment. The WW-TES utilizes a free-standing design with a surface-modified polytetrafluoroethylene (PTFE) film and a stainless-steel rotor within a biocompatible polylactic acid (PLA) package. Electrode distance is optimized to maximize the output signal. We propose and discuss the WW-TES working mechanism. The final design is validated for activities of daily living (ADLs), with varying signal amplitudes corresponding to tremor severity levels ("normal" to "severe") based on MDS-UPDRS tremor frequency. Wavelet packet transform (WPT) is employed for signal analysis during ADLs. The WW-TES demonstrates the potential for continuous tremor monitoring, offering an accurate screening of severity and comfortable, unobtrusive wearability.

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          Highlights

          • •

            Developed a wristwatch-like PD tremor sensor (WW-TES) inspired by automatic watches

          • •

            Optimized electrode spacing for enhanced signal distinction

          • •

            Proposed a working mechanism aligning with WW-TES output signals

          • •

            Signal amplitude correlates with tremor severity levels in tests

          Abstract

          Health sciences; Natural sciences; Materials science

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          Most cited references52

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          Movement Disorder Society-sponsored revision of the Unified Parkinson's Disease Rating Scale (MDS-UPDRS): scale presentation and clinimetric testing results.

          Christopher G. Goetz, Barbara C. Tilley, Stephanie Shaftman … (2008)
          We present a clinimetric assessment of the Movement Disorder Society (MDS)-sponsored revision of the Unified Parkinson's Disease Rating Scale (MDS-UPDRS). The MDS-UDPRS Task Force revised and expanded the UPDRS using recommendations from a published critique. The MDS-UPDRS has four parts, namely, I: Non-motor Experiences of Daily Living; II: Motor Experiences of Daily Living; III: Motor Examination; IV: Motor Complications. Twenty questions are completed by the patient/caregiver. Item-specific instructions and an appendix of complementary additional scales are provided. Movement disorder specialists and study coordinators administered the UPDRS (55 items) and MDS-UPDRS (65 items) to 877 English speaking (78% non-Latino Caucasian) patients with Parkinson's disease from 39 sites. We compared the two scales using correlative techniques and factor analysis. The MDS-UPDRS showed high internal consistency (Cronbach's alpha = 0.79-0.93 across parts) and correlated with the original UPDRS (rho = 0.96). MDS-UPDRS across-part correlations ranged from 0.22 to 0.66. Reliable factor structures for each part were obtained (comparative fit index > 0.90 for each part), which support the use of sum scores for each part in preference to a total score of all parts. The combined clinimetric results of this study support the validity of the MDS-UPDRS for rating PD.
          Article 0 comments Cited 1571 times – based on 0 reviews     Review now
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            Triboelectric Nanogenerator Based on Fully Enclosed Rolling Spherical Structure for Harvesting Low-Frequency Water Wave Energy

            Simiao Niu, Fang Yi, Zheng You … (2015)
            Article 0 comments Cited 151 times – based on 0 reviews     Review now
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              Self-Powered and Self-Functional Cotton Sock Using Piezoelectric and Triboelectric Hybrid Mechanism for Healthcare and Sports Monitoring

              Minglu Zhu, Qiongfeng Shi, Tianyiyi He … (2019)
              Wearable devices rely on hybrid mechanisms that possess the advantages of establishing a smarter system for healthcare, sports monitoring, and smart home applications. Socks with sensing capabilities can reveal more direct sensory information on the body for longer duration in daily life. However, the limitation of suitable materials for smart textile makes the development of multifunctional socks a major challenge. In this paper, we have developed a self-powered and self-functional sock (S2-sock) to realize diversified functions including energy harvesting and sensing various physiological signals, i.e., gait, contact force, sweat level, etc., by hybrid integrating poly(3,4-ethylenedioxythiophene) polystyrenesulfonate (PEDOT:PSS)-coated fabric triboelectric nanogenerator (TENG) and lead zirconate titanate (PZT) piezoelectric chips. An output power of 1.71 mW is collected from a PEDOT:PSS-coated sock with mild jumping at 2 Hz and load resistance of 59.7 MΩ. The study shows that cotton socks worn daily can potentially be a power source for enabling self-sustained socks comprising wireless transmission modules and integrated circuits in the future. We also investigate the influences of environmental humidity, temperature, and weight variations and verify that our S2-sock can successfully achieve walking pattern recognition and motion tracking for smart home applications. On the basis of the sensor fusion concept, the outputs from TENG and PZT sensors under exercise activities are effectively merged together for quick detection of the sweat level. By leveraging the hybrid S2-sock, we can achieve more functionality in the applications of foot-based energy harvesting and monitoring the diversified physiological signals for healthcare, smart homes, etc.
              Article 0 comments Cited 125 times – based on 0 reviews     Review now
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                Author and article information

                Contributors
                Naratip Vittayakorn
                Thitirat Charoonsuk
                Journal
                Journal ID (nlm-ta): iScience
                Journal ID (iso-abbrev): iScience
                Title: iScience
                Publisher: Elsevier
                ISSN (Electronic): 2589-0042
                Publication date PMC-release: 26 November 2024
                Publication date Collection: 20 December 2024
                Publication date (Electronic): 26 November 2024
                Volume: 27
                Issue: 12
                Electronic Location Identifier: 111480
                Affiliations
                [1 ]Department of Materials Science, Faculty of Science, Srinakharinwirot University, Sukhumvit 23, Watthana, Bangkok 10110, Thailand
                [2 ]Department of Physics, Faculty of Science, King Mongkut’s University of Technology Thonburi, Bangkok 10140, Thailand
                [3 ]Department of Electrical Engineering, Siksha O Anusandhan University, Bhubaneswar 751030, India
                [4 ]Department of Robotics and Mechatronics Engineering, Daegu Gyeongbuk Institute of Science and Technology, Daegu 42988, South Korea
                [5 ]Department of Chemistry, School of Science, King Mongkut’s Institute of Technology Ladkrabang, Bangkok 10520, Thailand
                [6 ]Advanced Materials Research Unit, School of Science, King Mongkut’s Institute of Technology Ladkrabang, Bangkok 10520, Thailand
                Author notes
                [∗ ]Corresponding author naratip.vi@ 123456kmitl.ac.th
                [∗∗ ]Corresponding author thitiratc@ 123456g.swu.ac.th
                [7]

                Lead contact

                Article
                Publisher Item ID: S2589-0042(24)02707-X Publisher ID: 111480
                DOI: 10.1016/j.isci.2024.111480
                PMC ID: 11667019
                PubMed ID: 39720518
                SO-VID: b091b0cd-6122-4cbc-a4aa-6a67de0bb648
                Copyright © © 2024 The Author(s)
                License:

                This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

                History
                Date received : 24 May 2024
                Date revision received : 23 October 2024
                Date accepted : 22 November 2024
                Categories
                Subject: Article

                Keywords: health sciences,natural sciences,materials science
                Data availability:
                Keywords: health sciences, natural sciences, materials science

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