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Non-Contact Hand Movement Analysis for Optimal Configuration of Smart Sensors to Capture Parkinson's Disease Hand Tremor.
Khwaounjoo, Prashanna; Singh, Gurleen; Grenfell, Sophie; Özsoy, Burak; MacAskill, Michael R; Anderson, Tim J; Çakmak, Yusuf O.
Afiliación
  • Khwaounjoo P; Department of Anatomy, School of Biomedical Sciences, University of Otago, Dunedin 9016, New Zealand.
  • Singh G; Medical Technologies Centre of Research Excellence, Auckland 1142, New Zealand.
  • Grenfell S; Department of Anatomy, School of Biomedical Sciences, University of Otago, Dunedin 9016, New Zealand.
  • Özsoy B; New Zealand Brain Research Institute, Christchurch 8011, New Zealand.
  • MacAskill MR; Global Dynamic Systems (GDS) ARGE, Teknopark Istanbul, Istanbul 34906, Turkey.
  • Anderson TJ; New Zealand Brain Research Institute, Christchurch 8011, New Zealand.
  • Çakmak YO; Department of Medicine, University of Otago, Christchurch 8140, New Zealand.
Sensors (Basel) ; 22(12)2022 Jun 18.
Article en En | MEDLINE | ID: mdl-35746395
Parkinson's disease affects millions worldwide with a large rise in expected burden over the coming decades. More easily accessible tools and techniques to diagnose and monitor Parkinson's disease can improve the quality of life of patients. With the advent of new wearable technologies such as smart rings and watches, this is within reach. However, it is unclear what method for these new technologies may provide the best opportunity to capture the patient-specific severity. This study investigates which locations on the hand can be used to capture and monitor maximal movement/tremor severity. Using a Leap Motion device and custom-made software the volume, velocity, acceleration, and frequency of Parkinson's (n = 55, all right-handed, majority right-sided onset) patients' hand locations (25 joints inclusive of all fingers/thumb and the wrist) were captured simultaneously. Distal locations of the right hand, i.e., the ends of fingers and the wrist showed significant trends (p < 0.05) towards having the largest movement velocities and accelerations. The right hand, compared with the left hand, showed significantly greater volumes, velocities, and accelerations (p < 0.01). Supplementary analysis showed that the volumes, acceleration, and velocities had significant correlations (p < 0.001) with clinical MDS-UPDRS scores, indicating the potential suitability of using these metrics for monitoring disease progression. Maximal movements at the distal hand and wrist area indicate that these locations are best suited to capture hand tremor movements and monitor Parkinson's disease.
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Texto completo: 1 Base de datos: MEDLINE Asunto principal: Enfermedad de Parkinson / Temblor Tipo de estudio: Diagnostic_studies Idioma: En Revista: Sensors (Basel) Año: 2022 Tipo del documento: Article

Texto completo: 1 Base de datos: MEDLINE Asunto principal: Enfermedad de Parkinson / Temblor Tipo de estudio: Diagnostic_studies Idioma: En Revista: Sensors (Basel) Año: 2022 Tipo del documento: Article