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| 題名: | Motor Ingredients Derived from a Wearable Sensor-Based Virtual Reality System for Frozen Shoulder Rehabilitation |
| 作者: | 葉士青;Yang, Geng;Chen, Shih-Yin;Chan, Rai-Chi;Yeh, Shih-Ching;Lee, Si-Huei;Zheng, Li-Rong |
| 貢獻者: | 資訊電機學院資訊工程學系 |
| 關鍵詞: | Analysis;Arm - physiopathology;Bursitis - physiopathology;Bursitis - rehabilitation;Cats;Correlation analysis;Data mining;Data processing;Female;Hospitals;Humans;Internet of Things;Male;Medical research;Medicine, Experimental;Middle Aged;Motor Activity;Muscle Strength;Physical therapy;Range of Motion, Articular;Rehabilitation;Rehabilitation - instrumentation;Sensors;Shoulder;Studies;Task Performance and Analysis;User-Computer Interface;Virtual reality |
| 日期: | 2016-01-01 |
| 上傳時間: | 2026-04-23 13:54:45 (UTC+8) |
| 出版者: | Hindawi Publishing Corporation;Cairo, Egypt: Hindawi Publishing Corporation |
| 摘要: | 摘要： Objective. This study aims to extract motor ingredients through data mining from wearable sensors in a virtual reality goal-directed shoulder rehabilitation (GDSR) system and to examine their effects toward clinical assessment. Design. A single-group before/after comparison. Setting. Outpatient research hospital. Subjects. 16 patients with frozen shoulder. Interventions. The rehabilitation treatment involved GDSR exercises, hot pack, and interferential therapy. All patients first received hot pack and interferential therapy on the shoulder joints before engaging in the exercises. The GDSR exercise sessions were 40 minutes twice a week for 4 weeks. Main Measures. Clinical assessments included Constant and Murley score, range of motion of the shoulder, and muscle strength of upper arm as main measures. Motor indices from sensor data and task performance were measured as secondary measures. Results. The pre- and posttest results for task performance, motor indices, and the clinical assessments indicated significant improvement for the majority of the assessed items. Correlation analysis between the task performance and clinical assessments revealed significant correlations among a number of items. Stepwise regression analysis showed that task performance effectively predicted the results of several clinical assessment items. Conclusions. The motor ingredients derived from the wearable sensor and task performance are applicable and adequate to examine and predict clinical improvement after GDSR training.
其他題名： Biomed Res Int
出版者： Cairo, Egypt: Hindawi Publishing Corporation
出版日期： 2016-01-01
出處： BioMed research international, 2016-01, Vol.2016 (2016), p.1-10
資源來源： Publicly Available Content Database
版權： Copyright © 2016 Si-Huei Lee et al.
版權： COPYRIGHT 2016 John Wiley & Sons, Inc.
版權： Copyright © 2016 Si-Huei Lee et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
版權： Copyright © 2016 Si-Huei Lee et al. 2016
識別號： ISSN: 2314-6133
識別號： ISSN: 2314-6141
識別號： EISSN: 2314-6141
識別號： DOI: 10.1155/2016/7075464
識別號： PMID: 27642600 |
| 顯示於類別: | [資訊工程學系] 期刊論文
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