Sensing and Characterization of the Wrist Using Dart Thrower’s Movement
| Autor: | Sina Babazadeh, Aruna Seneviratne, Pubudu N. Pathirana, Nhan D. Nguyen, Trieu H. Pham, Richard S. Page |
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| Rok vydání: | 2018 |
| Předmět: |
030222 orthopedics
Dynamic time warping business.industry Computer science 010401 analytical chemistry Wearable computer Gyroscope Kinematics Wrist 01 natural sciences Motion (physics) 0104 chemical sciences law.invention 03 medical and health sciences 0302 clinical medicine medicine.anatomical_structure Inertial measurement unit law Trajectory medicine Computer vision Artificial intelligence Electrical and Electronic Engineering business Instrumentation |
| Zdroj: | IEEE Sensors Journal. 18:4145-4153 |
| ISSN: | 2379-9153 1530-437X |
| Popis: | The dart-throwing movement is engaged to capture wrist movements involved in numerous daily activities. This paper focuses on robust implementation in a wearable platform-based inertial sensors enhance opportunities for exploring day-to-day changes of wrist joint when performing dart-throwing motion. The kinematic characterization of the underlying movement is described in terms of time-series quaternions measured from gyroscope data. The distance metrics between these representations are used to compare quantitatively wrist kinematic performance against clinical observations. A clinical trial was conducted engaging five normal subjects and 10 patients undergoing a series of post-surgical rehabilitation programs. The approach classifies effectively the patients from normal subjects and alleviates the need for range of motion measurements of the wrist joint implying the quaternion trajectory associated with classical dynamic time warping as a useful kinematic description for dart thrower’s movement in assessing and characterizing the wrist performance. Clustering and classification results confirm that this proposed method is well-correlated with clinical assessments based on high positive correlation coefficients. The primary objective of this paper is to enhance the uptake and promote the uses of wearable sensors in longer term monitoring scenarios particularly relevant to non-clinical environments. |
| Databáze: | OpenAIRE |
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