Identification of ankle sprain motion from common sporting activities by dorsal foot kinematics data

This study presented a method to identify ankle sprain motion from common sporting activities by dorsal foot kinematics data. Six male subjects performed 300 simulated supination sprain trials and 300 non-sprain trials in a laboratory. Eight motion sensors were attached to the right dorsal foot to collect three-dimensional linear acceleration and angular velocity kinematics data, which were used to train up a support vector machine (SVM) model for the identification purpose. Results suggested that the best identification method required only one motion sensor located at the medial calcaneus, and the method was verified on another group of six subjects performing 300 simulated supination sprain trials and 300 non-sprain trials. The accuracy of this method was 91.3%, and the method could help developing a mobile motion sensor system for ankle sprain detection

Identification of ankle sprain motion from normal activities by dorsal foot kinematics data.

Chan, Yue Yan.Thesis (M.Phil.)--Chinese University of Hong Kong, 2008.Includes bibliographical references (leaves 36-40).Abstracts in English and Chinese.Abstract --- p.iChinese abstract --- p.iiAcknowledgement --- p.iiiTable of Contents --- p.ivList of figures --- p.viList of tables --- p.viiChapter Chapter 1: --- Introduction --- p.1Chapter Chapter 2: --- Review of literature --- p.4Chapter 2.1 --- Chapter introduction --- p.4Chapter 2.2 --- Anatomy and kinematics of the ankle --- p.4Chapter 2.3 --- Epidemiology of ankle sprain --- p.6Chapter 2.4 --- Grading system for classification of ankle sprain --- p.7Chapter 2.5 --- Previous measures of protecting ankle from sprain injury --- p.7Chapter 2.6 --- Usage of motion sensors in human motion detection --- p.9Chapter Chapter 3: --- A mechanical supination sprain simulator for studying ankle supination sprain kinematics --- p.11Chapter 3.1 --- Chapter Introduction --- p.11Chapter 3.2 --- Methods --- p.12Chapter 3.3 --- Results --- p.17Chapter 3.4 --- Discussion --- p.17Chapter Chapter 4: --- Identification of simulated ankle supination sprain from other normal motions by gyrometers and accelerometers --- p.19Chapter 4.1 --- Chapter introduction --- p.19Chapter 4.2 --- Methods --- p.20Chapter 4.2.1 --- Data collection --- p.20Chapter 4.2.2 --- Support Vector Machine for classification of human motion --- p.22Chapter 4.2.3 --- Training the Support Vector Machine --- p.23Chapter 4.2.4 --- Support Vector Machine verification --- p.24Chapter 4.2.5 --- Choose the optimal position of motion sensor --- p.25Chapter 4.3 --- Results --- p.25Chapter 4.4 --- Discussion --- p.29Chapter Chapter 5: --- Summary and future development --- p.34References --- p.36List of publications --- p.41List of presentations at international and local conferences --- p.41Appendix I: --- p.42Related publication:"Chan, Y. Y., Fong, D. T. P., Yung, P. S. H., Fung, K. Y., & Chan, K. M (1998). A mechanical supination sprain simulator for studying ankle supination sprain kinematics. Journal of Biomechanics. 41(11), 2571-2574."Appendix II: --- p.46Ethical approval of the investigation of ankle torque and motion signal pattern in foot segment during simulate sprain and other motio