부산대학교 도서관

A hallmark of cerebellar disease is impaired accuracy of intended movement which is often summarized as ataxia or incoordination. The diagnosis and assessment of cerebellar ataxia (CA) is primarily based on the expert clinician’s visual and auditory observations of the performance of these tasks, and as such, a significant level of subjectivity is implied. In order to address the limitations of this subjectivity we designed a novel automated system, utilizing the Microsoft Kinect device, to capture the finger chase task (in the assessment of upper limb ataxia) which is a part of the assessment of cerebellar upper limb function. Capturing the movements of the marker attached on the subject’s finger when following the target point generated by the program that mimics the finger movement of the clinician, we were able to capture the disability and provide a novel objective measure of the CA affecting upper limb function. In our approach, we essentially quantified the difference between the intended and achieved trajectories using Dynamic Time Warping (DTW) technique. Further, signal delay times and directional changes of the velocity of the marker were considered in characterizing the disability associated with patient’s finger movements. Finally, Principal Component Analysis (PCA) was employed to combine all the relevant features, reduce feature dimension while enhancing the robustness. This analysis demonstrates a significant separation between normal subjects and CA patients, highlighting this approach as a potential diagnostic aid in the objective assessment of Cerebellar ataxia.