The article focuses on a method of quantifying movement of patients with Parkinson's disease (PD) using wearable motion capture (MoCap) system and bilateral cyclograms. The method uses cyclogram characteristics such as the slope, second moment of area and the area of the cyclogram to compare movements of left and right side of body. For symmetric movement, cyclogram should lie on a symmetry line passing through the origin inclined at an angle 45º. To study the body movement, measurement was performed using accelerometers (Xsens Technologies B.V.). Four accelerometers were placed on subject's arms and legs to measure accelerations in the anterior-posterior, medial-lateral and inferior-superior directions. Subjects (patients and healthy subjects) accomplished an extended Timed Up & Go Test (TUG). The data from the accelerometers were preprocessed, and then the bilateral cyclograms of two synchronized accelerations were created and evaluated. Using the cyclograms we confirmed the hypothesis that patients with PD have asymmetrical movements of the limbs. Omitting medication 24 hours before the measurement in patients with early stage PD had little effect on the synkinesias of gait. Findings suggest the possibility of the designed application of wearable MoCap system and bilateral cyclograms for use in drug therapy by evaluating postural stability via measuring accelerations. Thus, method using accelerometers and bilateral cyclograms is newly proposed for patients with PD.
The aim of this paper is to describe methods proposed for motion capture subsystem of smart orthosis for quantitative evaluation of movement activity of upper limbs during a rehabilitation process carried out at a clinic or at home. To quantify the description of motion we used methods of evaluation of the relationship between measured variables and nonlinear methods. To test the functionality of the methods, we compared the movement of the dominant and nondominant limbs, assuming cyclical and acyclic movement, to obtain the expected values for a healthy population. In accordance with the goal, a group of cyclic and non-cyclic movements common to the home environment were proposed. The movements were divided according to the activities performed during sitting, standing and walking. It was: pen writing, typing on the keyboard / using the mouse, eating with a spoon and eating a croissant combing, lifting weights, reading a book, etc. Twenty healthy subjects participated in the study. Four gyro-accelerometers (Xsens Technologies B.V.) attached to the forearms and upper arms of both upper limbs were used to record the upper limb movements. The results show that the calculated values of dominant and non-dominant limb parameters differ significantly in most movements. The motion capture subsystem which uses the proposed methods can be used to evaluate the physical activity for quantification of the evaluation of the rehabilitation process, and thus, it finds use in practice.
Using information about the values of the total center of pressure (CoP) and total vertical ground reaction force (GRF) during gait, quantitative parameters based on CoP trajectory length and trajectory length of 3-D plot of vertical GRF vs. CoP can be calculated and used to compare pathological prosthetic gait and normal gait. Seven patients with right transtibial amputation using passive transtibial prostheses, and ten healthy subjects participated in the study. After calculating the parameters of each patient and healthy subject, the two-sample t-test was used to assess the significance of the differences between the results of the two groups. Also, the observed parameters were compared with each other. For this purpose, Pearson correlation coefficients between the parameters were calculated to study the relationships between the parameters. The results show that in all cases, the parameters described in patients are significantly different than in healthy subjects. New parameters provide new information on way of walking and show the differences in gait step as a whole. The described techniques and calculated and statistically evaluated values of proposed parameters can be used for gait analysis in clinical practice.
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