Loading...
Development of a Method to Quantitative Assessment of Fatigue in Upper Limb Rehabilitation in Stroke Patients
Zare Mohammadjani, Alireza | 2017
785
Viewed
- Type of Document: M.Sc. Thesis
- Language: Farsi
- Document No: 50197 (08)
- University: Sharif University of Technology
- Department: Mechanical Engineering
- Advisor(s): Behzadipour, Saeed
- Abstract:
- Stroke is a common neurological disorder that can lead to a large number of complications such as mobility impairments. Rehabilitation has been known as the most effective method of treatment. In recent years, many studies have been conducted on investigating the effective factors in increasing the efficiency of the rehabilitation process. One of these parameters is muscle fatigue. The aim of this study is to devise a method for detection and quantification of fatigue level in stroke patients while performing an upper limb rehabilitation exercise in a virtual reality environment. This may be used by the therapist or the VR rehab application to optimally adjust the type and intensity of the exercise and provide an accurate.For quantitative assessment of fatigue, it is necessary to find the relation between the changes in motion kinematics and the maximum voluntary contraction (MVC) as the main fatigue indicator. For this purpose, three separate experiment were designed and implemented. In the first step, stroke patients were asked to do bicep curls using dumbbells in order to acquire the most common parameters for sEMG fatigue in time, frequency, and time-frequency domains. Contemplating the results indicated that PCA and NSM have a higher sensitivity with respect to muscle fatigue in comparison to other parameters. In the second stage, the “Reaching” task, one of the most common upper body rehabilitation exercises, was implemented in a virtual reality environment for one-minute periods until the patient reached the highest level of exhaustion. During this stage, the sEMG signal of the anterior deltoid and its MVC level was recorded and the relation between fatigue parameters in the first step and MVC changes was obtained. Lastly, the reaching task was performed continuously from the beginning of the activity until the complete exhaustion while the kinematic data of the upper limbs were recorded using a Kinect camera as well as the sEMG signal of the anterior deltoid. Next, using the PSW non-linear algorithm, the changes made in the dynamical trajectories of phase-space were quantitatively calculated and it was observed that these changes increase homogeneously with the increase in fatigue levels. Finally, by combining the results from steps two and three and using the EMG fatigue parameters obtained in these steps, the relation between kinematic fatigue and MVC changes was obtained.
The presented method in this research could be useful in the field of intelligent rehabilitation, occupational environment, and sport competitions, thanks to the development of markerless motion analysis tools such as Kinect camera and the simplicity of kinematic data recording compared to other fatigue measurement tools - Keywords:
- Kinematics Analysis ; Data Analysis ; Fatigue Analysis ; Electromyogram Signal ; Electromyography Data ; Virtual Reality (VR)Environment ; Stroke ; Rehabilitation Exercises ; Fatigue Quantitative Assessment
- محتواي کتاب
- view