Masterarbeit, 2012
58 Seiten, Note: 1
This thesis presents the development of a software suite designed to objectively and qualitatively assess arm movements in individuals with brain or physical injuries. The software aims to provide a standardized and reliable method for tracking and evaluating patient progress during neuro-rehabilitation.
Neuro-rehabilitation, arm movement assessment, computer vision, machine learning, objective assessment, qualitative assessment, software suite, Fugl-Meyer Assessment, patient progress, brain injury, physical injury.
The software aims to provide an objective and qualitative assessment of arm movements for patients with brain or physical injuries, replacing subjective traditional methods.
The Microsoft Kinect is used to track movements and calculate joint angles, allowing for standardized data collection without human bias.
The Fugl-Meyer Assessment is a widely used clinical tool for evaluating upper limb function in stroke patients. This thesis digitizes it to solve intertester reliability problems.
Testing was conducted using human skeletons to determine the optimal distance from the Kinect sensor to minimize deviation and maximize results.
The system utilizes computer vision and machine learning algorithms to analyze patient movements and track progress over time.
The objective measurements are stored in text files within specific patient test folders for clinical review.
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