Research On Diagnosis And Hand Movement Compensation For Patients With Parkinson's Disease

Parkinson's disease, also known as paralysis agitagns, is one of the most common diseases caused by the neurological dysfunction in basal ganglia among the elderly. Since it was first reported in 1817, the number of patients with Parkinson's disease has increased all the years. Given today's strong concern of Parkinson's disease, April 11th is named the World Parkinson's Disease Day since 1997. Parkinson's disease afflicts patients later in life with tremor, slowness of movement, gait instability, and rigidity, and it brings huge burden to the patients and the relatives. However, the early symptoms of Parkinson's disease were easily confused with the bodily functions of normal aging; traditionally clinicians diagnose based on the patients'medical history and physical examination, and also draw conclusions based on survey from patients. This process is very time consuming, and disagreement among conditions of the same patient is common due to the subjective nature of the diagnosis. Therefore, automatic techniques have become necessary for prompt and accurate identification of epileptic activities. Similarly, the same problem also exists in the effectiveness evaluation of the treatment for patients with Parkinson's disease. Therefore, effective diagnostic and evaluation techniques have become necessary for patients with Parkinson's disease. Additionally, development of a technique for improving an accuracy of hand movement will be helpful for recovering a quality of patients'daily life.This research has made systematic analysis of diagnosis and hand movement compensation for patients with Parkinson's disease. At first, free spiral drawing experiment has been designed to extract the main features for patients with Parkinson's disease. Then a few characteristic parameters have been extracted to get the diagnosis results for clinicians through classification detection and numerical analysis methods. Besides, a new method based on polar coordinate system with varied origin has been proposed in order to quantitatively evaluate the performance for patients with Parkinson's disease and the effectiveness of the treatment. Then, a compensation model of hand movement for patients with Parkinson's disease has been constructed. The compensation model can describe the characteristics of hand motion accurately, and proposed compensation technique will be effective for assisting the movement of patients with Parkinson's disease. Finally, a new application software is desiged and developed for diagnosis and hand movement compensation for patients with Parkinson's disease.The originality and effectiveness of this research are as follows:●Real-time data processing has been introduced into diagnosis and quantitative evaluation work for patients with Parkinson's disease. Since the aging population grows and the number of patients with Parkinson's disease increases year by year in China, the effective method of hand movement compensation base on spiral drawing task has been proposed to improve the motor performance for the patients with Parkinson's disease. This research has important clinical significance and great social benefits.●Free spiral drawing experiment has been design in this research. Hand movement experiments in many previous studies had been designed with templates or drawing instructions and the patients with Parkinson's disease always depended on the guidance in those experiments; so they cannot reflect the motion characteristics of patients. In this research, free spiral drawing experiment has been proposed to acquire the features of the patients'spontaneous movement.●Feature extraction method has been applied to extract the characteristics of hand movement highly related to Parkinson's disease. Subsequently, pattern classification algorithm has been used for automatic detection of the patients with Parkinson's disease. The results prove that this classification method can detect the patients effectively.●A new evaluation method based on polar coordinate system with varied origin has been proposed in order to assess the performance in spiral drawing tasks for patients with Parkinson's disease. Using this method, the characteristics of hand movement disabilities can be easily extracted. The results show that the proposed polar coordinate system had good performance in quantitatively evaluating of spiral drawing and had clinical significance in measuring the effectiveness of operation or treatment for the patients with Parkinson's disease.●A new technique of hand movement compensation for patients with Parkinson's disease based on polar coordination system with varied origin is proposed. The compensation model is constructed by using the parameters obtained in spiral drawing tasks. The effectiveness of this method has also been verified in the simulation study. Therefore, this research can provide a strong theoretic foundation of realizing a portable and desirable system to assist the movement for patients with Parkinson's disease.●The application software is desiged and developed for diagnosis and hand movement compensation for patients with Parkinson's disease. The software provides varied functions, such as experimental data output, spiral trajectory redrawing, characteristic parameters extraction, hand movement modeling, system parameters identification and hand movement compensation. It has strong clinical application significances hand great help for clinicians in diagnosis and evaluation of motor function through the use of the application software.This research has a certain instructional significance to study on the feature extraction and diagnosis on motor function for the patients with Parkinson's disease. And partial results from this work also can be extended to clinical applications. The adaptability and accuracy of the researched methods need to be further verified due to the lack of more experimental data and the limitations of laboratory equipment. Finally, conclusions of the dissertation are deduced and the future work is discussed.