Key Technologies Study Of Tremor Detection And Analysis For Parkinson's Disease

Parkinson's disease(PD)is a common neurodegenerative disease which has a hidden onset and slow progress.It is more common in the elderly and the average age of its onset is about 60 years old.Patients with the disease will gradually lose the ability to take care of themselves,causing a great burden on their families.About 70% of patients with PD have a first symptom of tremor,which is one of the most common neurological symptoms.As the first manifestation of many diseases or syndromes,tremors are difficult to identify at the early clinical d iagnosis.In clinical practice,doctors mainly rely on subjective judgment to classify different kinds of tremors.Due to lack of objective evaluation criteria,a certain kind of tremor is easily misdiagnosed.Since accurate judgment and classification of tremor can provide valuable information for the diagnosis and treatment of tremor diseases,it is necessary to classify and evaluate tremor quantitatively.The classification and quantification of tremors mainly includes two aspects: detection and analysis.The tremor detection is to obtain its signal,while the tremor analysis is to analyze the characteristics of its signal in order to provide the relevant parameters for identifying the classification of the tremor.The method of acceleration inertial sensor has become a research hotspot in the tremor detection with the advantages of convenience,fastness,noninvasiveness,real-time monitoring and so on.The frequency domain in the tremor analysis often provides more signal characteristics.Therefore,based on the previous study,this paper chose the inertial acceleration sensor method to detect the tremor,and analyzed the power spectrum characteristics of the tremor acceleration signal to find the relevant characteristic parameters in order to distinguish the tremor from Parkinson's disease.For the purpose of assisting to identify the tremor from Parkinson's disease objectively for clinical doctors,the subject mainly focus ed on tremor detection method and tremor signal analysis method of Parkinson's disease and the main work was summarized in the following two aspects:On one hand,the tremor signal detection system has been designed and manufactured successfully,which included a tremor signal acquisition terminal and a tremor signal detection operating system.The tremor signal acquisition terminal was based on micro electro mechanical system(MEMS)and has the advantages of compactness and portability.The tremor signal detection operating system was based on VB.N ET open loop environment and had a simple operation interface.The whole system realized the real-time monitoring.On the other hand,with the help of the tremor signal detection system 30 cases were collected,among which 20 belonged to Pathological tremors and 10 physiological tremors.After all the tremor data were pretreated,the power spectrum analysis method was used in the frequency domain which could draw the conclusions: firstly,the amplitude of the tremor acceleration signal could be used as a parameter of the degree of tremor and the use of this parameter might be helpful to quantify patients' doses for doctors in courses of treatment;secondly,it was found that the power spectrum energy concentration frequency of Parkinson's disease tremor,Parkinson's syndrome tremor and idiopathic tremor overlapped,which was difficult to distinguish.The peak frequency of the quiescent power spectrum of Parkinson's disease had a characteristic of multiple relationship,which could be used to identify Parkinson's disease quiescent tremor and was expected to be used to assist in diagnoses of early PDs.