QUANTIFICATION SYSTEM AND METHOD OF PULL TEST TO EXTRACT FEATURES OF MOTOR SYSPTOM OF PARKINSON'S DISEASE

摘要

The present invention relates to a pull test data quantification system and method for extracting motor function symptom characteristics of Parkinson's disease, wherein the pull test data quantification method for extracting motor function symptom characteristics of Parkinson's disease is set in a terminal. Measuring the user's acceleration every hour and generating accelerometer data in a CSV file format; Removing noise included in the generated accelerometer data in the terminal; In the terminal, correcting an axis that fixes the y-axis in the gravitational direction among the three axes to correct the user's posture and the inclination of the terminal with respect to the accelerometer data from which noise has been removed; Separating the accelerometer data whose axis is corrected into an accelerometer data vector value of a vertical component and an accelerometer data vector value of a horizontal component; In the terminal, a fast Fourier transform of the accelerometer data of the vertical component and the accelerometer data of the horizontal component is performed using the size of the accelerometer data vector value of the separated vertical component and the size of the accelerometer data vector value of the separated horizontal component, and the vertical Calculating the maximum and minimum values of the accelerometer data of the component and the accelerometer data of the vertical component; Calculating, at a terminal, an average value of the accelerometer data of the vertical component and the accelerometer data of the vertical component using the separated vertical component accelerometer data vector value and the separated horizontal component accelerometer data vector value; In the quantization device, the accelerometer data is the data of the user standing, the data of the pulling state, and the decision tree outputting the result of the fast Fourier transform performed, the calculated maximum, minimum, and average values to WEKA. Quantifying with data in a state in response to the pulled force, the window size of the accelerometer data is 16, the interval of the window is 1.