Estimation of UPDRS Finger Tapping Score by using Artificial Neural Network for Quantitative Diagnosis of Parkinson´s disease

Author

Fukawa, K. ; Okuno, R. ; Yokoe, M. ; Sakoda, S. ; Akazawa, K.

Author_Institution

Osaka Univ., Osaka

fYear

2007

fDate

8-11 Nov. 2007

Firstpage

259

Lastpage

260

Abstract

The purpose of this study was to estimate UPDRS finger tapping score with Parkinson´s disease patients by using an artificial neural network. The measurement system was composed of a pair of 3-axis accelerometers, a pair of touch sensors, an analog to digital converter and a personal computer. Firstly, the accelerations during the finger tapping were measured with 44 normal subjects and 17 Parkinson´s diseases subjects by using this system. Secondly, the four features were extracted from the obtained accelerations. Finally, the UPDRS finger tapping score was estimated by using a three-layer artificial neural network model.

Keywords

accelerometers; biomedical measurement; diseases; estimation theory; feature extraction; medical computing; neural nets; neurophysiology; patient diagnosis; 3-axis accelerometer; analog-to-digital converter; artificial neural network; feature extraction; finger tapping score estimation; measurement system; patient diagnosis; personal computer; touch sensor; unified Parkinson disease rating scale; Acceleration; Accelerometers; Artificial neural networks; Biomedical measurements; Feature extraction; Fingers; Parkinson´s disease; Tactile sensors; Testing; Thumb; Artificial Neural Network; Parkinson´s disease; UPDRS; acceleration; finger tapping;

fLanguage

English

Publisher

ieee

Conference_Titel

Information Technology Applications in Biomedicine, 2007. ITAB 2007. 6th International Special Topic Conference on

Conference_Location

Tokyo

Print_ISBN

978-1-4244-1868-8

Electronic_ISBN

978-1-4244-1868-8

Type

conf

DOI

10.1109/ITAB.2007.4407396

Filename

4407396