Literature DB >> 17959469

Finger taps movement acceleration measurement system for quantitative diagnosis of Parkinson's disease.

Ryuhei Okuno1, Masaru Yokoe, Kenzo Akazawa, Kazuo Abe, Saburo Sakoda.   

Abstract

The purpose of this study was to develop a finger taps acceleration measurement system for the quantitative diagnosis of Parkinson's disease. The system was composed of two 3-axis piezoelectric element accelerometers, a pair of touch sensors made of thin stainless steel sheets, an analog-digital(AD) converter and a personal computer (PC). Fingerstalls,with these sensors, were attached to subject's index finger and thumb. The acceleration and output of the touch sensors were recorded using the PC during the finger taps movements. Intervals between the single finger taps movements were calculated from the measured output of the touch sensors. Velocities during the single finger taps movements were calculated by integrating the measured acceleration. The amplitudes were calculated by integrating the velocities. The standard deviation of the single finger taps intervals, average of maximum single finger taps velocities and average of maximum single finger taps amplitudes were calculated from them. They were used as features for the quantitative diagnosis of Parkinson's disease. The developed system was used to conduct finger taps tests employing 27 normal subjects and 16 Parkinson's diseases subjects. The subjects were asked to execute continuous finger taps movement for 60 s. It was shown that the acceleration and output of the touch sensors could be measured and the features could be extracted.

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Year:  2006        PMID: 17959469     DOI: 10.1109/IEMBS.2006.260904

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  9 in total

1.  Quantifying Parkinson's disease finger-tapping severity by extracting and synthesizing finger motion properties.

Authors:  Yuko Sano; Akihiko Kandori; Keisuke Shima; Yuki Yamaguchi; Toshio Tsuji; Masafumi Noda; Fumiko Higashikawa; Masaru Yokoe; Saburo Sakoda
Journal:  Med Biol Eng Comput       Date:  2016-03-31       Impact factor: 2.602

2.  Music-supported motor training after stroke reveals no superiority of synchronization in group therapy.

Authors:  Floris T Van Vugt; Juliane Ritter; Jens D Rollnik; Eckart Altenmüller
Journal:  Front Hum Neurosci       Date:  2014-05-20       Impact factor: 3.169

3.  Feature visualization and classification for the discrimination between individuals with Parkinson's disease under levodopa and DBS treatments.

Authors:  Alessandro R P Machado; Hudson Capanema Zaidan; Ana Paula Souza Paixão; Guilherme Lopes Cavalheiro; Fábio Henrique Monteiro Oliveira; João Areis Ferreira Barbosa Júnior; Kheline Naves; Adriano Alves Pereira; Janser Moura Pereira; Nader Pouratian; Xiaoyi Zhuo; Andrew O'Keeffe; Justin Sharim; Yvette Bordelon; Laurice Yang; Marcus Fraga Vieira; Adriano O Andrade
Journal:  Biomed Eng Online       Date:  2016-12-30       Impact factor: 2.819

4.  Quantitative Assessment of the Arm/Hand Movements in Parkinson's Disease Using a Wireless Armband Device.

Authors:  Sofija Spasojević; Tihomir V Ilić; Ivan Stojković; Veljko Potkonjak; Aleksandar Rodić; José Santos-Victor
Journal:  Front Neurol       Date:  2017-08-11       Impact factor: 4.003

5.  Quantification of Finger-Tapping Angle Based on Wearable Sensors.

Authors:  Milica Djurić-Jovičić; Nenad S Jovičić; Agnes Roby-Brami; Mirjana B Popović; Vladimir S Kostić; Antonije R Djordjević
Journal:  Sensors (Basel)       Date:  2017-01-25       Impact factor: 3.576

6.  On the Use of t-Distributed Stochastic Neighbor Embedding for Data Visualization and Classification of Individuals with Parkinson's Disease.

Authors:  Fábio Henrique M Oliveira; Alessandro R P Machado; Adriano O Andrade
Journal:  Comput Math Methods Med       Date:  2018-11-04       Impact factor: 2.238

7.  Measurement and Evaluation of Finger Tapping Movements Using Log-linearized Gaussian Mixture Networks.

Authors:  Keisuke Shima; Toshio Tsuji; Akihiko Kandori; Masaru Yokoe; Saburo Sakoda
Journal:  Sensors (Basel)       Date:  2009-03-26       Impact factor: 3.576

8.  Knowledge representation of motor activity of patients with Parkinson's disease.

Authors:  Bożena Kostek; Adam Kupryjanow; Andrzej Czyżewski
Journal:  Nat Comput       Date:  2014-12-31       Impact factor: 1.690

9.  Touchscreen-based finger tapping: Repeatability and configuration effects on tapping performance.

Authors:  Soma Makai-Bölöni; Eva Thijssen; Emilie M J van Brummelen; Geert J Groeneveld; Robert J Doll
Journal:  PLoS One       Date:  2021-12-07       Impact factor: 3.240

  9 in total

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