Development of image-projective desktop arm trainer, IDAT

Yang Liu, Yi Jiang, Takafumi Matsumaru

Research output: Chapter in Book/Report/Conference proceedingConference contribution

8 Citations (Scopus)

Abstract

Aim to improve upper limb rehabilitation effect, we design and develop an Image-projective Desktop Arm Trainer (IDAT). Compared with conventional therapy, IDAT provides a more effective and interesting training method. IDAT's goal is to maintain and improve patients' upper limb function by training their eye-hand coordination. We select step-on interface (SOI) as the input system which makes trainees can operate IDAT with hand directly. Trainees can make a customized training setting. It can provide motivation and accomplishment to trainees and maintain their enthusiasm and interest. So IDAT provides a much different human robot interaction with pervious upper limb rehabilitation robots that equip a joystick or controller to operate remotely. We propose this idea in 2007 and have applied SOI on some mobile robots. Now we apply it on IDAT to make a new way to upper limb rehabilitation.

Original languageEnglish
Title of host publication2012 IEEE/SICE International Symposium on System Integration, SII 2012
Pages355-360
Number of pages6
DOIs
Publication statusPublished - 2012 Dec 1
Event2012 IEEE/SICE International Symposium on System Integration, SII 2012 - Fukuoka, Japan
Duration: 2012 Dec 162012 Dec 18

Publication series

Name2012 IEEE/SICE International Symposium on System Integration, SII 2012

Conference

Conference2012 IEEE/SICE International Symposium on System Integration, SII 2012
CountryJapan
CityFukuoka
Period12/12/1612/12/18

ASJC Scopus subject areas

  • Information Systems

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    Liu, Y., Jiang, Y., & Matsumaru, T. (2012). Development of image-projective desktop arm trainer, IDAT. In 2012 IEEE/SICE International Symposium on System Integration, SII 2012 (pp. 355-360). [6426964] (2012 IEEE/SICE International Symposium on System Integration, SII 2012). https://doi.org/10.1109/SII.2012.6426964