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System-level design of a cloud-based training device for upper limb spasticity rehabilitation

Authors :
Fazah Akhtar Hanapiah
Noor Ayuni Che Zakaria
Cheng Yee Low
Ramhuzaini Abd. Rahman
Ubaidullah Mohammad
Jingye Yee
Source :
2017 IEEE 3rd International Symposium in Robotics and Manufacturing Automation (ROMA).
Publication Year :
2017
Publisher :
IEEE, 2017.

Abstract

This paper describes a system-level design for an upper limb spasticity part-task trainer driven by clinical data stored in a cloud database. The robotic part-task trainer has been developed for pre-clinical training of medical personnel on the evaluation of upper limb spasticity based on the Modified Ashworth Scale. The cloud-based system enables continuous updating of clinical data of upper limb spasticity by rehabilitation physicians. Multiple part-task trainers can be connected to the cloud database via the internet, thus enabling the remote coaching of trainees and instant feedback of professional therapists and clinicians to the trainees. It is expected that the functionality provided by the cloud technology will benefit the pedagogy of medical education in the future.

Details

Database :
OpenAIRE
Journal :
2017 IEEE 3rd International Symposium in Robotics and Manufacturing Automation (ROMA)
Accession number :
edsair.doi...........c5422200a15b420e223f34885b731de2
Full Text :
https://doi.org/10.1109/roma.2017.8231732