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

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 Modifi...

Full description

Saved in:
Bibliographic Details
Published in2017 IEEE 3rd International Symposium in Robotics and Manufacturing Automation (ROMA) pp. 1 - 6
Main Authors Yee, Jingye, Cheng Yee Low, Hanapiah, Fazah Akhtar, Zakaria, Noor Ayuni Che, Mohammad, Ubaidullah, bin Abd Rahman, Ramhuzaini
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.09.2017
Subjects
Cloud computing
cloud technology
Manipulators
Medical diagnostic imaging
Medical services
patient simulator
rehabilitation
smart health
spasticity
Training
Online AccessGet full text

Cover

More Information
Summary: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.
DOI:10.1109/ROMA.2017.8231732