Analysis of grasping strategies using sensor based systems

Analysis of Grasping Strategies for Stroke Patients in Rehabilitative Technologies for Final Year Project Academic Year 17/18 explores the novel approach of using inexpensive electronic materials to develop a methodology for analysing the grasping strategies of individual subjects. The data for thes...

Full description

Saved in:
Bibliographic Details
Main Author: Luai, Jonathan Wei Jie
Other Authors: Domenico Campolo
Format: Final Year Project
Language:English
Published: 2018
Subjects:
Online Access:http://hdl.handle.net/10356/75287
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Nanyang Technological University
Language: English
id sg-ntu-dr.10356-75287
record_format dspace
spelling sg-ntu-dr.10356-752872023-03-04T19:11:42Z Analysis of grasping strategies using sensor based systems Luai, Jonathan Wei Jie Domenico Campolo School of Mechanical and Aerospace Engineering Asif Hussain DRNTU::Engineering Analysis of Grasping Strategies for Stroke Patients in Rehabilitative Technologies for Final Year Project Academic Year 17/18 explores the novel approach of using inexpensive electronic materials to develop a methodology for analysing the grasping strategies of individual subjects. The data for these grasping strategies can then be extrapolated and extended to hemiparetic stroke patients who are undergoing stroke rehabilitative treatment. In doing so, the aim is to build a reliable algorithm in predicting the grasp pattern of individuals when they participate in upper limb rehabilitation. The use of these data would also serve as a good source of reference in the future development of the project, which could potentially involve the system integration of a portable lightweight interactive board, as well as a gaming platform for stroke patients. This paper hence presents the experimental and design process on the various methods used for the grasping analysis and data collection. Bachelor of Engineering (Mechanical Engineering) 2018-05-30T07:33:58Z 2018-05-30T07:33:58Z 2018 Final Year Project (FYP) http://hdl.handle.net/10356/75287 en Nanyang Technological University 77 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Engineering
spellingShingle DRNTU::Engineering
Luai, Jonathan Wei Jie
Analysis of grasping strategies using sensor based systems
description Analysis of Grasping Strategies for Stroke Patients in Rehabilitative Technologies for Final Year Project Academic Year 17/18 explores the novel approach of using inexpensive electronic materials to develop a methodology for analysing the grasping strategies of individual subjects. The data for these grasping strategies can then be extrapolated and extended to hemiparetic stroke patients who are undergoing stroke rehabilitative treatment. In doing so, the aim is to build a reliable algorithm in predicting the grasp pattern of individuals when they participate in upper limb rehabilitation. The use of these data would also serve as a good source of reference in the future development of the project, which could potentially involve the system integration of a portable lightweight interactive board, as well as a gaming platform for stroke patients. This paper hence presents the experimental and design process on the various methods used for the grasping analysis and data collection.
author2 Domenico Campolo
author_facet Domenico Campolo
Luai, Jonathan Wei Jie
format Final Year Project
author Luai, Jonathan Wei Jie
author_sort Luai, Jonathan Wei Jie
title Analysis of grasping strategies using sensor based systems
title_short Analysis of grasping strategies using sensor based systems
title_full Analysis of grasping strategies using sensor based systems
title_fullStr Analysis of grasping strategies using sensor based systems
title_full_unstemmed Analysis of grasping strategies using sensor based systems
title_sort analysis of grasping strategies using sensor based systems
publishDate 2018
url http://hdl.handle.net/10356/75287
_version_ 1759854431162073088