NDLI: Classification of hand preshaping in persons with stroke using Linear Discriminant Analysis

Content Provider	IEEE Xplore Digital Library
Author	Puthenveettil, S. Fluet, G. Qinyin Qiu Adamovich, S.
Copyright Year	2012
Description	Author affiliation: Univ. of Med. & Dentistry of New Jersey, Newark, NJ, USA (Fluet, G.) \|\| New Jersey Inst. of Technol., Newark, NJ, USA (Puthenveettil, S.; Qinyin Qiu; Adamovich, S.)
Abstract	Objective: This study describes the analysis of hand preshaping using Linear Discriminant Analysis (LDA) to predict hand formation during reaching and grasping tasks of the hemiparetic hand, following a series of upper extremity motor intervention treatments. The purpose of this study is to use classification of hand posture as an additional tool for evaluating the effectiveness of therapies for upper extremity rehabilitation such as virtual reality (VR) therapy and conventional physical therapy. Classification error for discriminating between two objects during hand preshaping is obtained for the hemiparetic and unimpaired hands pre and post training. Methods: Eight subjects post stroke participated in a two-week training session consisting of upper extremity motor training. Four subjects trained with interactive VR computer games and four subjects trained with clinical physical therapy procedures of similar intensity. Subjects' finger joint angles were measured during a kinematic reach to grasp test using $CyberGlove^{®}$ and arm joint angles were measured using the trackSTAR™ system prior to training and after training. Results: The unimpaired hand of subjects preshape into the target object with greater accuracy than the hemiparetic hand as indicated by lower classification errors. Hemiparetic hand improved in preshaping accuracy and time to reach minimum error. Conclusion: Classification of hand preshaping may provide insight into improvements in motor performance elicited by robotically facilitated virtually simulated training sessions or conventional physical therapy.
Sponsorship	IEEE Eng. Medicine Biol. Soc.
Starting Page	4563
Ending Page	4566
File Size	820698
Page Count	4
File Format	PDF
ISBN	9781424441198
ISSN	1557170X
e-ISBN	9781457717871
DOI	10.1109/EMBC.2012.6346982
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-08-28
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Training Thumb Joints Shape Grasping Kinematics
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Classification of Hand Preshaping in Persons with Stroke using Linear Discriminant Analysis*

Tracking whole hand kinematics using extended Kalman filter

Linear and nonlinear subspace analysis of hand movements during grasping

Towards a complete description of grasping kinematics: A framework for quantifying human grasping and manipulation

A novel design method of anthropomorphic prosthetic hands for reproducing human hand grasping

Decoding of finger, hand and arm kinematics using switching linear dynamical systems with pre-motor cortical ensembles

Correlation of reaching and grasping kinematics and clinical measures of upper extremity function in persons with stroke related hemiplegia

Coordinated upper limb training assisted with an electromyography (EMG)-driven hand robot after stroke

Multi-constrained inverse kinematics for the human hand

Classification of hand preshaping in persons with stroke using Linear Discriminant Analysis

Similar Documents

Classification of Hand Preshaping in Persons with Stroke using Linear Discriminant Analysis*

Tracking whole hand kinematics using extended Kalman filter

Linear and nonlinear subspace analysis of hand movements during grasping

Towards a complete description of grasping kinematics: A framework for quantifying human grasping and manipulation

A novel design method of anthropomorphic prosthetic hands for reproducing human hand grasping

Decoding of finger, hand and arm kinematics using switching linear dynamical systems with pre-motor cortical ensembles

Correlation of reaching and grasping kinematics and clinical measures of upper extremity function in persons with stroke related hemiplegia

Coordinated upper limb training assisted with an electromyography (EMG)-driven hand robot after stroke

Multi-constrained inverse kinematics for the human hand

Classification of hand preshaping in persons with stroke using Linear Discriminant Analysis