By Topic

A generalised framework for analysing human hand motions based on multisensor information

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Zhaojie Ju ; Sch. of Creative Technol., Univ. of Portsmouth, Portsmouth, UK ; Honghai Liu

In this paper, an integrated framework with multiple sensory information for analysing human hand motions is proposed, and it consists of components of system integration, signal preprocessing, correlation study of sensory information and human motion recognition based on manipulation intention. Three types of sensors are employed in the framework to simultaneously capture the finger angle trajectory, the hand contact force and the forearm electromyography (EMG) signal. The signal preprocessing module is to facilitate the rapid acquisition of human hand tasks by automatically synchronising and segmenting the manipulation primitives. Correlations of the sensory information are studied by using Empirical Copula and demonstrate there exist significant relationships between muscle signals and finger trajectories and between muscle signals and contact forces. In addition, motion recognition based on the EMG intention is investigated by using both Gaussian Mixture Models (GMMs) and Support Vector Machine (SVM) and discussion of the comparative results is presented.

Published in:

Fuzzy Systems (FUZZ-IEEE), 2012 IEEE International Conference on

Date of Conference:

10-15 June 2012