Real-time hand gesture identification for human computer interaction based on ica of surface electromyogram

Ganesh R. Naik, Hans Weghorn, Dinesh K. Kumar, Vijay P. Singh, Marimuthu Palaniswami

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

6 Citations (Scopus)

Abstract

Today, there exists a variety of interfaces that allow human users to interact with computerized systems. Many of these input and output devices force the user to adapt to the requirements of the machine construction, like e.g. numeric keyboards on tiny devices often have to be used also for letter input. In contradiction to such technically-driven concepts, the aim of the investigation presented here is to provide a reliable input mode, which enables machine control for rehabilitation and human-computer interaction applications in a quite natural way. The processing in this new input system consists of three major stages: At first, hand gestures are sensed from non-invasive surface electromyograms, and in the second step the activities of the involved individual muscles are decomposed by semi-blind independent component analysis (ICA). In the last step, the particular hand action is identified with an artificial neural network (ANN). In this model-based approach, the order and magnitude ambiguity of ICA have been overcome by using a priori knowledge of the hand muscle anatomy and a fixed un-mixing matrix for the signal decomposition. In 360 single-shot experiments, this system was able to classify all tested hand gestures fully correct. These experimental results demonstrate that the proposed approach yields a high recognition rate with various gestures, and the system was verified being insensitive against electrode positions. A comparative evaluation of applying the same recognition mechanism in identifying facial movement yields new findings about the properties of the derived ICA mixing matrix, which can be exploited as indicator for the reliability and efficiency of the pattern classification mechanism in a distinct application.

Original languageEnglish
Title of host publicationMCCSIS 2007
Subtitle of host publicationProceedings of the IADIS International Conference on Interfaces and Human Computer Interaction
EditorsAntonio Palma dos Reis, Katherine Blashki, Yingcai Xiao
PublisherIADIS Press
Pages83-90
Number of pages8
ISBN (Electronic)9789728924393
Publication statusPublished - 2007
Externally publishedYes
Event2007 IADIS International Conference on Interfaces and Human Computer Interaction, IHCI 2007, part of the 1st IADIS Multi Conference on Computer Science and Information Systems, MCCSIS 2007 - Lisbon, Portugal
Duration: 3 Jul 20078 Jul 2007

Conference

Conference2007 IADIS International Conference on Interfaces and Human Computer Interaction, IHCI 2007, part of the 1st IADIS Multi Conference on Computer Science and Information Systems, MCCSIS 2007
CountryPortugal
CityLisbon
Period3/07/078/07/07

Keywords

  • Bio-signal Analysis
  • Hand Gesture Sensing
  • Human Computer Interface (HCI)
  • Independent Component Analysis (ICA)
  • Surface Electromyography (SEMG)

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