Dinesh K. Kumar, Sridhar Poosapadi Arjunan

Human-Computer Interface Technologies for the Motor Impaired (eBook, ePUB)

• Format: ePub

Produktbeschreibung

Human Computer Interface Technologies for the Motor Impaired examines both the technical and social aspects of human computer interface (HCI). Written by world-class academic experts committed to improving HCI technologies for people with disabilities, this all-inclusive book explores the latest research, and offers insight into the current limitat

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Produktdetails

• Verlag: Taylor & Francis
• Seitenzahl: 214
• Erscheinungstermin: 22. Oktober 2015
• Englisch
• ISBN-13: 9781498766807
• Artikelnr.: 44754025

Autorenporträt

Dinesh K. Kumar received a B.Tech from IIT Madras, and a Ph.D in biomedical engineering from IIT Delhi and AIIMS, Delhi. He is a professor and leader of biomedical engineering at RMIT University, Melbourne, Australia. Dr. Kumar has published more than 330 refereed papers in the field, and his interests include muscle control, affordable diagnostics, and human-computer interface. He is editor of multiple journals, chairs a range of conferences related to biomedical engineering, and enjoys walking in nature in his spare time.

Sridhar Poosapadi Arjunan received a B.Eng in electronics and communication from the University of Madras, India; a M.Eng in communication systems from Madurai Kamaraj University, India; and a Ph.D in biomedical signal processing from RMIT University, Australia. He is currently a postdoctoral research fellow with Biosignals Lab at RMIT University. Dr. Poosapadi Arjunan is a recipient of the RMIT SECE Research Scholarship, CASS Australian Early Career Researcher Grant, and the Australia-India ECR Fellowship. His major research interests include biomedical signal processing, rehabilitation study, fractal theory, and human-computer interface applications.

Inhaltsangabe

Introduction. Human
computer interface: Mechanical sensors. Brain
computer interface based on thought waves. Evoked potentials
based brain
computer interface. Myoelectric
based hand gesture recognition for human
computer interface applications. Video
based hand movement for human
computer interface. Human
computer interface based on electrooculography. Video
based eye tracking. Speech for controlling computers. Lip movement for human
computer interface.