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Vibrotactile rendering of head gestures for controlling electric wheelchair
Umeå University, Faculty of Science and Technology, Department of Applied Physics and Electronics. (Digital Media lab.)
Department of Information Engineering, Hiroshima University, Japan. (Intelligent Systems & Modelling Laboratory,)
Information Technology Research Institute (ITRI), National Institute of Advanced Industrial Science and Technology (AIST), Japan. (Ubiquitous Vision Group)
Umeå University, Faculty of Science and Technology, Department of Applied Physics and Electronics. (Digital Media Lab.)
2009 (English)In: Proceedings of IEEE international conference on systems, man and cybernetics, San Antonio, Texas, USA: IEEE , 2009, 413-417 p.Conference paper (Refereed)
Abstract [en]

We have developed a head gesture controlled electric wheelchair system to aid persons with severe disabilities. Real-time range information obtained from a stereo camera is used to locate and segment the face images of the user from the sensed video. We use an Isomap based nonlinear manifold learning map of facial textures for head pose estimation. Our system is a non-contact vision system, making it much more convenient to use. The user is only required to gesture his/her head to command the wheelchair. To overcome problems with a non responding system, it is necessary to notify the user of the exact system state while the system is in use. In this paper, we explore the use of vibrotactile rendering of head gestures as feedback. Three different feedback systems are developed and tested, audio stimuli, vibrotactile stimuli and audio plus vibrotactile stimuli. We have performed user tests to study the usability of these three display methods. The usability studies show that the method using both audio plus ibrotactile response outperforms the other methods (i.e. audio stimuli, vibrotactile stimuli response).

Place, publisher, year, edition, pages
San Antonio, Texas, USA: IEEE , 2009. 413-417 p.
Keyword [en]
extended Isomap, Multidimensional Scaling (MDS), head gesture recognition, vibrotactile rendering, wheelchair system, usability.
National Category
Signal Processing
Research subject
Computerized Image Analysis
URN: urn:nbn:se:umu:diva-32993DOI: 10.1109/ICSMC.2009.5346213ISBN: 978-1-4244-2793-2OAI: diva2:308424
IEEE international conference on systems, man and cybernetics, San Antonio, Texas, USA, 2009
Available from: 2010-04-06 Created: 2010-04-06 Last updated: 2010-04-20Bibliographically approved
In thesis
1. Expressing emotions through vibration for perception and control
Open this publication in new window or tab >>Expressing emotions through vibration for perception and control
2010 (English)Doctoral thesis, comprehensive summary (Other academic)
Alternative title[en]
Expressing emotions through vibration
Abstract [en]

This thesis addresses a challenging problem: “how to let the visually impaired ‘see’ others emotions”. We, human beings, are heavily dependent on facial expressions to express ourselves. A smile shows that the person you are talking to is pleased, amused, relieved etc. People use emotional information from facial expressions to switch between conversation topics and to determine attitudes of individuals. Missing emotional information from facial expressions and head gestures makes the visually impaired extremely difficult to interact with others in social events. To enhance the visually impaired’s social interactive ability, in this thesis we have been working on the scientific topic of ‘expressing human emotions through vibrotactile patterns’.

It is quite challenging to deliver human emotions through touch since our touch channel is very limited. We first investigated how to render emotions through a vibrator. We developed a real time “lipless” tracking system to extract dynamic emotions from the mouth and employed mobile phones as a platform for the visually impaired to perceive primary emotion types. Later on, we extended the system to render more general dynamic media signals: for example, render live football games through vibration in the mobile for improving mobile user communication and entertainment experience. To display more natural emotions (i.e. emotion type plus emotion intensity), we developed the technology to enable the visually impaired to directly interpret human emotions. This was achieved by use of machine vision techniques and vibrotactile display. The display is comprised of a ‘vibration actuators matrix’ mounted on the back of a chair and the actuators are sequentially activated to provide dynamic emotional information. The research focus has been on finding a global, analytical, and semantic representation for facial expressions to replace state of the art facial action coding systems (FACS) approach. We proposed to use the manifold of facial expressions to characterize dynamic emotions. The basic emotional expressions with increasing intensity become curves on the manifold extended from the center. The blends of emotions lie between those curves, which could be defined analytically by the positions of the main curves. The manifold is the “Braille Code” of emotions.

The developed methodology and technology has been extended for building assistive wheelchair systems to aid a specific group of disabled people, cerebral palsy or stroke patients (i.e. lacking fine motor control skills), who don’t have ability to access and control the wheelchair with conventional means, such as joystick or chin stick. The solution is to extract the manifold of the head or the tongue gestures for controlling the wheelchair. The manifold is rendered by a 2D vibration array to provide user of the wheelchair with action information from gestures and system status information, which is very important in enhancing usability of such an assistive system. Current research work not only provides a foundation stone for vibrotactile rendering system based on object localization but also a concrete step to a new dimension of human-machine interaction.

Place, publisher, year, edition, pages
Umeå: Umeå universitet, Institutionen för tillämpad fysik och elektronik, 2010. 159 p.
Digital Media Lab, ISSN 1652-6295 ; 12
Multimodal Signal Processing, Mobile Communication, Vibrotactile Rendering, Locally Linear Embedding, Object Detection, Human Facial Expression Analysis, Lip Tracking, Object Tracking, HCI, Expectation-Maximization Algorithm, Lipless Tracking, Image Analysis, Visually Impaired.
National Category
Signal Processing Computer Vision and Robotics (Autonomous Systems) Computer Science Telecommunications Information Science
Research subject
Computerized Image Analysis; Computing Science; Electronics; Systems Analysis
urn:nbn:se:umu:diva-32990 (URN)978-91-7264-978-1 (ISBN)
Public defence
2010-04-28, Naturvetarhuset, N300, Umeå universitet, Umeå, Sweden, 09:00 (English)
Taktil Video
Available from: 2010-04-07 Created: 2010-04-06 Last updated: 2010-04-20Bibliographically approved

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