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Telelife: An immersive media experience for rehabilitation
Umeå University, Faculty of Science and Technology, Department of Applied Physics and Electronics. (Digital Media Lab)
Umeå University, Faculty of Science and Technology, Department of Applied Physics and Electronics.
KTH Royal Institue of Technology, Department of Media Technology and Interaction Design, School of Computer Science and Communication.
2014 (English)In: Proceedings of the 2014 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA 2014), IEEE, 2014Conference paper, Published paper (Refereed)
Abstract [en]

In recent years, emergence of telerehabilitation systems for home-based therapy has altered healthcare systems. Telerehabilitation enables therapists to observe patients status via Internet, thus a patient does not have to visit rehabilitation facilities for every rehabilitation session. Despite the fact that telerehabilitation provides great opportunities, there are two major issues that affect effectiveness of telerehabilitation: relegation of the patient at home, and loss of direct supervision of the therapist. Since patients have no actual interaction with other persons during the rehabilitation period, they will become isolated and gradually lose their social skills. Moreover, without direct supervision of therapists, rehabilitation exercises can be performed with bad compensation strategies that lead to a poor quality recovery. To resolve these issues, we propose telelife, a new concept for future rehabilitation systems. The idea is to use media technology to create a totally new immersive media experience for rehabilitation. In telerehabilitation patients locally execute exercises, and therapists remotely monitor patients' status. In telelife patients, however, remotely perform exercises and therapists locally monitor. Thus, not only telelife enables rehabilitation at distance, but also improves the patients' social competences, and provides direct supervision of therapists. In this paper we introduce telelife to enhance telerehabilitation, and investigate technical challenges and possible methods to achieve telelife.

Place, publisher, year, edition, pages
IEEE, 2014.
National Category
Signal Processing
Identifiers
URN: urn:nbn:se:umu:diva-88093DOI: 10.1109/APSIPA.2014.7041675ISI: 000392861900163ISBN: 978-6-1636-1823-8 (electronic)OAI: oai:DiVA.org:umu-88093DiVA, id: diva2:713589
Conference
2014 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA 2014), 9-12 December 2014, Chiang Mai, Thailand
Available from: 2014-04-23 Created: 2014-04-23 Last updated: 2018-01-09Bibliographically approved
In thesis
1. Bring Your Body into Action: Body Gesture Detection, Tracking, and Analysis for Natural Interaction
Open this publication in new window or tab >>Bring Your Body into Action: Body Gesture Detection, Tracking, and Analysis for Natural Interaction
2014 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Due to the large influx of computers in our daily lives, human-computer interaction has become crucially important. For a long time, focusing on what users need has been critical for designing interaction methods. However, new perspective tends to extend this attitude to encompass how human desires, interests, and ambitions can be met and supported. This implies that the way we interact with computers should be revisited. Centralizing human values rather than user needs is of the utmost importance for providing new interaction techniques. These values drive our decisions and actions, and are essential to what makes us human. This motivated us to introduce new interaction methods that will support human values, particularly human well-being.

The aim of this thesis is to design new interaction methods that will empower human to have a healthy, intuitive, and pleasurable interaction with tomorrow’s digital world. In order to achieve this aim, this research is concerned with developing theories and techniques for exploring interaction methods beyond keyboard and mouse, utilizing human body. Therefore, this thesis addresses a very fundamental problem, human motion analysis.

Technical contributions of this thesis introduce computer vision-based, marker-less systems to estimate and analyze body motion. The main focus of this research work is on head and hand motion analysis due to the fact that they are the most frequently used body parts for interacting with computers. This thesis gives an insight into the technical challenges and provides new perspectives and robust techniques for solving the problem.

Place, publisher, year, edition, pages
Umeå: Umeå Universitet, 2014. p. 70
Series
Digital Media Lab, ISSN 1652-6295 ; 19
Keyword
Human Well-Being, Bodily Interaction, Natural Interaction, Human Motion Analysis, Active Motion Estimation, Direct Motion Estimation, Head Pose Estimation, Hand Pose Estimation.
National Category
Signal Processing
Research subject
Signal Processing; Computerized Image Analysis
Identifiers
urn:nbn:se:umu:diva-88508 (URN)978-91-7601-067-9 (ISBN)
Public defence
2014-06-04, Naturvetarhuset, N420, Umeå universitet, Umeå, 13:00 (English)
Opponent
Supervisors
Available from: 2014-05-14 Created: 2014-05-08 Last updated: 2014-05-13Bibliographically approved

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