An IoT Sensing Platform and Serious Game for Remote Martial Arts Training.
- Publisher:
- MDPI
- Publication Type:
- Journal Article
- Citation:
- Sensors (Basel), 2023, 23, (17), pp. 7565
- Issue Date:
- 2023-08-31
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Full metadata record
Field | Value | Language |
---|---|---|
dc.contributor.author |
Ishac, K https://orcid.org/0000-0001-6215-3297 |
|
dc.contributor.author | Bourahmoune, K | |
dc.contributor.author |
Carmichael, M https://orcid.org/0000-0001-8439-0074 |
|
dc.date.accessioned | 2023-11-06T04:30:56Z | |
dc.date.available | 2023-08-29 | |
dc.date.available | 2023-11-06T04:30:56Z | |
dc.date.issued | 2023-08-31 | |
dc.identifier.citation | Sensors (Basel), 2023, 23, (17), pp. 7565 | |
dc.identifier.issn | 1424-8220 | |
dc.identifier.issn | 1424-8220 | |
dc.identifier.uri | http://hdl.handle.net/10453/173037 | |
dc.description.abstract | We propose a system for self-supported martial arts training using an IoT sensing platform and Serious Game that can also be extended for general sports training. In martial arts, it is important that the practitioner is correctly performing each technique to accurately learn and prevent injury. A common stance in all martial arts, but especially in Shaolin Kung Fu, is the horse stance or Mabu. With the pandemic, many more people adopted remote training without the presence of a professional trainer to give advice. Our developed LifeMat system, which is a novel IoT pressure-sensitive training mat, uses pressure maps and pattern recognition to accurately classify key martial arts postures, provide feedback on form, and detect when the user performs the technique incorrectly. This is presented in the form of a Serious Game we have developed named Kung Future that focuses on the Mabu stance as a case study. We tested 14 participants with three different feedback conditions and demonstrated that, on average, participants had higher performance, duration, engagement, and motivation when game feedback was active. Furthermore, user responses from the surveys suggested positive feedback for real-world and long-term use and scalability. | |
dc.format | Electronic | |
dc.language | eng | |
dc.publisher | MDPI | |
dc.relation.ispartof | Sensors (Basel) | |
dc.relation.isbasedon | 10.3390/s23177565 | |
dc.rights | info:eu-repo/semantics/openAccess | |
dc.subject | 0301 Analytical Chemistry, 0502 Environmental Science and Management, 0602 Ecology, 0805 Distributed Computing, 0906 Electrical and Electronic Engineering | |
dc.subject.classification | Analytical Chemistry | |
dc.subject.classification | 3103 Ecology | |
dc.subject.classification | 4008 Electrical engineering | |
dc.subject.classification | 4009 Electronics, sensors and digital hardware | |
dc.subject.classification | 4104 Environmental management | |
dc.subject.classification | 4606 Distributed computing and systems software | |
dc.subject.mesh | Animals | |
dc.subject.mesh | Horses | |
dc.subject.mesh | Martial Arts | |
dc.subject.mesh | Learning | |
dc.subject.mesh | Motivation | |
dc.subject.mesh | Pandemics | |
dc.subject.mesh | Posture | |
dc.subject.mesh | Animals | |
dc.subject.mesh | Horses | |
dc.subject.mesh | Motivation | |
dc.subject.mesh | Learning | |
dc.subject.mesh | Posture | |
dc.subject.mesh | Martial Arts | |
dc.subject.mesh | Pandemics | |
dc.title | An IoT Sensing Platform and Serious Game for Remote Martial Arts Training. | |
dc.type | Journal Article | |
utslib.citation.volume | 23 | |
utslib.location.activity | Switzerland | |
utslib.for | 0301 Analytical Chemistry | |
utslib.for | 0502 Environmental Science and Management | |
utslib.for | 0602 Ecology | |
utslib.for | 0805 Distributed Computing | |
utslib.for | 0906 Electrical and Electronic Engineering | |
pubs.organisational-group | /University of Technology Sydney | |
pubs.organisational-group | /University of Technology Sydney/Faculty of Engineering and Information Technology | |
pubs.organisational-group | /University of Technology Sydney/Strength - RI - Robotics Institute | |
pubs.organisational-group | /University of Technology Sydney/Faculty of Engineering and Information Technology/School of Mechanical and Mechatronic Engineering | |
utslib.copyright.status | open_access | * |
dc.date.updated | 2023-11-06T04:30:51Z | |
pubs.issue | 17 | |
pubs.publication-status | Published online | |
pubs.volume | 23 | |
utslib.citation.issue | 17 |
Abstract:
We propose a system for self-supported martial arts training using an IoT sensing platform and Serious Game that can also be extended for general sports training. In martial arts, it is important that the practitioner is correctly performing each technique to accurately learn and prevent injury. A common stance in all martial arts, but especially in Shaolin Kung Fu, is the horse stance or Mabu. With the pandemic, many more people adopted remote training without the presence of a professional trainer to give advice. Our developed LifeMat system, which is a novel IoT pressure-sensitive training mat, uses pressure maps and pattern recognition to accurately classify key martial arts postures, provide feedback on form, and detect when the user performs the technique incorrectly. This is presented in the form of a Serious Game we have developed named Kung Future that focuses on the Mabu stance as a case study. We tested 14 participants with three different feedback conditions and demonstrated that, on average, participants had higher performance, duration, engagement, and motivation when game feedback was active. Furthermore, user responses from the surveys suggested positive feedback for real-world and long-term use and scalability.
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