On Learning Weight Distribution of Tai Chi Chuan Using Pressure Sensing Insoles and MR-HMD

Kao, Peng-Yuan; Han, Ping-Hsuan; Jan, Yao-Fu; Yang, Zhiwei; Li, Chun-Hsien; Hung, Yi‐Ping

doi:10.1109/vr.2019.8797986

Cited by 5 publications

(4 citation statements)

References 10 publications

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“…Description and Study Display of educational content in relevant locations [56], [60], [86] Information [45], [54] [95] Presentation of ideal behavior [64], [66], [67], [84] [69], [78] Demonstration [61], [63], [88] [91] Expanding the flexibility of training content by adding information to physical objects [38], [39], [41], [46], [80] [68], [69], [70], [75] [92] Facilitation of the skill transfer through imitation of the actual [14], [42], [43], [44], [45] Task support by presenting relevant information [16], [36], [41], [47], [49], [50], [51], [53] Practice [86], [87] [83] Feedback on the performance, problems, and ways to improve [39] [59] [65] Real-time feedback for motion compensation [71], [72], [75], [76], [78], [82] [41] Real-time visualization of invisible current conditions Feedback [93] learning prin...…”

Section: Strategymentioning

confidence: 99%

Systematic Review of Augmented Reality Training Systems

Butaslac

Fujimoto

Sawabe

et al. 2023

IEEE Trans. Visual. Comput. Graphics

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Recent augmented reality (AR) advancements have enabled the development of effective training systems, especially in the medical, rehabilitation, and industrial fields. However, it is unclear from the literature what the intrinsic value of AR to training is and how it differs across multiple application fields. In this work, we gathered and reviewed the prototypes and applications geared towards training the intended user's knowledge, skills, and abilities. Specifically, from IEEE Xplore plus other digital libraries, we collected 64 research papers present in high-impact publications about augmented reality training systems (ARTS). All 64 papers were then categorized according to the training method used, and each paper's evaluations were identified by validity. The summary of the results shows trends in the training methods and evaluations that incorporate ARTS in each field. The narrative synthesis illustrates the different implementations of AR for each of the training methods. In addition, examples of the different evaluation types of the current ARTS are described for each of the aforementioned training methods. We also investigated the different training strategies used by the prevailing ARTS. The insights gleaned from this review can suggest standards for designing ARTS regarding training strategy, and recommendations are provided for the implementation and evaluation of future ARTS.

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Section: Strategymentioning

confidence: 99%

Systematic Review of Augmented Reality Training Systems

Butaslac

Fujimoto

Sawabe

et al. 2023

IEEE Trans. Visual. Comput. Graphics

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“…Any experienced martial arts practitioner will also emphasize the importance of the correct weight distribution for different stances and techniques. The research in [32] used a Mixed Reality headset and in-sole pressure sensors to teach the correct weight distribution when performing basic Tai-Chi Chuan techniques. However, the calibration of the weight distribution is heavily dependent on user performance, and the variability of the calibration methodology exposes it to significant human error.…”

Section: Martial Arts and Gamificationmentioning

confidence: 99%

An IoT Sensing Platform and Serious Game for Remote Martial Arts Training

Ishac,

Bourahmoune,

Carmichael

2023

Sensors

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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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“…As it requires highly accurate movements, it has been popularly used in research to help users practice it. Due to the complexity of the movements, most works employ virtual 3D teachers, either with a screen [5], head mounted displays [4,[9][10][11][12], or audio-visual-tactile devices [16]. The most similar work to ours is Stillness Moves [14], which uses the recorded weight from pressure sensing shoes and video data from the Kinect for the training.…”

Section: Background and Related Workmentioning

confidence: 99%

Pose Estimation for Facilitating Movement Learning from Online Videos

Tharatipyakul,

Choo,

Perrault

2020

Preprint

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On Learning Weight Distribution of Tai Chi Chuan Using Pressure Sensing Insoles and MR-HMD

Cited by 5 publications

References 10 publications

Systematic Review of Augmented Reality Training Systems

Systematic Review of Augmented Reality Training Systems

An IoT Sensing Platform and Serious Game for Remote Martial Arts Training

Pose Estimation for Facilitating Movement Learning from Online Videos

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