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

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.

Improving Balance and Movement Control in Fencing Using IoT and Real-Time Sensorial Feedback

“…Traditionally positioned on the hip [ 9 ], alternative placements such as the wrist [ 10 , 11 ], thigh [ 12 ], knee [ 13 ], or even the back [ 14 ] are viable options contingent upon the specific demands of a given sport. Notably, across a spectrum of sports like tennis [ 15 ], football [ 16 ], basketball [ 17 ], handball [ 18 ], hockey [ 19 ], and martial arts [ 20 ], insufficient attention has been directed towards fencing in the existing research literature.…”