<p>This paper presents a smartphone application that supports Shotokan Karate training by analysing posture and providing real-time feedback. The app evaluates three fundamental stances (Zenkutsu Dachi, Kokutsu Dachi, and Kiba Dachi) using Google ML Kit Pose Detection to extract body landmarks and compute joint-angle and alignment features, including proxy indicators of weight shift. The app also includes conditioning exercises (squats and push-ups) and a reflex-oriented interaction task. Results from a single-participant pilot are reported as feasibility evidence only and should not be generalised. A larger validation study with at least 30 practitioners across three skill levels (beginner, intermediate, advanced) is required, together with power analysis and reliability assessment, before broader conclusions can be drawn.</p>

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A pilot study of a mobile application for postural analysis and training support in Shotokan Karate

  • Carlos Manuel Silva,
  • António Oseas Pataca,
  • Frederico Branco,
  • Paulo Jorge Coelho,
  • Ivan Miguel Pires

摘要

This paper presents a smartphone application that supports Shotokan Karate training by analysing posture and providing real-time feedback. The app evaluates three fundamental stances (Zenkutsu Dachi, Kokutsu Dachi, and Kiba Dachi) using Google ML Kit Pose Detection to extract body landmarks and compute joint-angle and alignment features, including proxy indicators of weight shift. The app also includes conditioning exercises (squats and push-ups) and a reflex-oriented interaction task. Results from a single-participant pilot are reported as feasibility evidence only and should not be generalised. A larger validation study with at least 30 practitioners across three skill levels (beginner, intermediate, advanced) is required, together with power analysis and reliability assessment, before broader conclusions can be drawn.