KUMITRON is an AI and sensor-based sports training system designed to enhance athletes’ performance and personalize their training. Its innovative approach addresses the lack of precision in traditional methods and aims to establish itself as a market leader.


  1. Personalized training: Tailors workouts to individual athletes’ needs and goals.
  2. Enhanced performance: Improves technique, motor skills, artistic prowess, and physical fitness.
  3. Real-time feedback: Provides instant, precise instructions and adjustments to optimize training.
  4. Injury prevention: Helps reduce the risk of injuries by monitoring athletes’ movements and fatigue.
  5. Data-driven insights: Collects and analyzes data for better decision-making and strategy development.
  6. Time efficiency: Maximizes training results by focusing on areas that need improvement.
  7. Motivation and engagement: Keeps athletes motivated and engaged through customized and dynamic training sessions.
  8. Applicability across sports: Adaptable to various sports for a broader range of athletes and coaches.


Unlock your athletic potential with KUMITRON - Get started today and experience the future of personalized sports training!



Selected references:

J. Echeverria & O. C. Santos (2021), “Toward modeling psychomotor performance in Karate combats using computer vision pose estimation”, in Sensors (Basel), vol. 21, núm. 24, p. 8378.

J. Echeverria & O. C. Santos (2021), “KUMITRON: Learning in Pairs Karate related skills with Artificial Intelligence support”, in 22nd International Conference on Artificial Intelligence in Education (AIED 2021).

J. Echeverria & O. C. Santos (2021), “KUMITRON: A Multimodal Psychomotor Intelligent Learning System to Provide Personalized Support when Training Karate Combats”, in 1st International Workshop on Multimodal Artificial Intelligence in Education, MAIED 2021, pp. 71–82.

J. Echeverria & O. C. Santos (2021), “KUMITRON: Artificial intelligence system to monitor karate fights that synchronize aerial images with physiological and inertial signals”, en 26th International Conference on Intelligent User Interfaces.

J. Echeverria & O. C. Santos (2021), “Punch Anticipation in a Karate Combat with Computer Vision”, en Adjunct Proceedings of the 29th ACM Conference on User Modeling, Adaptation and Personalization.