Equimetrics -- Applying HAR principles to equestrian activities

TL;DR

The paper introduces Equimetrics, a sensor-based system applying human activity recognition principles to analyze and improve equestrian performance through comprehensive data collection of rider and horse movements.

Contribution

It presents a novel, cost-effective data capture system that integrates sensors to classify activities and detect subtle movement changes in equestrian settings.

Findings

Accurately classifies walking, trotting, cantering, jumping

Detects subtle rider posture and horse movement changes

Offers an accessible alternative to traditional motion capture

Abstract

This paper presents the Equimetrics data capture system. The primary objective is to apply HAR principles to enhance the understanding and optimization of equestrian performance. By integrating data from strategically placed sensors on the rider's body and the horse's limbs, the system provides a comprehensive view of their interactions. Preliminary data collection has demonstrated the system's ability to accurately classify various equestrian activities, such as walking, trotting, cantering, and jumping, while also detecting subtle changes in rider posture and horse movement. The system leverages open-source hardware and software to offer a cost-effective alternative to traditional motion capture technologies, making it accessible for researchers and trainers. The Equimetrics system represents a significant advancement in equestrian performance analysis, providing objective, data-driven insights that can be used to enhance training and competition outcomes.