Emotion, the AI neuro-athletic trainer for semi-pro long jumpers turning motion into performance and emotion into precision.
Understanding constraints and design packagings
Artificial intelligence is rapidly transforming the future of sports, providing advanced tools to analyze performance, optimize training, and prevent injuries.
The brief was to design an AI-powered product for the sports industry, harnessing these technologies to boost athletic performance in a smarter, more personalized way.
Emotive state in athletes
Studies show that athletes’ emotional states greatly impact performance, with imbalances often causing injuries and underperformance.
The product concept focuses on this dynamic, still little explored, to monitor and manage emotions using AI.
Target and sport analysis
This project centers on the long jump, a sport that combines power, precision, and rhythm, demanding intense focus during short, repeated efforts in training and competition.
The target group is athletes aged 14 to 17, at a crucial stage of specialization who typically lack access to professional mental coaching.
Emotion capturing and technologies analysis
Many existing solutions monitor parameters like facial expressions, voice, physiology, and brainwaves, but they often lack versatility for sports. After evaluating technologies, we chose EEG, which measures brain activity to infer emotional states. Neurofeedback uses EEG data to provide real-time feedback, helping users better understand and manage their emotions.
Experimenting with different solutions
The project resulted in EMotion, an AI-powered system that helps young athletes enhance performance by managing emotional states.
Designed for training and pre-competition, it prioritizes lightness, ergonomics, and precise data analysis.
Sketching phase and shape definition
Designed for physical activity, EMotion features a lightweight, ergonomic form with a flexible, semi-transparent silicone shell that both protects and reveals the LED, and a removable rigid core for easy cleaning. Adjustable hinges and a breathable nylon strap ensure comfort during use.
Experimenting with different solutions
The EEG headband monitors brainwave activity to detect the athlete’s emotional state, sending data via Bluetooth to an app where AI generates personalized feedback.
A complementary monitoring band enhances accuracy by tracking biometric and performance data, such as heart rate, oxygen saturation, body load, and movement—integrated and analyzed alongside EEG data by the AI system.
Sketching phase and shape definition
The app, used with a smartphone on a tripod at the take-off line, automatically records each jump and delivers detailed feedback. It provides a comprehensive report of technical, physiological, and emotional data, supported by an AI mental coach that offers personalized advice and comparisons across sessions or with other athletes to support continuous improvement.
Image of EMotion ecosystem
