Demo

Improve the generalisation ability of models for animal pose estimation.

Learning activity representation and estimating heart rate using PPG and IMU data from the smartwatch. Activity encoding was trained with self-supervised contrastive learning. Our heart rate estimation model archives mean absolute error 5 bpm and mean absolute percentage error only 4%. Because of the small number of params (5M MAC operations only) tiny AI chip with implemented model consumes only 0.1 mW.

Developed model for inertial navigation and activity classification on smartphones based on IMU data. Created new algorithm for gyroscope bias correction based on smart quaternions correction. Archived 8.9 RMSE and 6.0 MAPE in trajectory estimation task.

Built model for sweat loss estimation during workout via Samsung Galaxy Watch 4 (implemented feature) for Samsung Research based on BMI, age, weight and accelerometer and gyroscope data.