Ultrarobust Underwater Kicking Phase Estimation for Robotic Exosuit-Assisted Diving

Assisting divers with robotic exoskeletons would increase their working efficiency and reduce the risk of accidents. Nonetheless, the synchronization of assistance with underwater movements has not been investigated and remains a complex issue. Due to the agility and individuality of these movements in aquatic environments, conventional methods utilized on land may not work properly. In this article, we proposed an ultrarobust adaptive oscillator (AO) (URAO) method for predicting the kicking phase for the flutter kick and breaststroke kick, two main underwater motion patterns in diving activity. The URAO works without the need for data collection or training and can adapt to different users, motion patterns, and rapid changes in kicking frequency, offering greater precision than methods previously utilized for land-based exoskeletons. Eight participants were tested while performing fluctuating-frequency flutter and breaststroke kicks in indoor and outdoor swimming pools. The results showed that URAO outperformed both conventional AO and state-of-the-art estimators in predicting underwater kicking phases, reducingRMS_EWSprediction error by up to 49.5% for flutter kicks and up to 44.8% for breaststroke kicks.