Assistive Technology Research

KEY FINDING: Lateral trunk muscular strength significantly improved after intervention with VDE-BWSTT.

KEY FINDING: The key innovation of the proposed protocol is in the co-registration of data from three synchronised systems (high-density EEG, surface EMG and IMU) before, during and after robot-assisted gait-training.

KEY FINDING: Patients experienced improved PIDA scores or reduced completion times with the customized joysticks, indicating enhanced driving performance.

KEY FINDING: Seven out of eleven patients were able to walk 10 meters unassisted using the Atalante exoskeleton after 12 training sessions.

KEY FINDING: Wheelchair propulsion performance was very similar in both immersive and non-immersive VR environments, specifically in terms of start angle, end angle, stroke angle, and shoulder movement.

KEY FINDING: Exercise intensity, measured by metabolic equivalents (METs), remained at a moderate level throughout the 10-week exoskeleton-assisted walking training.

KEY FINDING: Users of tilt-in-space wheelchairs experienced twice the proportion of high-risk caster failures than the ultralightweight manual wheelchair users.

KEY FINDING: Muscle activity decreased up to 10 training sessions in a standing position and up to 15 sessions in sit-to-stand and stand-to-sit motions.

KEY FINDING: The proposed method achieved an overall accuracy of 96.86% in recognizing physical activities.

KEY FINDING: The machine learning models achieved high accuracy in predicting TAI item scores, with AUC values ranging from 0.79 to 0.94 and precisions over 0.87.