Biofeedback is a promising tool to complement conventional physi-cal therapy by fostering active participation of neurologically impaired patients during treatment. This work aims at a user-centered design and usability as-sessment for different age groups of a novel wearable augmented reality (AR) application composed of a multimodal sensor network and corresponding con-trol strategies for personalized biofeedback during gait training. The proposed solution includes wearable AR glasses that deliver visual cues controlled in re-al-time according to mediolateral center of mass position, sagittal ankle angle, or tibialis anterior muscle activity from inertial and EMG sensors. Control strat-egies include positive and negative reinforcement conditions and are based on the user’s performance by comparing real-time sensor data with an automatical user-personalized threshold. The proposed solution allows ambulatory practice on daily scenarios, physiotherapists' involvement through a laptop screen, and contributes to further benchmark biofeedback regarding the type of sensor. Alt-hough old healthy adults with low academic degrees have a preference for guidance from an expert person, excellent usability scores (SUS scores: 81.25-96.87) were achieved with young and middle-aged healthy adults and one neu-rologically impaired patient.This work was funded by the Fundação para a Ciência e Tecnologia under the scholarship reference 2020.05709.BD, under the Stimulus of Scientific Employment with the grant 2020.03393.CEECIND, with the FAIR project under grant 2022.05844.PTDC, under the national support to R&D units grant through the reference project UIDB/04436/2020 and UIDP/04436/2020
