Biofeedback is a promising tool to complement conventional physical therapy by fostering active participation of neurologically impaired patients during treatment. This work aims at a user-centered design and usability assessment for different age groups of a novel wearable augmented reality application composed of a multimodal sensor network and corresponding control strategies for personalized biofeedback during gait training. The proposed solution includes wearable AR glasses that deliver visual cues controlled in real-time according to mediolateral center of mass position, sagittal ankle angle, or tibialis anterior muscle activity from inertial and EMG sensors. Control strategies include positive and negative reinforcement conditions and are based on the user’s performance by comparing real-time sensor data with an automatically 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. Although 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 neurologically impaired patient.


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    Title :

    Design and Usability Assessment of Multimodal Augmented Reality System for Gait Training


    Additional title:

    Lect. Notes in Networks, Syst.



    Conference:

    Iberian Robotics conference ; 2023 ; Coimbra, Portugal November 22, 2023 - November 24, 2023



    Publication date :

    2024-04-27


    Size :

    13 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




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