Stroke and Parkinson’s disease often result in significant gait impairments reducing mobility, independence and overall quality of life. While biofeedback has proven effective in restoring healthy gait, it is typically designed without considering the patient perspective. Therefore, this study aimed to implement a co-design process for personalized real-time biofeedback, to determine its impact on patient motivation and gait outcomes. Five participants (4 stroke, 1 stroke and Parkinson’s disease) participated in multiple personalized real-time biofeedback-based gait training sessions using a Computer Assisted Rehabilitation Environment, actively shaping the features (e.g. visual biofeedback presentation, background settings, sound preferences, etc.). Continuous adjustments to the biofeedback and its difficulty effectively maintained patient motivation and engagement. Combined with eliciting changes in gait outcomes, personalized real-time biofeedback represents a promising approach to improve current gait training approaches, with potential implications in the rehabilitation process.