Identifying engineering, clinical and patient´s metrics for evaluating and quantifying performance of brain-machine interface (BMI) systems

Brain-machine interface (BMI) devices have unparalleled potential to restore functional movement capabilities to stroke, paralyzed and amputee patients. Although BMI systems have achieved success in a handful of investigative studies, translation of closed-loop neuroprosthetic devices from the laboratory to the market is challenged by gaps in the scientific data regarding long-term device reliability and safety, uncertainty in the regulatory, market and reimbursement pathways, lack of metrics for evaluating and quantifying performance in BMI systems, as well as patient-acceptance challenges that impede their fast and effective translation to the end user. This review focuses on the identification of engineering, clinical and user´s BMI metrics for new and existing BMI applications.