A clinical roadmap for brain-neural machine interfaces: trainees' perspectives on the 2013 international workshop

Abstract

Brain-neural machine interfaces (BNMIs) are systems that allow a user to control an artificial device, such as a computer cursor or a robotic limb, through imagined movements that are measured as neural activity. They provide the potential to restore mobility for those with motor deficiencies caused by stroke, spinal cord injury, or limb amputations. Such systems would have been considered a topic of science fiction a few decades ago but are now being increasingly developed in both research and industry. Workers in this area are charged with fabricating BNMIs that are safe, effective, easy to use, and affordable for clinical populations. Because of the rapid growth of this new field, however, many issues with development, ethics, metrics, and use need to be addressed. To bring together some of the leading minds, researchers, and critics of the neural prosthetics field to discuss the current state of BNMIs, the 2013 International Workshop on Clinical Brain-Neural Machine Interface Systems was held 24-27 February 2013 in Houston, Texas [1]-[3]. Attendees included researchers from academic and government agencies; program managers from the U.S. Food and Drug Administration (FDA), the National Institutes of Health (NIH), the National Aeronautics and Space Administration (NASA), and the Defense Advanced Research Projects Agency (DARPA); as well as top industry representatives; end users of BNMI technology; medical centers and science media representatives; and selected graduate students and postdoctoral researchers (postdocs).

Human‐Centered Design of Wearable Neuroprostheses and Exoskeletons

“…Indeed, consensus at the NRI workshop on Clinical Brain–Neural Machine Interface Systems held at the Houston Methodist Research Institute in Spring 2013 1 showed that although neuroprostheses, neurally controlled exoskeletons, and other types of 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, as well as patient‐acceptance challenges that impede their fast and effective translation to the end user (Liew et al 2013).…”

Applications of Brain–Machine Interface Systems in Stroke Recovery and Rehabilitation

“…One of the first meetings to address these challenges and discuss potential solutions to accelerate the translation of clinical BMI systems to the end-user was held at The Methodist Hospital Research Institute in February 2013 (http://bmiconference.org/), which brought together about 100 leaders from government, academia, medical centers, industry, foundations, and the patients. A preliminary report [66] reported on key challenges facing the translation of neuroprosthetic technology, including gaps in the scientific data regarding long-term device reliability and safety, uncertainty in the regulatory, market and reimbursement pathways, as well as patient-acceptance challenges that impede fast and effective translation to the end-user. It is clear that a regulatory roadmap and associated guidelines will facilitate innovation and investment in BMI device development, and translation of this neurotechnology to patients in need.…”

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

“…The 2013 International Workshop on Clinical Brain--Neural Machine Interface (BMI) Systems was held on February 25–27, 2013 at the Houston Methodist Research Institute, Houston, Texas [1]–[3]. The purpose of the workshop was to identify and discuss challenges and potential solutions leading to the development and deployment of interface systems based on neural activity in clinical applications.…”

“…The purpose of the workshop was to identify and discuss challenges and potential solutions leading to the development and deployment of interface systems based on neural activity in clinical applications. A review of the workshop written by participating trainees can be found in [1]. …”

“…The exposition below summarizes the discussion by participants at the Houston's workshop [1]. Although efforts have been made to provide an impartial and comprehensive review of the spectrum of opinions voiced by the participants at the workshop, the author assumes responsibility for any errors or omissions in this short review.…”