Standardization of Neurotechnology for Brain-Machine Interfacing: State of the Art and Recommendations

Abstract

Research and development of brain-machine interfacing (BMI) systems and related neurotechnologies are at a crucial stage in their history. Progress in sensing technologies, advanced materials, robotics and artificial intelligence provides possibilities that until recently were considered science fiction. Direct neural interfacing with external or virtual devices can usher a new era where merging biological and artificial intelligence will have significant impact in multiple domains. First and foremost, BMIs are becoming powerful tools to improve our understanding of the brain and nervous system. In turn, this can lead to better therapeutic and assistive approaches to tackle healthcare challenges, as well as new modalities for human-machine interaction that may have transformative effects in many consumer-oriented applications. Not surprisingly, these technologies have generated remarkable interest and investment from both public and private organizations, including several publicly funded national and regional brain initiatives, as well as the worldwide creation of a large number of neurotechnology enterprises. Some projections expect the neurotechnology market to reach a valuation of USD 19 billion by the end of 2026 [1]. Despite their promise, BMI may be on the cusp of the hype curve, facing increasing pressure to demonstrate concrete value to users. In addition to the numerous technical challenges inherent to developing safe, efficacious, and reliable solutions, researchers and developers face the complex human-centered challenges of discerning which data and use cases provide the most value to which users and organizations. The development and commercialization of BMI systems require researchers, clinicians, manufacturers, and regulatory bodies to ensure that these devices comply with well-defined safety and effectiveness criteria. BMI systems typically require integration of multiple modules comprising measurement and analysis of neural activity, and provision of feedback to the user through various means, such as visual displays, virtual reality systems, haptic interfaces, and exoskeleton.