Advanced Brain-Machine Interfaces (BMIs) for Neuromusculoskeletal Disorders

Neuromusculoskeletal disorders—encompassing conditions such as stroke, spinal cord injury, amyotrophic lateral sclerosis, cerebral palsy, and traumatic limb loss—represent a profound challenge to global health, often resulting in significant and persistent impairment of motor function and sensory feedback. While traditional neurorehabilitation and prosthetic solutions have provided substantial benefits, they frequently fall short of restoring natural, intuitive, and coordinated movement. The convergence of neuroscience, engineering, and clinical medicine has now brought us to a pivotal moment where advanced Brain-Machine Interfaces (BMIs) offer a transformative pathway to bridge this gap.Modern BMIs are evolving beyond foundational communication and control paradigms. The next generation of systems aims to establish closed-loop, bidirectional communication between the brain and the periphery. These advanced interfaces seek not only to decode motor intent with high fidelity but also to deliver precise somatosensory feedback by encoding information from robotic prostheses or neuromuscular stimulation devices. This bi-directional flow is critical for restoring the sense of embodiment, improving motor learning, and achieving fluid, adaptive control of complex neuromusculoskeletal systems. However, the journey from laboratory breakthroughs to robust, user-centric clinical applications is fraught with interdisciplinary challenges. These include the need for more stable and biocompatible neural interfaces, the development of computationally efficient and adaptive decoding algorithms, the integration of BMIs with novel actuation and stimulation technologies, and the imperative for rigorous, longitudinal clinical validation.This Research Topic, "Advanced Brain-Machine Interfaces (BMIs) for Neuromusculoskeletal Disorders," aims to capture the cutting edge of this rapidly advancing field. We invite original research, reviews, methodological papers, and perspective articles that address the multifaceted journey of BMI technology from bench to bedside. We seek contributions that push the boundaries of what is possible in restoring function and improving the quality of life for individuals with neuromusculoskeletal impairments.Topics of interest include, but are not limited to:- Neural Decoding & Control: Novel algorithms for intention decoding, adaptive shared control, and multi-limb coordination.- Bidirectional BMIs: Technologies and approaches for delivering closed-loop tactile, proprioceptive, and kinesthetic feedback.- Hybrid & Integrated Systems: BMI integration with functional electrical stimulation (FES), powered exoskeletons, and robotic prosthetics.- Neural Interface Technology: Advances in implantable (e.g., ECoG, Utah arrays, stereo-EEG) and non-invasive (e.g., high-density EEG, fNIRS) recording and stimulation hardware.- Neuroplasticity & Rehabilitation: The role of BMIs in promoting neuroplasticity and their use in therapeutic neurorehabilitation paradigms.- Translational & Clinical Studies: Results from pilot and pivotal clinical trials, long-term usability studies, and real-world performance evaluation.- Computational Challenges: Embedded system design, low-latency processing, and cloud-based frameworks for BMI data.- User-Centric Design: Studies on embodiment, user acceptance, ethical considerations, and human factors in BMI development.We welcome submissions from engineers, neuroscientists, clinicians, computer scientists, and rehabilitation specialists. By fostering a dialogue across these disciplines, this Special Issue will serve as a comprehensive repository of current knowledge and a catalyst for future innovation, ultimately accelerating the development of clinically viable BMI solutions. Topic editors: Christina Zong-Hao Ma, Mingming Zhang, Eduard Masvidal Codina Source: https://www.frontiersin.org/research-topics/79622/advanced-brain-machine-interfaces-bmis-for-neuromusculoskeletal-disorders