Editorial -Sensorimotor decoding: characterization and modeling for rehabilitation and assistive technologies Vol. II

Jean Faber^1*Vassiliy Tsytsarev²Miguel Pais-Vieira³Tetiana Aksenova⁴

• ¹Neuroscience Division, Department of Neurology and Neurosurgery, Universidade Federal de São Paulo, Escola Paulista de Medicina, São Paulo, Brazil
• ²School of Medicine, University of Maryland, Baltimore, Maryland, United States
• ³University of Aveiro, iBiMED – Institute of Biomedicine, Department of Medical Sciences, Portugal, Aveiro, Portugal
• ⁴Univ. Grenoble Alpes, CEA, LETI, Clinatec, Grenoble, Rhône-Alpes, France

The dynamic field of Brain-Computer Interface (BCI) continues to promote crucial insights and technological advancements with significant implications for neurorehabilitation and assistive technologies. The present research topic, Sensorimotor Decoding: Characterization and Modeling for Rehabilitation and Assistive Technologies Vol II aims to increase our current understanding of sensorimotor processing in healthy individuals and in pathologies. Furthermore, it seeks to translate this knowledge to rehabilitation protocols, BCI procedures, and neurophysiological mechanisms through different approaches applied to the characterization, identification, and classification of electrophysiological sensorimotor patterns. In the first volume [1], the set of studies demonstrated that bridging the gap between basic and clinical sensorimotor science requires balancing time-proven techniques and novel technological approaches. Namely, encoding, decoding, and action were studied in normal and altered conditions using natural and artificial stimuli. In this second volume, the novel set of studies includes original articles as well as reviews and a case report, diversifying the types of approaches to study sensorimotor activity. These studies cover a range of topics from hardware design and algorithm development to clinical application. Collectively, they reflect an evolution in the field of BCI. The results of the studies listed in this editorial emphasize the interdisciplinary nature of the BCI field for neurorehabilitation and assistive applications (Figure 1). It shows that the progress in BCI area relies on an integrated approach focusing on: (i) the optimization of recording and stimulation hardware -considering efficiency, biocompatibility, and sensor miniaturization; (ii) the development of novel signal processing techniques -considering more robust and adaptable algorithms for different contexts, as well as features that maximize neural code/decode information; (iii) the enhancement of neuroplasticity through BCI-guided therapeutic interventions -with personalized protocols featuring direct stimulation of neural pathways with hybrid technologies, and real-time feedback; and (iv) the strategic direction of future research -pointing towards new modalities of signal acquisition, bidirectional interfaces, and innovative applications. The integration of these guidelines is crucial for the development of more impactful and, at the same time, more accessible solutions in the BCI field. By consequence, the autonomy and quality of life of individuals with sensorimotor impairments will become increasingly effective.