Revolution in biomechanics
intelligent wearable suits for MoCap and neurophysiological monitoring
Keywords:
biometric suit, moCAP, electrotactile stimulation, TENS, FES, wearable devices, neural interface, VR, neurorehabilitation, digital phenotyping, AI, haptic feedback, skin-integrated electronics, closed-loop biofeedbackAbstract
This review presents a systematic analysis of the concept and architecture of next-generation intelligent wearable suits that integrate high-precision motion capture, multimodal neurophysiological monitoring, electrotactile and functional electrical stimulation (TENS/FES), and adaptive AI-based control. Drawing on publications from 2020–2026 in IEEE Transactions on Haptics, Nature Electronics, Nature Machine Intelligence, Nature Communications, Science Advances, Advanced Science, and arXiv preprints, the article examines the physical principles of electrotactile stimulation, architectural solutions for distributed electrode arrays, hardware–software pipelines for haptic rendering, and the application of attention mechanisms to the processing of multichannel sensory streams. Using the Biometric Suit platform and its international counterparts as case studies, the paper demonstrates that the field is shifting from isolated kinematic capture toward the paradigm of in situ digital phenotyping — a comprehensive description of the body's state in the context of behavioral and physiological data. The review also addresses clinical efficacy, market prospects (haptic suit market CAGR estimates ranging from 5.4% to 16%, with market size between USD 285 million and USD 7.87 billion in 2024–2025), and the principal technical limitations of the field: inter-individual variability of stimulation thresholds, electrode durability, user cognitive load, and the absence of standardized haptic content formats. The convergence of neurophysiology, materials science, and artificial intelligence is identified as the foundation for transforming the intelligent suit into a universal platform for managing human motor and cognitive performance.
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Copyright (c) 2026 Сергей Исмулин, Станислав Лаук-Дубицкий
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