AI-Powered Closed-Loop Multielectrode Transcutaneous Spinal Cord Stimulation: Real-Time Adjustments for Enhanced Motor Recovery in Spinal Cord Injury (AIM RECOVER)

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Spinal Cord Injury (SCI) is a debilitating condition affecting approximately 20.6 million individuals worldwide, with an annual incidence of 0.9 million. In Singapore, the prevalence of SCI increased from 5 to 6 per 100,000 in 1990 to 13 to 15 per 100,000 in 2019. SCI often results in profound and long-term neurological impairments, particularly in motor function, leading to significant limitations in activities of daily living (ADLs) and ambulation. The costs associated with SCI acute treatment, rehabilitation, and long-term care are substantial. While conventional rehabilitation strategies remain essential, their effectiveness in restoring lost motor function is limited, leaving many individuals with permanent disability. Spinal cord stimulation (SCS) has emerged as a promising neuromodulation technique to improve neurological recovery following SCI. SCS delivers electrical impulses to activate afferent fibers, enhancing interneuronal connections, motor neuron excitability, and communication between spinal networks SCS can be broadly classified into epidural SCS (eSCS) and transcutaneous SCS (tSCS). Owning to its non-invasive nature and therapeutic potential, tSCS has gained significant attention, with numerous studies demonstrating its effectiveness in improving motor function following SCI. Most current tSCS protocols for lower limb motor control involve placing one or two active electrodes over the thoracolumbar spine (T10 - L2), with fixed stimulation sites and parameters throughout each session. This approach is grounded in the hypothesis that tSCS enhances overall excitability of the neural network by increasing sensory input. However, the lack of muscle-specific stimulation may lead to unwanted co-contraction of antagonistic muscles, hindering functional movement and reducing overall gait efficiency. Emerging evidence indicates that spinal cord excitability responds dynamically to variations in stimulation sites and parameters. Spatially selective eSCS with real-time processing has been shown to rapidly restore voluntary motor control even in individuals with chronic, motor-complete SCI. In animal studies, integrated approaches combining epidural spinal cord stimulation with peripheral muscle stimulation designed to mimic sensory feedback and feedforward muscle contraction loops demonstrated synergistic effects, providing a framework for the development of neuromodulation systems to enhance motor recovery following SC. In human studies, another study team has reported that multielectrode tSCS with continuous stimulation to engage central pattern generator (CPG) networks in combination with spatiotemporal alternating stimulation targeting dorsal roots projecting to the leg flexor and extensor motor pools, can induce alternating locomotor activity. Remarkably, this approach enabled immediate recovery of locomotor function in individuals with severe lower limb motor deficits even in clinically complete SCI. To date, the relative efficacy of combing continuous stimulation with spatiotemporal modulation, compared with continuous stimulation alone, has not yet been systematically evaluated in humans. This study aims to address these gaps by developing and evaluating an AI-powered closed-loop multielectrode tSCS system that integrates continuous midline stimulation with real-time, feedback-driven spatiotemporal modulation. The system leverages wearable kinematic sensors and surface electromyography (EMG) to dynamically adjust stimulation timing and intensity based on ongoing gait and muscle activation patterns. By aligning stimulation delivery with physiological motor demands, the proposed approach seeks to enhance muscle selectivity, optimize lower limb motor recruitment, and improve gait performance in individuals with incomplete SCI. If successful, this study will provide critical evidence supporting adaptive, AI-driven neuromodulation strategies and establish a foundation for next-generation tSCS systems that more effectively engage spinal sensorimotor circuits to promote functional recovery after SCI.