We studied the influence of levodopa (L-Dopa) on training effects in subjects with spinal cord injury (SCI). A low-dose of L-Dopa per day is known to enhance the effects of physical training after stroke. This is tested here in subjects suffering a SCI. Twelve subacute, incomplete SCI (iSCI) subjects (ASIA C and D) were randomized in a trial with a double-blind, crossover design to receive 6 weeks of L-Dopa (200 mg), followed by 6 weeks of placebo, or vice versa. Outcome measures were ASIA Motor-Score (AMS) reflecting motor recovery; walking ability, assessed by the Walking Index of Spinal Cord Injury (WISCI); and Activities of Daily Living (ADL), as monitored by the Spinal Cord Independence Measure (SCIM). Both placebo and L-Dopa, in combination with physiotherapy, produced a significant motor recovery after SCI. The combination of L-Dopa and physiotherapy had no greater effect on the outcome than placebo and physiotherapy. The possible reasons for the different effect of L-Dopa in stroke and iSCI subjects are discussed.

Locomotor recovery after incomplete spinal cord injury (iSCI) is influenced by spinal and supraspinal networks. Conventional clinical gait analysis fails to differentiate between these components. There is evidence that corticospinal control is enhanced during targeted walking, where each foot must be continuously placed on visual targets in randomized order. This study investigates the potential of targeted walking in the functional assessment of corticospinal integrity. Twenty-one controls and 16 individuals with chronic iSCI performed normal and targeted walking on a treadmill while electromyograms (EMGs) and kinematics were recorded. Precision (% of accurate foot placements) in targeted walking was significantly lower in individuals with iSCI (82.9 ± 14.7%, controls: 94.9 ± 4.0%). Although the overall kinematic pattern was comparable between walking conditions, controls showed significantly higher semitendinosus (ST) activity before heel-strike during targeted walking. This was accompanied by a shift of relative EMG intensity from 90–120 Hz to lower frequencies of 20–60 Hz, previously associated with corticospinal control of muscle activity. Targeted walking in individuals with iSCI evoked smaller EMG changes, suggesting that the switch to more corticospinal control is impaired. Accordingly, mildly impaired iSCI individuals revealed higher adaptations to the targeted walking task than more-impaired individuals. Recording of EMGs during targeted walking holds potential as a research tool to reveal further insights into the neuromuscular control of locomotion. It also complements findings of pre-clinical studies and is a promising novel surrogate marker of integrity of corticospinal control in individuals with iSCI and other neurological impairments. Future studies should investigate its potential for diagnosis or tracking recovery during rehabilitation.

Background: Spinal cord injury (SCI) causes long-term neurological deficits resulting in functional disabilities. While longitudinal recovery patterns of sensorimotor outcomes after SCI have been studied, few analyses have applied machine learning to systematically model the relationship between neurological impairments and functional independence at different post-injury phases. Methods: This study compared ordinal and nominal classification models predicting functional independence from sensorimotor status cross-sectionally. Inputs included motor and sensory scores from the International Standards for Neurological Classification of SCI, age, sex, and time since injury collected in the European Multicenter Study about SCI. Models were evaluated on a task from each domain of the Spinal Cord Independence Measure, namely grooming (self-care), bladder management (respiration and sphincter management), and indoor mobility (mobility). Analyses were stratified into early (≤ 40 days), intermediate (70–100 days), and late (> 182 days) post-injury phases. Models were ranked based on five evaluation metrics, and interpretability explored using Shapley Additive Explanations (SHAP). Results: Model accuracy improved over time (early phase: 46–71%, late phase: 50–85%), indicating that functional independence is more reliably determined from sensorimotor scores in later post-injury phases. Across all scenarios, random forest achieved the best overall performance (0.93 ± 0.03, averaged across different metrics). Ordinal models yielded fewer severe misclassifications compared to nominal models. Motor scores were stronger predictors than sensory scores, with lower limb function (L2–L4) strongly associated with mobility, voluntary anal contraction with bladder control, and upper limb function (C6, C8) with grooming ability, highlighting that models utilise known relationships. Conclusion: We show that both multiclass and ordinal models can accurately classify SCIM-based functional independence outcomes after SCI from neurological assessments at different time points post-injury. Ordinal approaches provide particular clinical value by minimizing severe misclassifications, a crucial advantage when distinguishing between functional independence classes that require fundamentally different care approaches. Interpretability analysis showed that the predictions are grounded in clinical knowledge. The developed models provide the basis for a modular prognostic framework, in which predicted ISNCSCI scores can be used to derive the most likely functional independence class, enabling a modular, computationally efficient and scalable approach to prediction in SCI care across a range of neurological and functional outcomes.

Spinal cord injuries (SCI) often result in impaired motor functions. To quantify these impairments, swimming patterns were analyzed in individuals with SCI. Water provides a unique rehabilitation environment where buoyancy supports weight-bearing activities and can reveal deficits that might otherwise go unnoticed. Data were collected of 30 individuals with chronic, motor-incomplete SCI and 20 healthy controls during breaststroke swimming on a kickboard. Using eight wearable inertial sensors attached to the lower limbs, we captured detailed kinematic data. Spatiotemporal parameters were then calculated and compared between the two groups to assess differences in swimming patterns. An analysis of the parameters revealed significant differences in velocity (p < 0.001, ε² = 0.476) and distance per stroke (p < 0.001, ε² = 0.516), indicating decreased swimming speeds in individuals with SCI compared to controls. Furthermore, individuals with SCI demonstrated a reduced range of motion (RoM) in the ankle (p = 0.003, ε² = 0.516) and knee joints (p = 0.041, ε² = 0.142). The limited RoM likely contributes to the shorter distance covered per stroke. These observations underscore the impact of SCI on functional capabilities. The developed algorithm holds promise for enhancing the assessment of motor deficits after neurological injuries.