Objective. Transcutaneous spinal cord stimulation (tSCS) has been gaining momentum as a non-invasive rehabilitation approach to restore movement to paralyzed muscles after spinal cord injury (SCI). However, its low selectivity limits the types of movements that can be enabled and, thus, its potential applications in rehabilitation. Approach. In this cross-over study design, we investigated whether muscle recruitment selectivity of individual muscles could be enhanced by multielectrode configurations of tSCS in 16 neurologically intact individuals. We hypothesized that due to the segmental innervation of lower limb muscles, we could identify muscle-specific optimal stimulation locations that would enable improved recruitment selectivity over conventional tSCS. We elicited leg muscle responses by delivering biphasic pulses of electrical stimulation to the lumbosacral enlargement using conventional and multielectrode tSCS. Results. Analysis of recruitment curve responses confirmed that multielectrode configurations could improve the rostrocaudal and lateral selectivity of tSCS. To investigate whether motor responses elicited by spatially selective tSCS were mediated by posterior root-muscle reflexes, each stimulation event was a paired pulse with a conditioning-test interval of 33.3 ms. Muscle responses to the second stimulation pulse were significantly suppressed, a characteristic of post-activation depression suggesting that spatially selective tSCS recruits proprioceptive fibers that reflexively activate muscle-specific motor neurons in the spinal cord. Moreover, the combination of leg muscle recruitment probability and segmental innervation maps revealed a stereotypical spinal activation map in congruence with each electrode’s position. Significance. Improvements in muscle recruitment selectivity could be essential for the effective translation into stimulation protocols that selectively enhance single-joint movements in neurorehabilitation.

Objective Transcutaneous spinal cord stimulation (tSCS) has been gaining momentum as a non-invasive rehabilitation approach to restore movement to paralyzed muscles after spinal cord injury (SCI). However, its low selectivity limits the types of movements that can be enabled and, thus, its potential applications in rehabilitation. Approach In this cross-over study design, we investigated whether muscle recruitment selectivity of individual muscles could be enhanced by multielectrode configurations of tSCS in 16 neurologically intact individuals. We hypothesized that due to the segmental innervation of lower limb muscles, we could identify muscle-specific optimal stimulation locations that would enable improved recruitment selectivity over conventional tSCS. We elicited leg muscle responses by delivering biphasic pulses of electrical stimulation to the lumbosacral enlargement using conventional and multielectrode tSCS. Results Analysis of recruitment curve responses confirmed that multielectrode configurations could improve the rostrocaudal and lateral selectivity of tSCS. To investigate whether motor responses elicited by spatially selective tSCS were mediated by posterior root-muscle reflexes, each stimulation event was a paired pulse with a conditioning-test interval of 33.3 ms. Muscle responses to the second stimulation pulse were significantly suppressed, a characteristic of post-activation depression suggesting that spatially selective tSCS recruits proprioceptive fibers that reflexively activate muscle-specific motor neurons in the spinal cord. Moreover, the combination of leg muscle recruitment probability and segmental innervation maps revealed a stereotypical spinal activation map in congruence with each electrode’s position. Significance Improvements in muscle recruitment selectivity could be essential for the effective translation into stimulation protocols that selectively enhance single-joint movements in neurorehabilitation.

Background: Indirect calorimetry is the gold standard field-testing technique for measuring energy expenditure and exercise intensity based on the volume of oxygen consumed (VO₂, mL O₂/min). Although heart rate is often used as a proxy for VO₂, heart rate-based estimates of VO₂ may be inaccurate after stroke due to changes in the heart rate–VO₂ relationship. Our objective was to evaluate in people post stroke the accuracy of using heart rate to estimate relative walking VO₂ (wVO₂) and classify exercise intensity. Moreover, we sought to determine if estimation accuracy could be improved by including clinical variables related to patients’ function and health in the estimation. Methods: Sixteen individuals post stroke completed treadmill walking exercises with concurrent indirect calorimetry and heart rate monitoring. Using 70% of the data, forward selection regression with repeated k-fold cross-validation was used to build wVO₂ estimation equations that use heart rate alone and together with clinical variables available at the point-of-care (i.e., BMI, age, sex, and comfortable walking speed). The remaining 30% of the data were used to evaluate accuracy by comparing (1) the estimated and actual wVO₂ measurements and (2) the exercise intensity classifications based on metabolic equivalents (METs) calculated using the estimated and actual wVO₂ measurements. Results: Heart rate-based wVO₂ estimates were inaccurate (MAE = 3.11 mL O₂/kg/min) and unreliable (ICC = 0.68). Incorporating BMI, age, and sex in the estimation resulted in improvements in accuracy (MAE Δ: −36.01%, MAE = 1.99 mL O₂/kg/min) and reliability (ICC Δ: +20, ICC = 0.88). Improved exercise intensity classifications were also observed, with higher accuracy (Δ: +29.85%, from 0.67 to 0.87), kappa (Δ: +108.33%, from 0.36 to 0.75), sensitivity (Δ: +30.43%, from 0.46 to 0.60), and specificity (Δ: +17.95%, from 0.78 to 0.92). Conclusions: In people post stroke, heart rate-based wVO₂ estimations are inaccurate but can be substantially improved by incorporating clinical variables readily available at the point of care.

Post-stroke gait dysfunction is biomechanically heterogeneous, yet biomechanically informed classifications of functional walking remain underdeveloped. In particular, there is a lack of clinically accessible methods for classifying gait deficits that account for propulsion impairments—a historically laboratory-dependent gait parameter requiring measurement with force plate systems. This study examined whether propulsion impairment can be classified by combining a global measure of walking function (i.e., the 10 m walk test speed) with specific measures of dynamic walking ability derived from the Functional Gait Assessment (FGA). Forty participants >6 months post-stroke completed biomechanical evaluations quantifying propulsion during walking and clinical assessments including the FGA. Multivariable stepwise regression identified the FGA items most strongly associated with paretic propulsion. Models augmented with these FGA items explained 15% greater variance in the paretic propulsion peak and 7% greater variance in paretic propulsion impulse compared with models using Comfortable Walking Speed (CWS) alone. Incorporating FGA items also yielded the highest overall accuracy (72.5% vs. 60% with CWS alone) and best per-class performance in propulsion severity classification. These findings establish the co-assessment of walking speed and targeted FGA items as a clinically feasible approach to biomechanically informed classification of post-stroke gait dysfunction.

Background: Gait propulsion (anterior ground reaction force) is commonly impaired after stroke. Force plates and wearable sensors can quantify propulsion but are not routinely available in clinical settings. Walking speed alone does not adequately capture the heterogeneity of propulsion deficits. Objective: To determine whether standardized clinical measures can estimate post- stroke propulsion metrics and classify propulsion impairment. Methods: Forty individuals post-stroke participated: 33 for model development and cross-validation (11 with repeated observations for longitudinal validation) and 7 for independent-cohort validation. Clinical measures included the 6-Minute Walk Test (6MWT), comfortable walking speed (CWS), Functional Gait Assessment (FGA), Fugl- Meyer Assessment of the Lower Extremity (FMA-LE), Short Physical Performance Battery (SPPB), Timed Up and Go test (TUG), and stroke chronicity. Regression models were developed to estimate three propulsion metrics: paretic propulsion peak and impulse, and interlimb propulsion symmetry. Model performance was evaluated using R ² and RMSE. Propulsion impairment was classified from symmetry estimates using a prespecified cutoff of 31.5%, with classification accuracy reported. Results: Models using the 6MWT, SPPB, TUG, and chronicity estimated paretic propulsion peak (R ² = 0.77, RMSE = 3.00 %body weight) and impulse (R ² = 0.81, RMSE = 0.65 %body weight·%stance phase). FMA-LE, SPPB, TUG, and chronicity estimated propulsion symmetry (R ² = 0.75, RMSE = 8.56%) and classified propulsion impairment with 84.8% accuracy. Classification accuracy was 91.7% in longitudinal validation and 85.7% in independent-cohort validation. Conclusions: A multidomain clinical assessment framework may support practical and accurate estimation and classification of post-stroke propulsion impairment in clinical settings where specialized instrumentation is unavailable.