Christopher A. Johnson

Cerebral palsy (CP) is traditionally characterized as a disorder of motor impairment; however, growing evidence suggests it reflects broader dysregulation across multiple physiological systems. We present a longitudinal case study examining whether pairing transcutaneous spinal neuromodulation (TSN) with a proprioceptive-derived intervention (PDI) can engage systems-level functional adaptation in an adolescent with CP spastic diplegia, whose progress had plateaued after years of conventional therapy. Across two years of the intervention, structured clinical observations revealed progressive and reversible improvements spanning posture, locomotion, fine motor control, speech, vision, hearing, sleep, endurance, executive function, and psychosocial engagement. Motor coordination often changed rapidly with stimulation, autonomic functions evolved over intermediate timescales, and longer-lasting changes consistent with support of physiological capacity and recovery emerged more gradually. The task specificity, state dependence, and reversibility of these effects are consistent with activity-dependent processes guided by enhanced proprioceptive signaling during TSN + PDI. Importantly, these adaptations did not emerge uniformly across domains. These findings support a reconceptualization of CP not solely as an isolated motor disorder, but as a condition of maladaptive multisystem regulation that may be amenable to noninvasive, proprioceptively derived neuromodulatory rehabilitation strategies. While limited to a single case, this work highlights underappreciated neuroadaptive potential in CP and motivates future controlled studies targeting systems-level recovery.

The thumb plays a crucial role in hand function, yet its proprioceptive abilities remain poorly understood. Here we quantified dynamic thumb localization ability, as well as how this ability adapts to a perturbation, in unimpaired participants. For this, we developed a novel task in which a robot moved the thumb in a circle and participants pressed a button when they felt their thumb aligning with a target point on a screen, receiving visual error feedback in the form of a ball jumping toward the target after they pushed the button. The task also incorporated a propriovisual rotational perturbation to elicit and measure adaptation. To characterize thumb localization ability, we varied thumb speed and rotation diameter, assessed the effect of the propriovisual rotational perturbation, and compared index finger performance. Following task familiarization, average thumb localization error was relatively consistent, with a constant error (CE) of − 5.9°, variable error (VE) of 25.2°, and absolute error (AE) of 29.2°. Errors did not change significantly with speed or circle diameter. Reversing thumb rotation temporarily increased error followed by rapid error adaptation across the next 20 trials, as would be expected if individuals adapted using a body-centered (movement-aligned) frame of reference rather than a world-centered spatial frame. Localization error was comparable for the thumb and the index finger error for the same task and was correlated with a different, robotic assessment of finger proprioception (ρ = 0.61, p = 0.001). These findings indicate that dynamic thumb localization is somewhat inaccurate, although it can leverage visual feedback within a body-centered reference frame to adapt. Further, in unimpaired adults, the dynamic localization abilities of the thumb and index finger are related.

In rehabilitation research, coarse clinical outcome measures may limit the sensitivity of trials by failing to detect meaningful intervention-induced changes. Sensorized robotic platforms can potentially improve the evaluation of motor function, yet their reliability compared to skilled therapists remains unclear. This study utilized a robotic device to measure two fundamental impairments that are critical to ankle function: range of motion (ROM, active and passive) and dorsiflexion maximum voluntary contraction (MVC). In 34 chronic hemiparetic post-stroke individuals, we assessed test–retest reliability over two days for the robot and experienced therapists, who used a goniometer and manual muscle testing (MMT). We also evaluated robotic test–retest reliability in 36 young and 26 older unimpaired adults. Reliability for robotic and therapist-based AROM and MVC measures was high (ICC > 0.86), consistent across all groups. Robotic AROM and PROM measurements correlated strongly with therapist assessments (r > 0.60, p < 0.001) but were 120% and 37% larger than therapist assessments (p < 0.001), respectively. For the MVC measurement, the therapist assigned 85% of participants a score of 1 on the MMT, but their MVC torque was distributed from 0 to ~20 Nm. Measurement differences between methods likely arose from the robot’s constrained setup, allowing for compensatory muscle activation. The increased granularity provided by robotic MVC measurements could enable more precise tracking of motor recovery and facilitate tailored rehabilitation strategies. These results support the clinical utility of robotic platforms for ankle assessment, offering detailed, objective measurements that can augment traditional evaluations, and provide a benchmark dataset for other researchers.

In rehabilitation research, coarse clinical outcome measures may limit the sensitivity of trials by failing to detect meaningful intervention-induced changes. Sensorized robotic platforms can potentially improve the evaluation of motor function, yet their reliability compared to skilled therapists remains unclear. This study utilized a robotic device to measure two fundamental impairments that are critical to ankle function: range of motion (ROM, active and passive) and dorsiflexion maximum voluntary contraction (MVC). In 34 chronic hemiparetic post-stroke individuals, we assessed test-retest reliability over two days for the robot and experienced therapists, who used a goniometer and manual muscle testing (MMT). We also evaluated robotic test-retest reliability in 36 young and 26 older unimpaired adults. Reliability for robotic and therapist-based AROM and MVC measures was high (ICC > 0.86), consistent across all groups. Robotic AROM and PROM measure-ments correlated strongly with therapist assessments (r > 0.60, p < 0.001) but were 120% and 37% larger than therapist assessments (p < 0.001), respectively. For the MVC measurement, the therapist assigned 85% of participants a score of 1 on the MMT, but their MVC torque was distributed from 0 to ~20 Nm. Measurement differences between methods likely arose from the robot's constrained setup, allowing compensatory muscle activation. The increased granularity provided by robotic MVC measurements could enable more precise tracking of motor recovery and facilitate tailored rehabilitation strategies. These results support the clinical utility of robotic platforms for ankle assessment, offering detailed, objective measurements that can augment traditional evaluations. A supplementary dataset for benchmarking future research is provided.

Background: After stroke, ankle proprioceptive deficits are common and do not typically correlate with ankle weakness. Some studies report that these deficits correlate with gait function, supporting the importance of somatosensory input for gait control. Others have not found a relationship, possibly due to use of coarse proprioception measures. Robotic assessments of proprioception offer improved consistency and sensitivity. Objective: To establish relationships between ankle proprioception, gait function, and ankle motor in stroke survivors. Methods: We studied 39 individuals in the chronic phase of stroke using 2 robotic tests, Crisscross and Joint Position Reproduction (JPR), to quantify ankle proprioception. We examined associations of these measures with gait speed (10-meter walk test) and gait endurance (6-minute walk test). We also analyzed correlations with lower extremity motor impairment, including robotic measures of ankle strength (MVC) and active range of motion (AROM), and the lower extremity Fugl-Meyer exam (LEFM). Results: Impaired ankle proprioception was present in 87% of participants. Crisscross error weakly correlated with the 10mWT gait speed (ρ = −0.20, P = 0.23) and 6MWT distance (ρ = −0.28, P = .089). JPR error weakly correlated with 10mWT gait speed (ρ = −0.29, P = .092) and significantly correlated with 6MWT distance (ρ = −0.34, P = .04). No significant correlations were observed between ankle proprioceptive error and MVC, AROM, or LEFM ( P > 0.2). Conclusion: These results confirm the presence of a weak relationship between ankle proprioception and gait after stroke that is independent of several common measures of motor impairment.

The thumb plays a crucial role in hand function, yet its proprioceptive abilities remain poorly understood. Here we quantified dynamic thumb localization ability in unimpaired participants, using a novel task in which a robot moved the thumb in a circle and participants pressed a button when they felt their thumb aligning with a target point on a screen. After pressing the button, they received visual error feedback in the form of a ball jumping toward the target. To characterize thumb localization ability, we varied thumb speed and rotation diameter, assessed the effect of a propriovisual rotational perturbation, and compared index finger performance. Following task familiarization, thumb localization error was ~ 25º and did not change significantly with speed or circle diameter. Reversing thumb rotation increased error followed by rapid error adaptation across the next 20 trials, as would be expected if individuals formed an internal model based on a body-centered (movement-aligned) frame of reference rather than a world-centered spatial frame. Localization error was larger for the thumb than the index finger error for the same task (p = 0.02) and was correlated with a different, robotic assessment of finger proprioception (ρ = 0.61, p = 0.001). These findings indicate that dynamic thumb localization is somewhat inaccurate, although it can leverage visual feedback within a body-centered reference frame, a form of passive, cross-sensory adaptation. Further, in unimpaired adults, the dynamic proprioceptive abilities of the thumb and index finger are related, with thumb proprioception ability being less accurate than the finger.

Many medical conditions impair proprioception but there are few easy-to-deploy technologies for assessing proprioceptive deficits. Here, we developed a method—called “OpenPoint”—to quantify upper extremity (UE) proprioception using only a webcam as the sensor. OpenPoint automates a classic neurological test: the ability of a person to use one hand to point to a finger on their other hand with vision obscured. Proprioception ability is quantified with pointing error in the frontal plane measured by a deep-learning-based, computer vision library (MediaPipe). In a first experiment with 40 unimpaired adults, pointing error significantly increased when we replaced the target hand with a fake hand, verifying that this task depends on the availability of proprioceptive information from the target hand, and that we can reliably detect this dependence with computer vision. In a second experiment, we quantified UE proprioceptive ability in 16 post-stroke participants. Individuals post stroke exhibited increased pointing error (p < 0.001) that was correlated with finger proprioceptive error measured with an independent, robotic assessment (r = 0.62, p = 0.02). These results validate a novel method to assess UE proprioception ability using affordable computer technology, which provides a potential means to democratize quantitative proprioception testing in clinical and telemedicine environments.