Effects of a robot-aided somatosensory training on proprioception and motor function in stroke survivors

Abstract

Background: Proprioceptive deficits after stroke are associated with poor upper limb function, slower motor recovery, and decreased self-care ability. Improving proprioception should enhance motor control in stroke survivors, but current evidence is inconclusive. Thus, this study examined whether a robot-aided somatosensory-based training requiring increasingly accurate active wrist movements improves proprioceptive acuity as well as motor performance in chronic stroke.

Methods: Twelve adults with chronic stroke completed a 2-day training (age range: 42-74 years; median time-after-stroke: 12 months; median Fugl-Meyer UE: 65). Retention was assessed at Day 5. Grasping the handle of a wrist-robotic exoskeleton, participants trained to roll a virtual ball to a target through continuous wrist adduction/abduction movements. During training vision was occluded, but participants received real-time, vibro-tactile feedback on their forearm about ball position and speed. Primary outcome was the just-noticeable-difference (JND) wrist position sense threshold as a measure of proprioceptive acuity. Secondary outcomes were spatial error in an untrained wrist tracing task and somatosensory-evoked potentials (SEP) as a neural correlate of proprioceptive function. Ten neurologically-intact adults were recruited to serve as non-stroke controls for matched age, gender and hand dominance (age range: 44 to 79 years; 6 women, 4 men).

Results: Participants significantly reduced JND thresholds at posttest and retention (Stroke group: pretest: mean: 1.77° [SD: 0.54°] to posttest mean: 1.38° [0.34°]; Control group: 1.50° [0.46°] to posttest mean: 1.45° [SD: 0.54°]; F[2,37] = 4.54, p = 0.017, ηp2 = 0.20) in both groups. A higher pretest JND threshold was associated with a higher threshold reduction at posttest and retention (r = - 0.86, - 0.90, p ≤ 0.001) among the stroke participants. Error in the untrained tracing task was reduced by 22 % at posttest, yielding an effect size of w = 0.13. Stroke participants exhibited significantly reduced P27-N30 peak-to-peak SEP amplitude at pretest (U = 11, p = 0.03) compared to the non-stroke group. SEP measures did not change systematically with training.

Conclusions: This study provides proof-of-concept that non-visual, proprioceptive training can induce fast, measurable improvements in proprioceptive function in chronic stroke survivors. There is encouraging but inconclusive evidence that such somatosensory learning transfers to untrained motor tasks. Trial registration Clinicaltrials.gov; Registration ID: NCT02565407; Date of registration: 01/10/2015; URL: https://ichgcp.net/clinical-trials-registry/NCT02565407 .

Keywords: Cerebrovascular disease/stroke; Human; Rehabilitation; Somatosensation; Upper limb.

Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Fig. 1

Recruitment flowchart. UMN University of Minnesota, PM&R Physical medicine and rehabilitation

Fig. 2

a Study timeline. b Experimental setup of the robot and the virtual ball balancing task. Wrist abduction tilted the virtual table seen in the computer display toward the left, adduction toward the right, as indicated by the maroon arrows. The task was to move the virtual ball rolled into the blue target circle. The two vibration motors attached to the skin arm indicated the respective ball position relative to the target. The distal motor turned on when the ball was on the right side of the target, the proximal motor when the ball was to the left side. Distance from the target was frequency coded (frequency increased with increasing distance to the target. The motor on the non-trained side indicated the ball speed. c Figures of the untrained wrist tracing task. Red circles and arrows indicate the starting point and movement direction for right-handed users

Fig. 3

a Boxplot of Just-Noticeable Difference (JND) position sense thresholds at pretest, posttest and retention for both groups. Each box indicates the interquartile range (IQR). The line within the box indicates the median. Whiskers represent the 1st and 99th percentile. Adjacent diamond symbols show all individual subject JNDs. b Correlation between JND thresholds at pretest in relation to change in JND at retention. A negative value indicates a reduction in threshold, i.e. an improvement in proprioceptive acuity. c Change in JND for each participant as a function of training. Data are sorted in ascending order for the pretest value. Grey and white circles indicate the related values at posttest and retention

Fig. 4

a Exemplar wrist tracing performance at pretest for two stroke participants (S07, S10) during the triangle tracing task. The black triangle represents the mean trajectory of the controls. S07 demonstrated comparable performance to controls as indicated in the red dashed line, while S10 exhibited a large tracing error as indicated in the blue dashed line. b Boxplot of triangle tracing error at pretest, posttest and retention. Each box indicates the distribution between the 25th and 75th percentiles. The line within the box indicates the median. Whiskers represent the 1st and 99th percentile. Adjacent diamond symbols show all individual subject mean tracing errors values

Fig. 5

Median nerve SEP time-series data of two stroke participants and related summary data. a Stroke participant S08 exhibited a longer N30 latency and a decreased P27-N30 SEP amplitude in comparison to the average waveform of the control group. b Stroke participant S14 showed prolonged N30 and P45 latencies when compared to controls. c P27-N30 peak-to-peak amplitude across visits. Data of individual stroke participants and the summary statistics of the control group were shown: medians (lines), IQR (box boundary) and 5th−95th percentiles (whiskers)