Preliminary outcomes of combined treadmill and overground high-intensity interval training in ambulatory chronic stroke

Introduction: Locomotor high-intensity interval training (HIIT) is a promising intervention for stroke rehabilitation that typically involves bursts of fast treadmill walking alternated with recovery periods. However, overground translation of treadmill speed gains has been somewhat limited, some important outcomes have not been tested and baseline response predictors are poorly understood. This pilot study aimed to guide future research by assessing preliminary outcomes of combined overground and treadmill HIIT. Methods: Ten participants >6 months post stroke completed a multi-domain assessment battery before and after a 4-week no-intervention control phase, then again after a 4-week treatment phase involving 12 sessions of overground and treadmill HIIT. The primary analyses assessed relative changes in overground and treadmill walking speeds after HIIT, evaluated responsiveness of different outcome measures and estimated effects of baseline gait speed on treatment response. Results: Overground and treadmill gait function both improved during the treatment phase relative to the control phase, with overground speed changes averaging 61% of treadmill speed changes (95% CI: 33-89%). Moderate or larger effect sizes were observed for measures of gait performance, balance, fitness, cognition, fatigue, perceived change and brain volume. Participants with baseline comfortable gait speed <0.4 m/s had less absolute improvement in walking capacity but similar proportional and perceived changes. Discussion: Future locomotor HIIT studies should consider including: 1) both overground and treadmill training; 2) measures of cognition, fatigue and brain volume, to complement typical motor & fitness assessment; and 3) baseline gait speed as a covariate.

Speed-related but not detrended gait variability increases with more sensitive self-paced treadmill controllers at multiple slopes

Self-paced treadmills are being used more frequently to study humans walking with their self-selected gaits on a range of slopes. There are multiple options to purchase a treadmill with a built-in controller, or implement a custom written self-paced controller, which raises questions about how self-paced controller affect treadmill speed and gait biomechanics on multiple slopes. This study investigated how different self-paced treadmill controller sensitivities affected gait parameters and variability on decline, level, and incline slopes. We hypothesized that increasing self-paced controller sensitivity would increase gait variability on each slope. We also hypothesized that detrended variability could help mitigate differences in variability that arise from differences in speed fluctuations created by the self-paced controllers. Ten young adults walked on a self-paced treadmill using three controller sensitivities (low, medium, and high) and fixed speeds at three slopes (decline, -10°; level, 0°; incline, +10°). Within each slope, average walking speeds and spatiotemporal gait parameters were similar regardless of self-paced controller sensitivity. With higher controller sensitivities on each slope, speed fluctuations, speed variance, and step length variance increased whereas step frequency variance and step width variance were unaffected. Detrended variance was not affected by controller sensitivity suggesting that detrending variability helps mitigate differences associated with treadmill speed fluctuations. Speed-trend step length variances, however, increased with more sensitive controllers. Further, detrended step length variances were similar for self-paced and fixed speed walking, whereas self-paced walking included substantial speed-trend step length variance not present in fixed speed walking. In addition, regardless of the self-paced controller, subjects walked fastest on the level slope with the longest steps, narrowest steps, and least variance. Overall, our findings suggest that separating gait variability into speed-trend and detrended variability could be beneficial for interpreting gait variability among multiple self-paced treadmill studies and when comparing self-paced walking with fixed speed walking.

Exploiting telerobotics for sensorimotor rehabilitation: a locomotor embodiment

Background Manual treadmill training is used for rehabilitating locomotor impairments but can be physically demanding for trainers. This has been addressed by enlisting robots, but in doing so, the ability of trainers to use their experience and judgment to modulate locomotor assistance on the fly has been lost. This paper explores the feasibility of a telerobotics approach for locomotor training that allows patients to receive remote physical assistance from trainers. Methods In the approach, a trainer holds a small robotic manipulandum that shadows the motion of a large robotic arm magnetically attached to a locomoting patient's leg. When the trainer deflects the manipulandum, the robotic arm applies a proportional force to the patient. An initial evaluation of the telerobotic system’s transparency (ability to follow the leg during unassisted locomotion) was performed with two unimpaired participants. Transparency was quantified by the magnitude of unwanted robot interaction forces. In a small six-session feasibility study, six individuals who had prior strokes telerobotically interacted with two trainers (separately), who assisted in altering a targeted gait feature: an increase in the affected leg’s swing length. Results During unassisted walking, unwanted robot interaction forces averaged 3−4 N (swing–stance) for unimpaired individuals and 2−3 N for the patients who survived strokes. Transients averaging about 10 N were sometimes present at heel-strike/toe-off. For five of six patients, these forces increased with treadmill speed during stance (R2 = .99; p < 0.001) and increased with patient height during swing (R2 = .71; p = 0.073). During assisted walking, the trainers applied 3.0 ± 2.8 N (mean ± standard deviation across patients) and 14.1 ± 3.4 N of force anteriorly and upwards, respectively. The patients exhibited a 20 ± 21% increase in unassisted swing length between Days 1−6 (p = 0.058). Conclusions The results support the feasibility of locomotor assistance with a telerobotics approach. Simultaneous measurement of trainer manipulative actions, patient motor responses, and the forces associated with these interactions may prove useful for testing sensorimotor rehabilitation hypotheses. Further research with clinicians as operators and randomized controlled trials are needed before conclusions regarding efficacy can be made.

Physiological Responses and Predictors of Performance in a Simulated Competitive Ski Mountaineering Race

Competitive ski mountaineering (SKIMO) has achieved great popularity within the past years. However, knowledge about the predictors of performance and physiological response to SKIMO racing is limited. Therefore, 21 male SKIMO athletes split into two performance groups (elite: VO2max 71.2 ± 6.8 ml· min-1· kg-1 vs. sub-elite: 62.5 ± 4.7 ml· min-1· kg-1) were tested and analysed during a vertical SKIMO race simulation (523 m elevation gain) and in a laboratory SKIMO specific ramp test. In both cases, oxygen consumption (VO2), heart rate (HR), blood lactate and cycle characteristics were measured. During the race simulation, the elite athletes were approximately 5 min faster compared with the sub-elite (27:15 ± 1:16 min; 32:31 ± 2:13 min; p < 0.001). VO2 was higher for elite athletes during the race simulation (p = 0.046) and in the laboratory test at ventilatory threshold 2 (p = 0.005) and at maximum VO2 (p = 0.003). Laboratory maximum power output is displayed as treadmill speed and was higher for elite than sub-elite athletes (7.4 ± 0.3 km h-1; 6.6 ± 0.3 km h-1; p < 0.001). Lactate values were higher in the laboratory maximum ramp test than in the race simulation (p < 0.001). Pearson’s correlation coefficient between race time and performance parameters was highest for velocity and VO2 related parameters during the laboratory test (r > 0.6). Elite athletes showed their superiority in the race simulation as well as during the maximum ramp test. While HR analysis revealed a similar strain to both cohorts in both tests, the superiority can be explainable by higher VO2 and power output. To further push the performance of SKIMO athletes, the development of named factors like power output at maximum and ventilatory threshold 2 seems crucial.

Speed-related but not detrended gait variability increases with more sensitive self-paced treadmill controllers at multiple slopes

Self-paced treadmills are being used more and more to study humans walking with their self-selected gaits on a range of slopes. There are multiple options to purchase a treadmill with or implement a custom written self-paced controller, which raises questions about how self-paced controller affect treadmill speed and gait biomechanics on multiple slopes. This study investigated how different self-paced treadmill controller sensitivities affected gait parameters and variability on a decline, level, and incline slopes. We hypothesized that increasing self-paced controller sensitivity would increase gait variability on each slope. We also hypothesized that detrended variability could help mitigate differences in variability that arise from differences in speed fluctuations created by the self-paced controllers. Ten young adults walked on a self-paced treadmill using three self-paced controller sensitivities (low, medium, and high) and fixed speeds at three slopes (decline, −10°; level, 0°; incline, +10°). Within each slope, average walking speeds and spatiotemporal gait parameters were similar regardless of self-paced controller sensitivity. With higher controller sensitivities on each slope, speed fluctuations, speed variance, and step length variance increased whereas step frequency variance and step width variance were unaffected. Detrended variance was not affected by controller sensitivity suggesting that detrending variability helps mitigate differences associated with treadmill speed fluctuations. Speed-trend step length variances, however, increased with more sensitive controllers. Further, detrended step length variances were similar for self-paced and fixed speed walking, whereas self-paced walking included substantial speed-trend step length variance not present in fixed speed walking. In addition, regardless of the self-paced controller, subjects walked fastest on the level slope with the longest steps, widest steps, and least variance. Overall, our findings suggest that separating gait variability into speed-trend and detrended variability could be beneficial for interpreting gait variability among multiple self-paced treadmill studies and when comparing self-paced walking with fixed speed walking.

Exploiting Telerobotics for Sensorimotor Rehabilitation: A Locomotor Embodiment

Background: Manual treadmill training is used for rehabilitating locomotor impairments but can be physically demanding for trainers. This has been addressed by enlisting robots, but in doing so, the ability of trainers to use their experience and judgment to modulate locomotor assistance on the fly has been lost. This paper explores the feasibility of a telerobotics approach that allows patients to receive physical assistance from robotically augmented trainers.Methods: In the approach, a trainer holds onto a small robotic manipulandum that shadows the motion of a large robotic arm, which is magnetically attached to the leg of a locomoting patient. When the trainer deflects the manipulandum, the robotic arm applies a proportional force to the patient. After an initial evaluation of the telerobotic system’s ability to follow the leg during unassisted locomotion with unimpaired participants, a small feasibility study was performed with six patients with prior strokes. Over six days, the patients interacted with two robotically augmented trainers (separately), who assisted in altering a targeted gait feature: an increase in the affected leg’s swing length. Results: During unassisted walking, unwanted robot interaction forces averaged 3−4 N (swing−stance) for unimpaired individuals and 2−3 N for the patients who survived strokes. Transients averaging about 10 N were sometimes present at heel-strike/toe-off. For five of six patients, these forces increased with treadmill speed during stance (R2 = .99; p < .001) and increased with patient height (R2 = .71; p = .073) during swing. During assisted walking, the trainers applied 3.0 ± 2.8 N (mean ± standard deviation across patients) and 14.1 ± 3.4 N of force anteriorly and upwards, respectively. The patients exhibited a 20 ± 21% increase in unassisted swing length between Days 1−6 (p = .058). Conclusions: The results support the feasibility of locomotor assistance with a telerobotics approach. Simultaneous measurement of trainer manipulative actions, patient motor responses, and the forces associated with these interactions may prove useful for testing sensorimotor rehabilitation hypotheses. Further research with clinicians as operators and randomized controlled trials with more comprehensive outcome measures are needed before conclusions regarding efficacy can be reached.

Fuzzy controller for the treadmill speed adaptation system in mechatronic device for gait reeducation

Training with use of mechatronic devices is an innovative rehabilitation method for patients with various locomotor dysfunction. High efficiency of training is noted in systems that combine a treadmill or orthosis with a body weight support system. Speed control is a limitation of such rehabilitation systems. In commercially available devices, the treadmill speed is constant or set by the therapist. Even better training results should be obtained for devices in which the speed of the treadmill will be automatically adjusted to the patient walking pace. This study presents a mechatronic device for locomotor training that uses an algorithm to adjust the speed of the treadmill. This speed is controlled with use of a sensor that measures the rope inclination. The end of rope is fastened to the orthopaedic harness. Speed control is realized in such a way that ensures the smallest possible swing angle of the rope. A fuzzy controller was applied to adjust the treadmill speed. The drive system of the treadmill is equipped in a servodrive with PMSM motor and energy recovery module, which allows smooth speed control, limiting acceleration and minimizing electricity consumption. The presented solution was implemented in a real object and subjected to experimental tests.

Significance of trends in gait dynamics

Trends in time series generated by physiological control systems are ubiquitous. Determining whether trends arise from intrinsic system dynamics or originate outside of the system is a fundamental problem of fractal series analysis. In the latter case, it is necessary to filter out the trends before attempting to quantify correlations in the noise (residuals). For over two decades, detrended fluctuation analysis (DFA) has been used to calculate scaling exponents of stride time (ST), stride length (SL), and stride speed (SS) of human gait. Herein, rather than relying on the very specific form of detrending characteristic of DFA, we adopt Multivariate Adaptive Regression Splines (MARS) to explicitly determine trends in spatio-temporal gait parameters during treadmill walking. Then, we use the madogram estimator to calculate the scaling exponent of the corresponding MARS residuals. The durations of ST and SL trends are determined to be independent of treadmill speed and have distributions with exponential tails. At all speeds considered, the trends of ST and SL are strongly correlated and are statistically independent of their corresponding residuals. The averages of scaling exponents of ST and SL MARS residuals are slightly smaller than 0.5. Thus, contrary to the interpretation prevalent in the literature, the statistical properties of ST and SL time series originate from the superposition of large scale trends and small scale fluctuations. We show that trends serve as the control manifolds about which ST and SL fluctuate. Moreover, the trend speed, defined as the ratio of instantaneous values of SL and ST trends, is tightly controlled about the treadmill speed. The strong coupling between the ST and SL trends ensures that the concomitant changes of their values correspond to movement along the constant speed goal equivalent manifold as postulated by Dingwell et al. 10.1371/journal.pcbi.1000856.