Mechanisms of gait phase entrainment in healthy subjects during rhythmic electrical stimulation of the medial gastrocnemius

Gait Symmetric Adaptation and Aftereffect Through Concurrent Split-Belt Treadmill Walking and Explicit Visual Feedback Distortion

OBJECTIVE

Gait asymmetry can be improved with various gait training methods. Combining split-belt treadmill walking (SB) with visual feedback distortion (VD) could enhance motor learning, improving gait symmetry adaptation and retention. This study compared step length symmetry adaptation and aftereffects between SB-only and combined explicit VD with SB, as well as between explicit VD-only and combined explicit VD with SB.

METHOD

The 28-minute trials included three phases: a 3-minute baseline, a 10-minute adaptation, and a 15-minute post-adaptation. In the VD trial, two bars representing step lengths were displayed, with the right bar gradually decreasing by 3% to prompt participants to consciously correct their steps to match the heights of the two bars. In the SB trial, the right treadmill belt speed was incrementally increased by 5%. The VD+SB trial combined both perturbations. After the removal of these perturbations, the aftereffect of the adapted asymmetric step length was evaluated in the post-adaptation period.

RESULTS

During the adaptation period, the step length symmetry ratio shifted negatively in the SB trial, while it increased positively in the VD trial, indicating longer right steps than left. In the VD+SB trial, subjects extended their right step more than their left. Notably, the VD+SB trial demonstrated a longer aftereffect compared to both the SB-only and VD-only trials.

CONCLUSION

The visual distortion paradigm can be explicitly applied and integrated with split-belt treadmill walking to enhance the efficacy of symmetric gait adaptation, resulting in more sustained effects on the retention of newly learned motor patterns.

Amplitude and frequency of human gait synchronization with a machine oscillator system

Humans sometimes synchronize their steps to mechanical oscillations in the environment (e.g., when walking on a swaying bridge or with a wearable robot). Previous studies have discovered discrete frequencies and/or amplitudes where individuals spontaneously synchronize to external oscillations, but these parameters are often chosen arbitrarily or for convenience of a successful experiment and are sparsely sampled due to time constraints on subject availability. As a result, the parameter space under which human gait synchronization occurs is still relatively underexplored. Here we systematically measure synchronization over a broad range of parameters in machine oscillations, applied vertically near the body center of mass during walking. Two complementary experiments were utilized to characterize the amplitudes and frequencies where subjects' gait matched the oscillation frequency within ± 0.02 Hz for at least 80% of 20 consecutive steps (i.e., synchronization). Individuals were found to synchronize at lower amplitudes and in less time when the oscillation frequency was nearer their baseline step frequency, as well as over a broader range of frequencies during larger oscillation amplitudes. Subjects also had a greater tendency to synchronize with oscillation frequencies below (rather than above) their baseline step frequencies. The results of this study provide a comprehensive mapping of parameters where synchronization occurs and could inform the design of exoskeletons, rehabilitation devices and other gait-assistive technologies.

Induced discomfort promotes executive function while walking with(out) an artificial neuromuscular impairment

Neuromotor disorders can degrade one's ability to locomote and attend to salient stimuli in the environment. Many disorders are physiologically complex, making it difficult to tease apart interactions between motor adaptation and executive function processes. We address this challenge by giving participants a controlled artificial impairment, using electrical stimulation to produce an uncomfortable disruption in normal muscular coordination during locomotion. While adapting to this gait perturbation, participants performed an executive function task containing neutral and affectively charged stimuli. The artificial impairment was counterbalanced against control and sham (discomfort-only stimulation) walking conditions. Our twofold hypothesis that discomfort would selectively tax hot, emotionally charged executive function and motor adaptation would challenge cold, logical executive function was not supported. However, we found that the discomfort experienced with both stimulation conditions improved participants' ability to inhibit distracting information, enhancing this aspect of executive function, and the effect did not depend on whether the task was affectively charged. Moderate discomfort during physical activity may have improved inhibitory control by increasing arousal, a known factor mediating executive function. These results show that using a sensorimotor perturbation that acts internally and bridges multiple physiological domains, including discomfort, can reveal effects not seen with purely environmental manipulations. The broader implications are that when high cognitive performance is needed during physical activity, it may be beneficial to, quite literally, operate outside one's comfort zone.NEW & NOTEWORTHY When locomotor and cognitive tasks compete for shared neural resources, cognitive-motor interference may impair performance in both domains. To understand how impairments that cause pain or change neuromotor control impact cognition during locomotion, we gave healthy adults an uncomfortable, artificial neuromuscular impairment while they walked and completed a task dependent on ignoring distracting stimuli. We found that discomfort enhanced participants' ability to ignore distractions, providing new insight into the mediators of cognition during impaired movement.

Société de Biomécanique young investigator award 2022: Effects of applying functional electrical stimulation to ankle plantarflexor muscles on forward propulsion during walking in young healthy adults

The triceps surae muscle, composed of the gastrocnemius and soleus muscles, plays a major role in forward propulsion during walking. By generating positive ankle power during the push-off phase, these muscles produce the propulsive force required for forward progression. This study aimed to test the hypothesis that applying functional electrical stimulation (FES) to these muscles (soleus, gastrocnemius or the combination of the two) during the push-off phase would increase the ankle power generation and, consequently, enhance forward propulsion during walking in able-bodied adults. Fifteen young adults walked at their self-selected speed under four conditions: no stimulation, with bilateral stimulation of the soleus, gastrocnemius, and both muscles simultaneously. Muscles were stimulated just below the discomfort threshold during push-off, i.e., from heel-off to toe-off. FES significantly increased ankle power (+22 to 28 % depending on conditions), propulsive force (+15 to 18 %) and forward progression parameters such as walking speed (+14 to 20 %). Furthermore, walking speed was significantly higher (+5%) for combined soleus and gastrocnemius stimulation compared with gastrocnemius stimulation alone, with no further effect on other gait parameters. In conclusion, our results demonstrate that applying FES to the gastrocnemius and soleus, separately or simultaneously during the push-off phase, enhanced ankle power generation and, consequently, forward propulsion during walking in able-bodied adults. Combined stimulation of the soleus and gastrocnemius provided the greatest walking speed enhancement, without affecting other propulsion parameters. These findings could be useful for designing FES-based solutions for improving gait in healthy people with propulsion impairment, such as the elderly.

Human Gait Entrainment to Soft Robotic Hip Perturbation During Simulated Overground Walking

Entraining human gait with a periodic mechanical perturbation has been proposed as a potentially effective strategy for gait rehabilitation, but the related studies have mostly depended on the use of a fixed-speed treadmill (FST) due to various practical constraints. However, imposing a constant treadmill speed on participants becomes a critical problem because this speed constraint prohibits the participants from adjusting the gait speed, resulting in significant alterations in natural biomechanics as the entrainment alters the stride frequency. In this study, we hypothesized that the use of a variable-speed treadmill (VST), which enables the participants to continuously adjust their speed, can improve the success rate of gait entrainment and preserve natural gait biomechanics. To test this hypothesis, we recruited 15 young and healthy adults and let them walk on a conventional FST and a self-paced VST while wearing a soft robotic hip exosuit, which applied hip flexion perturbations at various frequencies, ranging from the preferred walking frequency to a 30% increased value. Kinematics and kinetics of the participants' walking under the two treadmill conditions were measured on two separate days. Experimental results demonstrated a higher success rate of entrainment during VST walking compared to FST walking, particularly at faster perturbation frequencies. Furthermore, walking on VST facilitated the maintenance of natural biomechanics, such as stride length and normalized propulsive impulse, better than walking on FST. The observed improvement, primarily attributed to allowing an increase in walking speed following the increase in the perturbation frequency, suggests that using a self-paced VST is a viable method for exploiting the potentially beneficial therapeutic effects of entrainment in gait rehabilitation.

Wearable sensing for understanding and influencing human movement in ecological contexts

Wearable sensors offer a unique opportunity to study movement in ecological contexts - that is, outside the laboratory where movement happens in ordinary life. This article discusses the purpose, means, and impact of using wearable sensors to assess movement context, kinematics, and kinetics during locomotion, and how this information can be used to better understand and influence movement. We outline the types of information wearable sensors can gather and highlight recent developments in sensor technology, data analysis, and applications. We close with a vision for important future research and key questions the field will need to address to bring the potential benefits of wearable sensing to fruition.

Effects of Functional Electrical Stimulation on Gait Characteristics in Healthy Individuals: A Systematic Review

BACKGROUND

This systematic review aimed to provide a comprehensive overview of the effects of functional electrical stimulation (FES) on gait characteristics in healthy individuals.

METHODS

Six electronic databases (PubMed, Embase, Epistemonikos, PEDro, COCHRANE Library, and Scopus) were searched for studies evaluating the effects of FES on spatiotemporal, kinematic, and kinetic gait parameters in healthy individuals. Two examiners evaluated the eligibility and quality of the included studies using the PEDro scale.

RESULTS

A total of 15 studies met the inclusion criteria. The findings from the literature reveal that FES can be used to modify lower-limb joint kinematics, i.e., to increase or reduce the range of motion of the hip, knee, and ankle joints. In addition, FES can be used to alter kinetics parameters, including ground reaction forces, center of pressure trajectory, or knee joint reaction force. As a consequence of these kinetics and kinematics changes, FES can lead to changes in spatiotemporal gait parameters, such as gait speed, step cadence, and stance duration.

CONCLUSIONS

The findings of this review improve our understanding of the effects of FES on gait biomechanics in healthy individuals and highlight the potential of this technology as a training or assistive solution for improving gait performance in this population.

How Might Consideration of Cell Polarity Affect Daily Therapeutic Practices?A Literature Review:

BACKGROUND

In addition to biochemical gradients and transcriptional networks, cell behaviour is controlled by endogenous bioelectrical signals resulting from the action of ion channels and pumps. Cells are regulated not only by their own membrane resting potential (Vmem) but also by the Vmem of neighbouring cells, establishing networks through electrical synapses known as gap junctions. V mem is the primary factor in producing a polarity that can regulate cell assimilation of various substances. This article aimed to examine how cell polarity can change and how variations in cell polarity may lead to clinical demonstrations.

MATERIALS AND METHODS

Using Cochrane Central, PubMed, Scopus, Web of Science (WOS), and Embase, a comprehensive qualitative literature review was conducted from February 1, 2018, to February 1, 2023, to identify studies addressing bioelectric, cell polarity, and electroceuticals in patients with foot and ankle problems.

RESULTS

Out of 1,281 publications, 27 were included. One study investigated bioelectric wound-healing. Twenty-five studies examined bioelectric nerve cell growth, whereas one study evaluated bioelectricity-induced cellular differentiation in the treatment of arteriopathies.

CONCLUSION

The author of this systematic review support addressing the predisposing factors and healing impediments for a disease, thereby enhancing the healing process and reducing the likelihood of recurrence or parallel conditions. This method of treatment has provided a summary of evidence indicating that cell polarity could be addressed for the treatment and prevention of most if not all, foot and ankle problems. However, owing to the limitations of V mem and bioelectricity measurement and the direct or indirect involvement of genetics and chemical gradients, further studies are required to confirm these results.

Gait Entrainment to Torque Pulses from a Hip Exoskeleton Robot

Robot-aided locomotor rehabilitation has proven challenging. To facilitate progress, it is important to first understand the neuro-mechanical dynamics and control of unimpaired human locomotion. Our previous studies found that human gait entrained to periodic torque pulses at the ankle when the pulse period was close to preferred stride duration. Moreover, synchronized gait exhibited constant phase relation with the pulses so that the robot provided mechanical assistance. To test the generality of mechanical gait entrainment, this study characterized unimpaired human subjects' responses to periodic torque pulses during overground walking. The intervention was applied by a hip exoskeleton robot, Samsung GEMS-H. Gait entrainment was assessed based on the time-course of the phase at which torque pulses occurred within each stride. Experiments were conducted for two consecutive days to evaluate whether the second day elicited more entrainment. Whether entrainment was affected by the difference between pulse period and preferred stride duration was also assessed. Results indicated that the intervention evoked gait entrainment that occurred more often when the period of perturbation was closer to subjects' preferred stride duration, but the difference between consecutive days was insignificant. Entrainment was accompanied by convergence of pulse phase to a similar value across all conditions, where the robot maximized mechanical assistance. Clear evidence of motor adaptation indicated the potential of the intervention for rehabilitation. This study quantified important aspects of the nonlinear neuro-mechanical dynamics underlying unimpaired human walking, which will inform the development of effective approaches to robot-aided locomotor rehabilitation, exploiting natural dynamics in a minimally-encumbering way.

Evaluating the energetics of entrainment in a human-machine coupled oscillator system

During locomotion, humans sometimes entrain (i.e. synchronize) their steps to external oscillations: e.g. swaying bridges, tandem walking, bouncy harnesses, vibrating treadmills, exoskeletons. Previous studies have discussed the role of nonlinear oscillators (e.g. central pattern generators) in facilitating entrainment. However, the energetics of such interactions are unknown. Given substantial evidence that humans prioritize economy during locomotion, we tested whether reduced metabolic expenditure is associated with human entrainment to vertical force oscillations, where frequency and amplitude were prescribed via a custom mechatronics system during walking. Although metabolic cost was not significantly reduced during entrainment, individuals expended less energy when the oscillation forces did net positive work on the body and roughly selected phase relationships that maximize positive work. It is possible that individuals use mechanical cues to infer energy cost and inform effective gait strategies. If so, an accurate prediction may rely on the relative stability of interactions with the environment. Our results suggest that entrainment occurs over a wide range of oscillation parameters, though not as a direct priority for minimizing metabolic cost. Instead, entrainment may act to stabilize interactions with the environment, thus increasing predictability for the effective implementation of internal models that guide energy minimization.

Machine learning to extract muscle fascicle length changes from dynamic ultrasound images in real-time

BACKGROUND AND OBJECTIVE

Dynamic muscle fascicle length measurements through B-mode ultrasound have become popular for the non-invasive physiological insights they provide regarding musculoskeletal structure-function. However, current practices typically require time consuming post-processing to track muscle length changes from B-mode images. A real-time measurement tool would not only save processing time but would also help pave the way toward closed-loop applications based on feedback signals driven by in vivo muscle length change patterns. In this paper, we benchmark an approach that combines traditional machine learning (ML) models with B-mode ultrasound recordings to obtain muscle fascicle length changes in real-time. To gauge the utility of this framework for 'in-the-loop' applications, we evaluate accuracy of the extracted muscle length change signals against time-series' derived from a standard, post-hoc automated tracking algorithm.

METHODS

We collected B-mode ultrasound data from the soleus muscle of six participants performing five defined ankle motion tasks: (a) seated, constrained ankle plantarflexion, (b) seated, free ankle dorsi/plantarflexion, (c) weight-bearing, calf raises (d) walking, and then a (e) mix. We trained machine learning (ML) models by pairing muscle fascicle lengths obtained from standardized automated tracking software (UltraTrack) with the respective B-mode ultrasound image input to the tracker, frame-by-frame. Then we conducted hyperparameter optimizations for five different ML models using a grid search to find the best performing parameters for a combination of high correlation and low RMSE between ML and UltraTrack processed muscle fascicle length trajectories. Finally, using the global best model/hyperparameter settings, we comprehensively evaluated training-testing outcomes within subject (i.e., train and test on same subject), cross subject (i.e., train on one subject, test on another) and within/direct cross task (i.e., train and test on same subject, but different task).

RESULTS

Support vector machine (SVM) was the best performing model with an average r = 0.70 ±0.34 and average RMSE = 2.86 ±2.55 mm across all direct training conditions and average r = 0.65 ±0.35 and average RMSE = 3.28 ±2.64 mm when optimized for all cross-participant conditions. Comparisons between ML vs. UltraTrack (i.e., ground truth) tracked muscle fascicle length versus time data indicated that ML tracked images reliably capture the salient qualitative features in ground truth length change data, even when correlation values are on the lower end. Furthermore, in the direct training, calf raises condition, which is most comparable to previous studies validating automated tracking performance during isolated contractions on a dynamometer, our ML approach yielded 0.90 average correlation, in line with other accepted tracking methods in the field.

CONCLUSIONS

By combining B-mode ultrasound and classical ML models, we demonstrate it is possible to achieve real-time tracking of human soleus muscle fascicles across a number of functionally relevant contractile conditions. This novel sensing modality paves the way for muscle physiology in-the-loop applications that could be used to modify gait via biofeedback or unlock novel wearable device control techniques that could enable restored or augmented locomotion performance.