A user-driven treadmill control scheme for simulating overground locomotion

Outdoor walking exhibits peak ankle and knee flexion differences compared to fixed and adaptive-speed treadmills in older adults

Background

Walking mechanics recorded with a traditional treadmill may not be the same as the mechanics exhibited during activities of daily living due to constrained walking speeds. Adaptive-speed treadmills allow for unconstrained walking speeds similar to outdoor walking. The aim of this study was to determine differences in kinematic walking parameters of older adults between adaptive-speed treadmill (AST), fixed-speed treadmill (FST) and outdoor walking. We hypothesized that self-selected walking speed (SSWS) during AST walking and outdoor walking would increase compared to FST walking. Furthermore, we hypothesized that AST walking and outdoor walking would increase peak knee flexion, hip flexion, and ankle plantarflexion angles compared to FST walking independent of walking speed changes.

Methods

Fourteen older adult participants were asked to complete 3 min of FST and AST walking on a split-belt treadmill. Participants were also asked to complete 6 min of outdoor walking following a circular route in a neighboring park. A wireless inertial measurement unit-based motion capture system was used to record lower extremity kinematics during all walking conditions.

Results

The outdoor walking condition produces significantly higher SSWS compared to FST (p < 0.001) and AST (p = 0.02) conditions. A significantly faster SSWS was exhibited during the AST condition compared to the FST condition (p = 0.026). Significantly higher peak ankle plantarflexion angles are exhibited during the outdoor walking condition compared to the AST (p < 0.001, g = 1.14) and FST (p < 0.001, g = 1.13) conditions after accounting for walking speed. There was a significantly lowered difference between the outdoor walking condition and both AST (p = 0.029, g = 0.49) and FST (p = 0.013, g = 0.63) conditions in peak knee flexion angles after accounting for SSWS. There are no significant differences between outdoor, AST, and FST conditions on peak hip flexion angles. Older adults exhibit changes in peak ankle plantarflexion and peak knee flexion angles during outdoor walking compared to treadmill walking but not between treadmill controller types. We found no differences in the kinematics exhibited by older adults between both AST and FST walking.

Conclusions

Incorporating unconstrained walking speed with the AST while maintaining similar FST sagittal plane kinematics may allow for more translatable conditional balance and walking rehabilitation.

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.

Novel velocity estimation for symmetric and asymmetric self-paced treadmill training

Background

Self-paced treadmills (SPT) can provide an engaging setting for gait rehabilitation by responding directly to the user’s intent to modulate the external environment and internal effort. They also can improve gait analyses by allowing scientists and clinicians to directly measure the effect of an intervention on walking velocity. Unfortunately, many common SPT algorithms are not suitable for individuals with gait impairment because they are designed for symmetric gait patterns. When the user’s gait is asymmetric due to paresis or if it contains large accelerations, the performance is diminished. Creating and validating an SPT that is suitable for asymmetric gait will improve our ability to study rehabilitation interventions in populations with gait impairment. The objective of this study was to test and validate a novel self-paced treadmill on both symmetric and asymmetric gait patterns and evaluate differences in gait kinematics, kinetics, and muscle activity between fixed-speed and self-paced treadmill walking.

Methods

We collected motion capture, ground reaction force data, and muscle activity from 6 muscles in the dominant leg during walking from 8 unimpaired subjects. In the baseline condition, the subjects walked at 3 fixed-speeds normalized to their leg length as Froude numbers. We developed a novel kinematic method for increasing the accuracy of the user’s estimated walking velocity and compared our method against other published algorithms at each speed. Afterward, subjects walked on the SPT while matching their walking speed to a given target velocity using visual feedback of the treadmill speed. We evaluated the SPT by measuring steady-state error and the number of steps to reach the desired speed. We split the gait cycle into 7 phases and compared the kinematic, kinetic, and muscle activity between the fixed speed and self-paced mode in each phase. Then, we validated the performance of the SPT for asymmetric gait by having subjects walk on the SPT while wearing a locked-knee brace set to 0° on the non-dominant leg.

Results

Our SPT enabled controlled walking for both symmetric and asymmetric gait patterns. Starting from rest, subjects were able to control the SPT to reach the targeted speeds using visual feedback in 13–21 steps. With the locked knee brace, subjects controlled the treadmill with substantial step length and step velocity asymmetry. One subject was able to execute a step-to gait and halt the treadmill on heel-strikes with the braced leg. Our kinematic correction for step-length outperformed the competing algorithms by significantly reducing the velocity estimation error at the tested velocities. The joint kinematics, joint torques, and muscle activity were generally similar between fixed-speed and self-paced walking. Statistically significant differences were found in 5 of 63 tests for joint kinematics, 2 of 63 tests for joint torques, and 9 of 126 tests for muscle activity. The differences that were statistically significant were not found across all speeds and were generally small enough to be of limited clinical relevance.

Conclusions

We present a validated method for implementing a self-paced treadmill for asymmetric and symmetric gaits. As a result of the increased accuracy of our estimation algorithm, our SPT produced controlled walking without including a position feedback controller, thereby reducing the influence of the controller on measurements of the user’s true walking speed. Our method relies only on a kinematic correction to step length and step time which can support transfer to systems outside of the laboratory for symmetric and asymmetric gaits in clinical populations.

Dynamic structure of variability in joint angles and center of mass position during user-driven treadmill walking

BACKGROUND

Overground locomotion exhibits greater movement variability and less dynamic stability compared to typical fixed-speed treadmill walking. To minimize the differences between treadmill and overground locomotion, researchers are developing user-driven treadmill systems that adjust the speed of the treadmill belts in real-time based on how fast the subject is trying to walk.

RESEARCH QUESTION

Does dynamic structure of variability, quantified by the Lyapunov exponent (LyE), of joint angles and center of mass (COM) position differ between a fixed-speed treadmill (FTM) and user-driven treadmill (UTM) for healthy subjects?

METHODS

Eleven healthy, adult subjects walked on a user-driven treadmill that updated its speed in real-time based on the subjects' propulsive forces, location, step length, and step time, and at a matched speed on a typical, fixed-speed treadmill for 1-minute. The LyE for flexion/extension joint angles and center of mass position were calculated.

RESULTS

Subjects exhibited higher LyE values of joint angles on the UTM compared to the FTM indicating that walking on the UTM may be more similar to overground locomotion. No change in COM LyE was observed between treadmill conditions indicating that subjects' balance was not significantly altered by this new training paradigm.

SIGNIFICANCE

The user-driven treadmill may be a more valuable rehabilitation tool for improving gait than fixed-speed treadmill training, as it may increase the effectiveness of transitioning learned behaviors to overground compared to fixed-speed treadmills.

Validating attentive locomotion training using interactive treadmill: an fNIRS study

BACKGROUND

Existing treadmill-based locomotion training, which has been used for gait function recovery, still has limitations, such as less attentive training. Interactive treadmills (ITMs) were developed to overcome these limitations, but it has not yet been verified that ITMs can make the user pay closer attention to walk training.

METHODS

An experimental comparison between ITMs and conventional treadmills was conducted by measuring the level of the user's attention using functional near-infrared spectroscopy (fNIRS). To consider the effect of task complexity on the subject's attention, we provided two (slow and fast) speed conditions for walking on both treadmills.

RESULTS

Both the cortical activity images and oxygenated hemoglobin (oxyHb) changes showed that the level of attention to walking induced by the ITM was significantly higher than that induced by the conventional treadmill. We found that the walking speed on the ITM also affected the level of attention.

CONCLUSION

ITM-based locomotion training would be a promising solution to the limitations of existing treadmill-based locomotion training currently used to improve gait function recovery.

TRIAL REGISTRATION

DGIST-HR-150309-03-02 . Registered 01 March 2015.

Walking speed and spatiotemporal step mean measures are reliable during feedback-controlled treadmill walking; however, spatiotemporal step variability is not reliable

The purpose of the study was to compare the effects of a feedback-controlled treadmill (FeedbackTM) to a traditional fixed-speed treadmill (FixedTM) on spatiotemporal gait means, variability, and dynamics. The study also examined inter-session reliability when using the FeedbackTM. Ten young adults walked on the FeedbackTM for a 5-minute familiarization followed by a 16-minute experimental trial. They returned within one week and completed a 5-minute familiarization followed by a 16-minute experimental trial each for FeedbackTM and FixedTM conditions. Mean walking speed and step time, length, width, and speed means and coefficient of variation were calculated from all experimental conditions. Step time, length, width, and speed gait dynamics were analyzed using detrended fluctuation analysis. Mean differences between experimental trials were determined using ANOVAs and reliability between FeedbackTM sessions was determined by intraclass correlation coefficient. No difference was found in mean walking speed nor spatiotemporal variables, with the exception of step width, between the experimental trials. All mean spatiotemporal variables demonstrated good to excellent reliability between sessions, while coefficient of variation was not reliable. Gait dynamics of step time, length, width, and speed were significantly more persistent during the FeedbackTM condition compared to FixedTM, especially step speed. However, gait dynamics demonstrated fair to poor reliability between FeedbackTM sessions. When walking on the FeedbackTM, users maintain a consistent set point, yet the gait dynamics around the mean are different when compared to walking on a FixedTM. In addition, spatiotemporal gait dynamics and variability may not be consistent across separate days when using the FeedbackTM.

Biomechanical Evaluation of Virtual Reality-based Turning on a Self-Paced Linear Treadmill

BACKGROUND

Patients with brain injuries such as Parkinson's disease or stroke exhibit abnormal gait characteristics especially during gait transitions such as step initiation and turning. Since such transitions could precipitate falls and resultant injuries, evaluation and rehabilitation of non-steady state gait in those patients are important. Whereas body weight supported treadmill training (BWSTT) provides a safe and controlled environment for gait training, it is unable to adequately train for gait transitions since the typical linear treadmill does not allow for changes in walking direction and natural fluctuations in speed.

RESEARCH QUESTION

This paper verifies if the suggested virtual reality (VR) based walking interface combined with the unidirectional treadmill can stimulate the user to initiate turning gait.

METHODS

To validate whether initiation of turning was successfully achieved with the proposed walking system, we developed the VR-based walking interface combined with the self-paced treadmill and compared kinematics, kinetics, and muscle activation levels during the VR-based turning and over ground (OG) turning as well as between straight walking and turning within conditions.

RESULTS

Despite walking on a linear treadmill, subjects showed significant increases in head rotation, pelvic rotation, right hip abduction, left hip adduction, foot progression, medial-lateral ground reaction forces, right medial hamstring activation level, and changes in step width during the VR turn compared to straight walking.

SIGNIFICANCE

The developed VR-based turning interface can provide a safe and controlled environment for assessment of turning in healthy controls and may have a potential for assessment and training in patients with neurological disorders.

Walking speed changes in response to novel user-driven treadmill control

Implementing user-driven treadmill control in gait training programs for rehabilitation may be an effective means of enhancing motor learning and improving functional performance. This study aimed to determine the effect of a user-driven treadmill control scheme on walking speeds, anterior ground reaction forces (AGRF), and trailing limb angles (TLA) of healthy adults. Twenty-three participants completed a 10-m overground walking task to measure their overground self-selected (SS) walking speeds. Then, they walked at their SS and fastest comfortable walking speeds on an instrumented split-belt treadmill in its fixed speed and user-driven control modes. The user-driven treadmill controller combined inertial-force, gait parameter, and position based control to adjust the treadmill belt speed in real time. Walking speeds, peak AGRF, and TLA were compared among test conditions using paired t-tests (α = 0.05). Participants chose significantly faster SS and fast walking speeds in the user-driven mode than the fixed speed mode (p > 0.05). There was no significant difference between the overground SS walking speed and the SS speed from the user-driven trials (p < 0.05). Changes in AGRF and TLA were caused primarily by changes in walking speed, not the treadmill controller. Our findings show the user-driven treadmill controller allowed participants to select walking speeds faster than their chosen speeds on the fixed speed treadmill and similar to their overground speeds. Since user-driven treadmill walking increases cognitive activity and natural mobility, these results suggest user-driven treadmill control would be a beneficial addition to current gait training programs for rehabilitation.

Reliability of a Feedback-Controlled Treadmill Algorithm Dependent on the User's Behavior

The reliability of the treadmill belt speed using a feedback-controlled treadmill algorithm was analyzed in this study. Using biomechanical factors of the participant's walking behavior, an estimated walking speed was calculated and used to adjust the speed of the treadmill. Our proposed algorithm expands on the current hypotheses of feedback-controlled treadmill algorithms and is presented below. Nine healthy, young adults walked on a treadmill controlled by the algorithm for three trials over two days. Each participant walked on the feedback-controlled treadmill for one 16-minute and one five-minute trial during day one and one 16-minute trial during day two. Mean, standard deviation, interclass correlation coefficient (ICC), and standard error of measurement (SEM) were analyzed on the treadmill belt speed mean, standard deviation, and coefficient of variation. There were significantly high ICC for mean treadmill speed within- and between-days. Treadmill speed standard deviation and coefficient of variation were significantly reliable within-day. These results suggest the algorithm will reliably produce the same treadmill belt speed mean, but may only produce a similar treadmill belt speed standard deviation and coefficient of variation if the trials are performed in the same day. A feedback-controlled treadmill algorithm that accounts for the user's behavior provides a greater level of control and minimizes any possible constraints of walking on a conventional treadmill.

User-driven control increases cortical activity during treadmill walking: an EEG study

Treadmills provide a safe and efficient method for gait rehabilitation but treadmill based training paradigms have not been shown to create superior results when compared with traditional physical therapy methods such as overground training. One explanation for this may be that walking at a constant, fixed speed requires little mental engagement from the user, which has been postulated as a key factor in the success of motor learning. To increase mental engagement, we developed a user-driven treadmill control scheme. In this paper we use electroencephalography (EEG) to compare cortical activity during user-driven (active) walking with activity on a normal (passive) treadmill in nine healthy subjects. We used independent component analysis (ICA) to isolate brain activity from artifactual components. We fit equivalent dipole sources to each brain component and clustered these across subjects. Our analysis revealed that relative to the passive treadmill, active walking resulted in statistically significant decreases in spectral power, i.e. desynchronization, in the anterior cingulate, sensorimotor cortices, and posterior parietal lobe of the cortex. These results indicate that user-driven treadmills more fully engage the motor cortex and therefore could facilitate better training outcomes than a traditional treadmill.

Prefrontal, posterior parietal and sensorimotor network activity underlying speed control during walking

Accumulating evidence suggests cortical circuits may contribute to control of human locomotion. Here, noninvasive electroencephalography (EEG) recorded from able-bodied volunteers during a novel treadmill walking paradigm was used to assess neural correlates of walking. A systematic processing method, including a recently developed subspace reconstruction algorithm, reduced movement-related EEG artifact prior to independent component analysis and dipole source localization. We quantified cortical activity while participants tracked slow and fast target speeds across two treadmill conditions: an active mode that adjusted belt speed based on user movements and a passive mode reflecting a typical treadmill. Our results reveal frequency specific, multi-focal task related changes in cortical oscillations elicited by active walking. Low γ band power, localized to the prefrontal and posterior parietal cortices, was significantly increased during double support and early swing phases, critical points in the gait cycle since the active controller adjusted speed based on pelvis position and swing foot velocity. These phasic γ band synchronizations provide evidence that prefrontal and posterior parietal networks, previously implicated in visuo-spatial and somotosensory integration, are engaged to enhance lower limb control during gait. Sustained μ and β band desynchronization within sensorimotor cortex, a neural correlate for movement, was observed during walking thereby validating our methods for isolating cortical activity. Our results also demonstrate the utility of EEG recorded during locomotion for probing the multi-regional cortical networks which underpin its execution. For example, the cortical network engagement elicited by the active treadmill suggests that it may enhance neuroplasticity for more effective motor training.

Low-cost implementation of a self-paced treadmill by using a commercial depth sensor

A self-paced treadmill that can simulate overground walking has the potential to improve the effectiveness of treadmill training for gait rehabilitation. We have implemented a self-paced treadmill without the need for expensive equipment such as a motion capture system and an instrumented treadmill. For this, an inexpensive depth sensor, ASUS XtionTM, substitutes for the motion capture system, and a low-cost commercial treadmill is considered as the platform of the self-paced treadmill. The proposed self-paced treadmill is also convenient because the depth sensor does not require markers placed on user's body. Through pilot tests with two healthy subjects, it is quantitatively and qualitatively verified that the proposed self-paced treadmill achieves similar performance as one which utilizes a commercial motion capture system (VICON) as well as an instrumented treadmill.