A novel walking speed estimation scheme and its application to treadmill control for gait rehabilitation

Virtual reality skateboarding training for balance and functional performance in degenerative lumbar spine disease

BACKGROUND

Degenerative lumbar spine disease (DLD) is a prevalent condition in middle-aged and elderly individuals. DLD frequently results in pain, muscle weakness, and motor impairment, which affect postural stability and functional performance in daily activities. Simulated skateboarding training could enable patients with DLD to engage in exercise with less pain and focus on single-leg weight-bearing. The purpose of this study was to investigate the effects of virtual reality (VR) skateboarding training on balance and functional performance in patients with DLD.

METHODS

Fourteen patients with DLD and 21 age-matched healthy individuals completed a 6-week program of VR skateboarding training. The motion capture and force platform systems were synchronized to collect data during a single-leg stance test (SLST). Musculoskeletal simulation was utilized to calculate muscle force based on the data. Four functional performance tests were conducted to evaluate the improvement after the training. A Visual Analogue Scale (VAS) was also employed for pain assessment.

RESULTS

After the training, pain intensity significantly decreased in patients with DLD (p = 0.024). Before the training, patients with DLD took longer than healthy individuals on the five times sit-to-stand test (p = 0.024). After the training, no significant between-group differences were observed in any of the functional performance tests (p > 0.05). In balance, patients with DLD were similar to healthy individuals after the training, except that the mean frequency (p = 0.014) was higher. Patients with DLD initially had higher biceps femoris force demands (p = 0.028) but shifted to increased gluteus maximus demand after the training (p = 0.037). Gluteus medius strength significantly improved in patients with DLD (p = 0.039), while healthy individuals showed consistent muscle force (p > 0.05).

CONCLUSION

This is the first study to apply the novel VR skateboarding training to patients with DLD. VR skateboarding training enabled patients with DLD to achieve the training effects in a posture that relieves lumbar spine pressure. The results also emphasized the significant benefits to patients with DLD, such as reduced pain, enhanced balance, and improved muscle performance.

How Important is Position in Adaptive Treadmill Control?

To more closely mimic overground walking, researchers are developing adaptive treadmills (ATMs) that update belt speed in real-time based on user gait mechanics. Many existing ATM control schemes are solely based on position on the belt and do not respond to changes in gait mechanics, like propulsive forces, that result in increased overground walking speed. To target natural causal mechanisms to alter speed, we developed an ATM controller that adjusts speed via changes in position, step length, and propulsion. Gains on each input dictate the impact of the corresponding parameter on belt speed. The study objective was to determine the effect of modifying the position gain on self-selected walking speed, measures of propulsion, and step length. Twenty-two participants walked at their self-selected speed with four ATM controllers, each with a unique position gain. Walking speed, anterior and posterior ground reaction force peaks and impulses, net impulse, and step length were compared between conditions. Smaller position gains promoted more equivalent anterior and posterior impulses, resulting in a net impulse closer to zero (p = 0.0043), a characteristic of healthy gait. Walking speed, anterior and posterior ground reaction force peaks and impulses, and step length did not change between conditions (all p > 0.05). These results suggest that reducing the importance of position in the ATM controller may promote more balanced anterior and posterior impulses, possibly improving the efficacy of the ATM for gait rehabilitation by emphasizing changes in gait mechanics instead of position to naturally adjust speed.

A robotic treadmill system to mimic overground walking training with body weight support

Introduction

Body weight support overground walking training (BWSOWT) is widely used in gait rehabilitation. However, existing systems require large workspace, complex structure, and substantial installation cost for the actuator, which make those systems inappropriate for the clinical environment. For wide clinical use, the proposed system is based on a self-paced treadmill, and uses an optimized body weight support with frame-based two-wire mechanism.

Method

The Interactive treadmill was used to mimic overground walking. We opted the conventional DC motors to partially unload the body weight and modified pelvic type harness to allow natural pelvic motion. The performance of the proposed system on the measurement of anterior/posterior position, force control, and pelvic motion was evaluated with 8 healthy subjects during walking training.

Results

We verified that the proposed system was the cost/space-effective and showed the more accurate anterior/posterior position than motion sensor, comparable force control performance, and natural pelvic motion.

Discussion

The proposed system is cost/space effective, and able to mimic overground walking training with body weight support. In future work, we will improve the force control performance and optimize the training protocol for wide clinical use.

A Comparison of Force-Plate Based Center of Mass Estimation Algorithms

Estimating horizontal center of mass (CoM) is an important process that is used in the control of self-paced treadmills, as well as in clinical and scientific biomechanical analysis. Many laboratories use motion-capture to estimate CoM, while others use force-plate based estimates, either because they cannot access motion-capture or they do not want to be taxed with post-processing optoelectronic data. Three force-plate derived center of mass estimation algorithms were compared against a benchmark motion-capture technique. Two of them have recently been reported in the literature, and both rely on numerical integration of 2nd-order differential equations. We propose a third technique that uses an algebraic equation to directly relate center of pressure to center of mass without numerical drift. Twenty-four healthy adults participated in a five-minute steady-state walking test to compare these algorithms. The sample-by-sample standard deviation of the three force-plate based algorithms from the motion-capture benchmark algorithm was evaluated. The algebraic technique provided less error than either of the two more common integration techniques (p<0.05). The results of this study support the viability of using only ground reaction forces for self-paced treadmills and also show that a simple algebraic model is preferred to integration approaches. The use of an algebraic estimation simplifies control implementation for self-paced treadmill applications and eliminates the need for event-based drift recalibration.

A Safe and Compliant Noncontact Interactive Approach for Wheeled Walking Aid Robot

Aiming at promptly and accurately detecting falls and drag-to gaits induced by asynchronous human-robot movement speed during assisted walking, a noncontact interactive approach with generality, compliance and safety is proposed in this paper, and is applied to a wheeled walking aid robot. Firstly, the structure and the functions of the wheeled walking aid robot, including gait rehabilitation robot (GRR) and walking aid robot (WAR) are illustrated, and the characteristic futures of falls and the drag-to gait are shown by experiments. To obtain gait information, a multichannel proximity sensor array is developed, and a two-dimensional gait information detection system is established by combining four proximity sensors groups which are installed in the robot chassis. Additionally, a node-iterative fuzzy Petri net algorithm for abnormal gait recognition is proposed by generating the network trigger mechanism using the fuzzy membership function. It integrates the walking intention direction vector by taking gait deviation, frequency, and torso angle as input parameters of the system. Finally, to improve the compliance of the robot during human-robot interaction, a PID_SC controller is designed by integrating the gait speed compensation, which enables the WAR to track human gait closely. Abnormal gait recognition and assisted walking experiments are carried out respectively. Experimental results show that the proposed algorithm can accurately identify abnormal gaits of different groups of users with different walking habits, and the recognition rate of abnormal gait reaches 91.2%. Results also show that the developed method can guarantee safety in human robot interaction because of user gate follow-up accuracy and compliant movements. The noncontact interactive approach can be applied to robots with similar structure for usage in walking assistance and gait rehabilitation.

Adaptive treadmill control can be manipulated to increase propulsive impulse while maintaining walking speed

Adaptive treadmills (ATM) designed to promote increased propulsion may be an effective tool for gait training since propulsion is often impaired post-stroke. Our lab developed a novel ATM controller that adjusts belt speed via real-time changes in step length, propulsive impulse, and position. This study modified the relative importance of propulsion to step length in the controller to determine the effect of increased propulsive feedback gain on measures of propulsion and walking speed. Twenty-two participants completed five trials at their self-selected speed, each with a unique ATM controller. Walking speed, peak AGRF and PGRF, and AGRF, PGRF, and net impulse were compared between the modifications using one-way repeated measures ANOVAs at a significance level of 0.05. Participants chose similar walking speeds across all conditions (all p > 0.2730). There were no significant differences in peak AGRF (p = 0.1956) or PGRF (p = 0.5159) between conditions. AGRF impulse significantly increased as the gain on the propulsive impulse term was increased relative to the gain on step length (p < 0.0001) while PGRF and net impulse were similar across all conditions (p = 0.5487). Increasing the propulsive impulse gain essentially alters the treadmill environment by providing a controlled amount of resistance to increases in propulsive forces. Our findings demonstrate that the ATM can be modified to promote increased propulsive impulse while maintaining a consistent walking speed. Since increasing propulsion is a common goal of post-stroke gait training, these ATM modifications may improve the efficacy of the ATM for gait 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.

Changes in Spatiotemporal Measures and Variability During User-Driven Treadmill, Fixed-Speed Treadmill, and Overground Walking in Young Adults: A Pilot Study

Walking is an integral indicator of human health commonly investigated while walking overground and with the use of a treadmill. Unlike fixed-speed treadmills, overground walking is dependent on the preferred walking speed under the individuals' control. Thus, user-driven treadmills may have the ability to better simulate the characteristics of overground walking. This pilot study is the first investigation to compare a user-driven treadmill, a fixed-speed treadmill, and overground walking to understand differences in variability and mean spatiotemporal measures across walking environments. Participants walked fastest overground compared to both fixed and user-driven treadmill conditions. However, gait cycle speed variability in the fixed-speed treadmill condition was significantly lower than the user-driven and overground conditions, with no significant differences present between overground and user-driven treadmill walking. The lack of differences in variability between the user-driven treadmill and overground walking may indicate that the user-driven treadmill can better simulate the variability of overground walking, potentially leading to more natural adaptation and motor control patterns of walking.

Improved cortical activity and reduced gait asymmetry during poststroke self-paced walking rehabilitation

Background

For patients with gait impairment due to neurological disorders, body weight-supported treadmill training (BWSTT) has been widely used for gait rehabilitation. On a conventional (passive) treadmill that runs at a constant speed, however, the level of patient engagement and cortical activity decreased compared with gait training on the ground. To increase the level of cognitive engagement and brain activity during gait rehabilitation, a self-paced (active) treadmill is introduced to allow patients to actively control walking speed, as with overground walking.

Methods

To validate the effects of self-paced treadmill walking on cortical activities, this paper presents a clinical test with stroke survivors. We hypothesized that cortical activities on the affected side of the brain would also increase during active walking because patients have to match the target walking speed with the affected lower limbs. Thus, asymmetric gait patterns such as limping or hobbling might also decrease during active walking.

Results

Although the clinical test was conducted in a short period, the patients showed higher cognitive engagement, improved brain activities assessed by electroencephalography (EEG), and decreased gait asymmetry with the self-paced treadmill. As expected, increases in the spectral power of the low γ and β bands in the prefrontal cortex (PFC), premotor cortex (PMC), and supramarginal gyrus (SG) were found, which are possibly related to processing sensory data and planning voluntary movements. In addition, these changes in cortical activities were also found with the affected lower limbs during the swing phase. Since our treadmill controller tracked the swing speed of the leg to control walking speed, such results imply that subjects made substantial effort to control their affected legs in the swing phase to match the target walking speed.

Conclusions

The patients also showed reduced gait asymmetry patterns. Based on the results, the self-paced gait training system has the potential to train the symmetric gait and to promote the related cortical activities after stroke.

Trial registration Not applicable

Design and kinematic analysis of a novel rehabilitative robotic walking simulation device

This paper presents an original rehabilitative robotic walking simulation device. As a novel feature, it can duplicate the walking motion of the feet completely by including the motion of the metatarsophalangeal joints as well. It is also adjustable to different foot sizes and gait parameters such as speed, step length, and foot elevation. The presented device comprises two identical mechanisms that simulate the right and left feet. Each mechanism is designed as a planar parallel manipulator with three degrees of freedom and thus its platform (i.e. foot plate) can duplicate the sagittal-plane motion of a foot completely. A prototype of the device is already built, patented, and tested by several people, two of whom are physiotherapists. In the paper, the inverse and forward kinematic analyses of each parallel manipulator are also presented. The inverse kinematic analysis is carried out based on a typical gait cycle data of a healthy person gathered from the related literature. The results of the inverse kinematic analysis are then used as reference trajectory data in testing the device with different healthy people at different speeds.

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.

Mechanisms used to increase propulsive forces on a treadmill in older adults

Older adults typically demonstrate reductions in overground walking speeds and propulsive forces compared to young adults. These reductions in walking speeds are risk factors for negative health outcomes. Therefore, this study aimed to determine the effect of an adaptive speed treadmill controller on walking speed and propulsive forces in older adults, including the mechanisms and strategies underlying any change in propulsive force between conditions. Seventeen participants completed two treadmill conditions, one with a fixed comfortable walking speed and one with an adaptive speed controller. The adaptive speed treadmill controller utilized a set of inertial-force, gait parameters, and position-based controllers that respond to an instantaneous anterior inertial force. A biomechanical-based model previously developed for individuals post-stroke was implemented for older adults to determine the primary gait parameters that contributed to the change in propulsive forces when increasing speed. Participants walked at faster average speeds during the adaptive speed controller (1.20 m/s) compared to the fixed speed controller conditions (0.98 m/s); however, these speeds were not as fast as their overground speed (1.44 m/s). Although average trailing limb angle (TLA) (p < 0.001) and ankle moment (p = 0.020) increased when speed also increased between treadmill conditions, increasing TLA contributed more to the increased propulsive forces seen during faster treadmill speeds. Our findings show that older adults chose faster walking speeds and increased propulsive force when walking on an adaptive speed treadmill compared to a fixed speed treadmill, suggesting that an adaptive speed treadmill controller has the potential to be a beneficial alternative to current exercise interventions for older adults.

A comparison of variability and gait dynamics in spatiotemporal variables between different self-paced treadmill control modes

This study investigates the effects of treadmill control algorithms on spatiotemporal variables when walking on a self-paced (SP) treadmill. Ten healthy subjects walked at their preferred walking speed for 15 min under three different treadmill control modes. Stride time, stride length, and stride speed were measured using an inertial measurement unit. The mean, coefficient of variance, Poincaré descriptors, and gait dynamics were calculated for each parameter. The mean values of stride length and stride speed were significantly increased when the treadmill had a quick response speed to the user's walking behavior. The long-term variability of stride length and stride speed was significantly affected by the treadmill control algorithms. A reduced strength of long-range correlations of stride time and stride speed was found when walking on the SP treadmill with suppressed treadmill accelerations and small velocity variations. We suggest that the suppression of treadmill acceleration provides more adaptability and less constraint to the user during SP treadmill walking. Although further research is required, the present work provides a basis for interpreting the influence of treadmill control algorithms on human gait.

Using force data to self-pace an instrumented treadmill and measure self-selected walking speed

BACKGROUND

Self-selected speed is an important functional index of walking. A self-pacing controller that reliably matches walking speed without additional hardware can be useful for measuring self-selected speed in a treadmill-based laboratory.

METHODS

We adapted a previously proposed self-pacing controller for force-instrumented treadmills and validated its use for measuring self-selected speeds. We first evaluated the controller's estimation of subject speed and position from the force-plates by comparing it to those from motion capture data. We then compared five tests of self-selected speed. Ten healthy adults completed a standard 10-meter walk test, a 150-meter walk test, a commonly used manual treadmill speed selection test, a two-minute self-paced treadmill test, and a 150-meter self-paced treadmill test. In each case, subjects were instructed to walk at or select their comfortable speed. We also assessed the time taken for a trial and a survey on comfort and ease of choosing a speed in all the tests.

RESULTS

The self-pacing algorithm estimated subject speed and position accurately, with root mean square differences compared to motion capture of 0.023 m s -1 and 0.014 m, respectively. Self-selected speeds from both self-paced treadmill tests correlated well with those from the 10-meter walk test (R>0.93,p<1×10-13). Subjects walked slower on average in the self-paced treadmill tests (1.23±0.27 ms-1) than in the 10-meter walk test (1.32±0.18 ms-1) but the speed differences within subjects were consistent. These correlations and walking speeds are comparable to those from the manual treadmill speed selection test (R=0.89,p=3×10-11;1.18±0.24 ms-1). Comfort and ease of speed selection were similar in the self-paced tests and the manual speed selection test, but the self-paced tests required only about a third of the time to complete. Our results demonstrate that these self-paced treadmill tests can be a strong alternative to the commonly used manual treadmill speed selection test.

CONCLUSIONS

The self-paced force-instrumented treadmill well adapts to subject walking speed and reliably measures self-selected walking speeds. We provide the self-pacing software to facilitate use by gait researchers and clinicians.

Local Dynamic Stability of Self-Paced Treadmill Walking Versus Fixed-Speed Treadmill Walking

The purpose of this study was to assess the influence of gait stability induced by treadmill accelerations during self-paced treadmill walking (SPW). Local dynamic stability of three-dimensional (3D) upper body accelerations and hip angles were quantified. The results demonstrated that SPW was more unstable and had higher risk of falling than fixed-speed treadmill walking (FSW) under the impact of treadmill accelerations. The frequency domain analysis of treadmill speed indicated that intrastride treadmill speed variation was the dominating cause of the instability, and self-paced control strategies which can reduce the intrastride variation may achieve higher gait stability during SPW.

Behavioral Dynamics of Pedestrians Crossing between Two Moving Vehicles

This study examines the human behavioral dynamics of pedestrians crossing a street with vehicular traffic. To this end, an experiment was constructed in which human participants cross a road between two moving vehicles in a virtual reality setting. A mathematical model is developed in which the position is given by a simple function. The model is used to extract information on each crossing by performing root-mean-square deviation (RMSD) minimization of the function from the data. By isolating the parameter adjusted to gap features, we find that the subjects primarily changed the timing of the acceleration to adjust to changing gap conditions, rather than walking speed or duration of acceleration. Moreover, this parameter was also adjusted to the vehicle speed and vehicle type, even when the gap size and timing were not changed. The model is found to provide a description of gap affordance via a simple inequality of the fitting parameters. In addition, the model turns out to predict a constant bearing angle with the crossing point, which is also observed in the data. We thus conclude that our model provides a mathematical tool useful for modeling crossing behaviors and probing existing models. It may also provide insight into the source of traffic accidents.

Models for temporal-spatial parameters in walking with cadence ratio as the independent variable

Accurate models that describe temporal-spatial parameters are desirable in gait estimation and rehabilitation. This study aimed to explore simple but relatively accurate models to describe stride length (SL), speed (SP) and walk ratio (WR) at various cadences. Twenty-four able-bodied participants (16 in a test group and 8 in a validation group) walked at seven cadence ratios (CRs). The individual and group mean SL, SP and WR were studied. Suitable temporal-spatial model structures were proposed and used to approximate the individual SL, SP and WR at various CRs. After the temporal-spatial model structures were found to be feasible, the general temporal-spatial models were analysed using the test group mean SL, SP and WR. Accuracy was assessed using the validation group mean values. Individual approximation accuracies showed that the proposed model structure deduced from the linear SL model was suitable for WR approximation. The linear, deduced quadratic and power functions approximated the individual SL, SP and WR, respectively, with high accuracy. Based on the test group mean SL, SP and WR, the general temporal-spatial models were obtained and produced comparable approximation accuracies in the validation group. The general temporal-spatial models predicted well the individual gait parameters with similar individual errors for both groups. These temporal-spatial models clearly describe SL, SP and especially WR at various cadences. They provide accurate reference data for gait estimation and have potential to guide speed modulation in robot-assisted gait rehabilitation.

Graphical abstract

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.

Evaluating the effects of delivering integrated kinesthetic and tactile cues to individuals with unilateral hemiparetic stroke during overground walking

BACKGROUND

Integration of kinesthetic and tactile cues for application to post-stroke gait rehabilitation is a novel concept which needs to be explored. The combined provision of haptic cues may result in collective improvement of gait parameters such as symmetry, balance and muscle activation patterns. Our proposed integrated cue system can offer a cost-effective and voluntary gait training experience for rehabilitation of subjects with unilateral hemiparetic stroke.

METHODS

Ten post-stroke ambulatory subjects participated in a 10 m walking trial while utilizing the haptic cues (either alone or integrated application), at their preferred and increased gait speeds. In the system a haptic cane device (HCD) provided kinesthetic perception and a vibrotactile feedback device (VFD) provided tactile cue on the paretic leg for gait modification. Balance, gait symmetry and muscle activity were analyzed to identify the benefits of utilizing the proposed system.

RESULTS

When using kinesthetic cues, either alone or integrated with a tactile cue, an increase in the percentage of non-paretic peak activity in the paretic muscles was observed at the preferred gait speed (vastus medialis obliquus: p <  0.001, partial eta squared (η2) = 0.954; semitendinosus p <  0.001, partial η2 = 0.793) and increased gait speeds (vastus medialis obliquus: p <  0.001, partial η2 = 0.881; semitendinosus p = 0.028, partial η2 = 0.399). While using HCD and VFD (individual and integrated applications), subjects could walk at their preferred and increased gait speeds without disrupting trunk balance in the mediolateral direction. The temporal stance symmetry ratio was improved when using tactile cues, either alone or integrated with a kinesthetic cue, at their preferred gait speed (p <  0.001, partial η2 = 0.702).

CONCLUSIONS

When combining haptic cues, the subjects walked at their preferred gait speed with increased temporal stance symmetry and paretic muscle activity affecting their balance. Similar improvements were observed at higher gait speeds. The efficacy of the proposed system is influenced by gait speed. Improvements were observed at a 20% increased gait speed, whereas, a plateau effect was observed at a 40% increased gait speed. These results imply that integration of haptic cues may benefit post-stroke gait rehabilitation by inducing simultaneous improvements in gait symmetry and muscle activity.

An evaluation of measurement systems estimating gait speed during a loaded military march over graded terrain

This study aimed to evaluate the accuracy of three measurement systems estimating gait speed during a loaded military march over graded terrain. Systems developed by the Swiss and Netherlands Armed Forces and a commercial wrist-based device were evaluated in comparison to a Global Positioning System. The first part of the paper focuses on the development of the Dutch system, where speed is estimated from a chest worn accelerometer and body measurements. For this validation study 36 subjects were walking or running 13 laps of 200 m at different speeds. Results showed that walking and running speed can be estimated with a R²_adj of 0.968 and 0.740, respectively. In the second part of this paper, data from 64 soldiers performing a 35 km march were used to evaluate the accuracy of three measurement systems in estimating speed. Data showed that estimating gait speed with a single accelerometer can be accurate for military activity, even without prior individual calibration measurements. However, predictions should be corrected for confounders such as body size and shoe type to be accurate. Both, downhill and uphill walking led to changes in gait characteristics and to an overestimation of speed by up to 10%. Correcting for slope or gradient using altimetry in future algorithms/experiments could improve the estimation of gait speed.

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.

Identifying the effects of using integrated haptic feedback for gait rehabilitation of stroke patients

This paper evaluates the prospects of using a novel Integrated Haptic Feedback (IHF) system. IHF can provide over-ground gait training regimens for post-stroke ambulatory subjects. IHF system combines the use of a portable cane for kinesthetic feedback and a wearable vibrotactor array for tactile feedback. Continuous somatosensory input is aiforded to the users at the handle of cane; it serves the purpose of balance assurance at higher gait speeds. Besides, restricted use of upper limb for weight-bearing inspires the users to involve the paretic lower limbs more actively. Furthermore, tactile feedback contributes in enhancing the gait symmetry through afferent signal of vibration. Six post-stroke ambulatory individuals participated in walking trials to identity the effects of IHF system. Results indicate that while walking faster patients' body sway was not disturbed. Statistically significant increase was observed in temporal stance symmetry (p-value=0.02) and in paretic muscle (vastus medialis obliquus and semitendinosus) activation during stance phase (p-value<0.01). The IHF system can be a valuable tool to assist physical therapist in gait rehabilitation of post-stroke individuals.

A method for automated control of belt velocity changes with an instrumented treadmill

Increased practice difficulty during asymmetrical split-belt treadmill rehabilitation has been shown to improve gait outcomes during retention and transfer tests. However, research in this area has been limited by manual treadmill operation. In the case of variable practice, which requires stride-by-stride changes to treadmill belt velocities, the treadmill control must be automated. This paper presents a method for automation of asymmetrical split-belt treadmill walking, and evaluates how well this method performs with regards to timing of gait events. One participant walked asymmetrically for 100 strides, where the non-dominant limb was driven at their self-selected walking speed, while the other limb was driven randomly on a stride-by-stride basis. In the control loop, the key factors to insure that the treadmill belt had accelerated to its new velocity safely during the swing phase were the sampling rate of the A/D converter, processing time within the controller software, and acceleration of the treadmill belt. The combination of these three factors resulted in a total control loop time during each swing phase that satisfied these requirements with a factor of safety that was greater than 4. Further, a polynomial fit indicated that belt acceleration was the largest contributor to changes in this total time. This approach appears to be safe and reliable for stride-by-stride adjustment of treadmill belt speed, making it suitable for future asymmetrical split-belt walking studies. Further, it can be incorporated into virtual reality rehabilitation paradigms that utilize split-belt treadmill walking.

Commercial Motion Sensor Based Low-Cost and Convenient Interactive Treadmill

Interactive treadmills were developed to improve the simulation of overground walking when compared to conventional treadmills. However, currently available interactive treadmills are expensive and inconvenient, which limits their use. We propose a low-cost and convenient version of the interactive treadmill that does not require expensive equipment and a complicated setup. As a substitute for high-cost sensors, such as motion capture systems, a low-cost motion sensor was used to recognize the subject’s intention for speed changing. Moreover, the sensor enables the subject to make a convenient and safe stop using gesture recognition. For further cost reduction, the novel interactive treadmill was based on an inexpensive treadmill platform and a novel high-level speed control scheme was applied to maximize performance for simulating overground walking. Pilot tests with ten healthy subjects were conducted and results demonstrated that the proposed treadmill achieves similar performance to a typical, costly, interactive treadmill that contains a motion capture system and an instrumented treadmill, while providing a convenient and safe method for stopping.

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.

Recent developments in computer assisted rehabilitation environments

Computer Assisted Rehabilitation Environment (CAREN) is a system that integrates a training platform (motion base), a virtual environment, a sensor system (motion capture) and D-flow software. It is useful for both diagnostic and therapeutic use. The human gait pattern can be impaired due to disease, trauma or natural decline. Gait analysis is a useful tool to identify impaired gait patterns. Traditional gait analysis is a very time consuming process and therefore only used in exceptional cases. With new systems a quick and extensive analysis is possible and provides useful tools for therapeutic purposes. The range of systems will be described in this paper, highlighting both their diagnostic use and the therapeutic possibilities. Because wounded warriors often have an impaired gait due to amputations or other extremity trauma, these systems are very useful for military rehabilitative efforts. Additionally, the virtual reality environment creates a very challenging situation for the patient, enhancing their rehabilitation experience. For that reason several Armed Forces have these systems already in use. The most recent experiences will be discussed; including new developments both in the extension of the range of systems and the improvement and adaptation of the software. A new and promising development, the use of CAREN in a special application for patients with post-traumatic stress disorder (PTSD), will also be reviewed.