A Feedback-Controlled Interface for Treadmill Locomotion in Virtual Environments

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.

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.

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.

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.

A new method for self-paced peak performance testing on a treadmill

PURPOSE

Self-paced maximal testing methods may be able to exploit central mediation of function-limiting fatigue and therefore have potential to generate more valid estimates of peak oxygen uptake. The aim of this study was to investigate the feasibility of a new method for self-paced peak performance testing on treadmills and to compare peak and submaximal performance outcomes with those obtained using a non-self-paced ('computer-paced') method employing predetermined speed and slope profiles.

METHODS

The proposed self-paced method is based upon automatic subject positioning using feedback control together with an exercise intensity which is driven by a predetermined, individualized work-rate ramp.

RESULTS

Peak oxygen uptake was not significantly different for the computer-paced (CP) versus self-paced (SP) protocols: 4·38 ± 0·48 versus 4·34 ± 0·46 ml min^-1 , P = 0·42. Likewise, there were no significant differences in the other peak and submaximal cardiopulmonary parameters, viz. peak heart rate, peak respiratory exchange ratio and the first and second ventilatory thresholds. Ramp duration for CP was longer than for SP: 494·5 ± 71·1 versus 371·3 ± 86·0 s, P = 0·00072. Concomitantly, the peak rate of work done against gravity was higher for CP: 264·8 ± 40·8 versus 203·8 ± 53·4 W, P = 0·0021.

CONCLUSIONS

The self-paced approach was found to be feasible for estimation of the principal performance outcomes: the method was technically implementable, it was acceptable to the subjects and it showed good responsiveness. Further investigation of the self-paced method, with adjustment of the target ramp-phase duration or modification of the work-rate calculation equations, is warranted.

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.

Kinesthetic Force Feedback and Belt Control for the Treadport Locomotion Interface

This paper describes an improved control system for the Treadport immersive locomotion interface, with results that generalize to any treadmill that utilizes an actuated tether to enable self-selected walking speed. A new belt controller is implemented to regulate the user's position; when combined with the user's own volition, this controller also enables the user to naturally self-select their walking speed as they would when walking over ground. A new kinesthetic-force-feedback controller is designed for the tether that applies forces to the user's torso. This new controller is derived based on maintaining the user's sense of balance during belt acceleration, rather than by rendering an inertial force as was done in our prior work. Based on the results of a human-subjects study, the improvements in both controllers significantly contribute to an improved perception of realistic walking on the Treadport. The improved control system uses intuitive dynamic-system and anatomical parameters and requires no ad hoc gain tuning. The control system simply requires three measurements to be made for a given user: the user's mass, the user's height, and the height of the tether attachment point on the user's torso.

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.

Self-paced versus fixed speed treadmill walking

Instrumented treadmills are increasingly used in gait research, although the imposed walking speed is suggested to affect gait performance. A feedback-controlled treadmill that allows subjects to walk at their preferred speed, i.e. functioning in a self-paced (SP) mode, might be an attractive alternative, but could disturb gait through accelerations of the belt. We compared SP with fixed speed (FS) treadmill walking, and also considered various feedback modes. Nineteen healthy subjects walked on a dual-belt instrumented treadmill. Spatio-temporal, kinematic and kinetic gait parameters were derived from both the average stride patterns and stride-to-stride variability. For 15 out of 70 parameters significant differences were found between SP and FS. These differences were smaller than 1cm, 1°, 0.2 Nm and 0.2 W/kg for respectively stride length and width, joint kinematics, moments and powers. Since this is well within the normal stride variability, these differences were not considered to be clinically relevant, indicating that SP walking is not notably affected by belt accelerations. The long-term components of walking speed variability increased during SP walking (43%, p<0.01), suggesting that SP allows for more natural stride variability. Differences between SP feedback modes were predominantly found in the timescales of walking speed variability, while the gait pattern was similar between modes. Overall, the lack of clinically significant differences in gait pattern suggests that SP walking is a suitable alternative to fixed speed treadmill walking in gait analysis.

A user-driven treadmill control scheme for simulating overground locomotion

Treadmill-based locomotor training should simulate overground walking as closely as possible for optimal skill transfer. The constant speed of a standard treadmill encourages automaticity rather than engagement and fails to simulate the variable speeds encountered during real-world walking. To address this limitation, this paper proposes a user-driven treadmill velocity control scheme that allows the user to experience natural fluctuations in walking velocity with minimal unwanted inertial force due to acceleration/deceleration of the treadmill belt. A smart estimation limiter in the scheme effectively attenuates the inertial force during velocity changes. The proposed scheme requires measurement of pelvic and swing foot motions, and is developed for a treadmill of typical belt length (1.5 m). The proposed scheme is quantitatively evaluated here with four healthy subjects by comparing it with the most advanced control scheme identified in the literature.

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

Background

Virtual reality (VR) technology along with treadmill training (TT) can effectively provide goal-oriented practice and promote improved motor learning in patients with neurological disorders. Moreover, the VR + TT scheme may enhance cognitive engagement for more effective gait rehabilitation and greater transfer to over ground walking. For this purpose, we developed an individualized treadmill controller with a novel speed estimation scheme using swing foot velocity, which can enable user-driven treadmill walking (UDW) to more closely simulate over ground walking (OGW) during treadmill training. OGW involves a cyclic acceleration-deceleration profile of pelvic velocity that contrasts with typical treadmill-driven walking (TDW), which constrains a person to walk at a preset constant speed. In this study, we investigated the effects of the proposed speed adaptation controller by analyzing the gait kinematics of UDW and TDW, which were compared to those of OGW at three pre-determined velocities.

Methods

Ten healthy subjects were asked to walk in each mode (TDW, UDW, and OGW) at three pre-determined speeds (0.5 m/s, 1.0 m/s, and 1.5 m/s) with real time feedback provided through visual displays. Temporal-spatial gait data and 3D pelvic kinematics were analyzed and comparisons were made between UDW on a treadmill, TDW, and OGW.

Results

The observed step length, cadence, and walk ratio defined as the ratio of stride length to cadence were not significantly different between UDW and TDW. Additionally, the average magnitude of pelvic acceleration peak values along the anterior-posterior direction for each step and the associated standard deviations (variability) were not significantly different between the two modalities. The differences between OGW and UDW and TDW were mainly in swing time and cadence, as have been reported previously. Also, step lengths between OGW and TDW were different for 0.5 m/s and 1.5 m/s gait velocities, and walk ratio between OGS and UDW was different for 1.0 m/s gait velocities.

Conclusions

Our treadmill control scheme implements similar gait biomechanics of TDW, which has been used for repetitive gait training in a small and constrained space as well as controlled and safe environments. These results reveal that users can walk as stably during UDW as TDW and employ similar strategies to maintain walking speed in both UDW and TDW. Furthermore, since UDW can allow a user to actively participate in the virtual reality (VR) applications with variable walking velocity, it can induce more cognitive activities during the training with VR, which may enhance motor learning effects.

Development of a VR-based treadmill control interface for gait assessment of patients with Parkinson's disease

Freezing of gait (FOG) is a commonly observed phenomenon in Parkinson's disease, but its causes and mechanisms are not fully understood. This paper presents the development of a virtual reality (VR)-based body-weight supported treadmill interface (BWSTI) designed and applied to investigate FOG. The BWSTI provides a safe and controlled walking platform which allows investigators to assess gait impairments under various conditions that simulate real life. In order to be able to evoke FOG, our BWSTI employed a novel speed adaptation controller, which allows patients to drive the treadmill speed. Our interface responsively follows the subject's intention of changing walking speed by the combined use of feedback and feedforward controllers. To provide realistic visual stimuli, a three dimensional VR system is interfaced with the speed adaptation controller and synchronously displays realistic visual cues. The VR-based BWSTI was tested with three patients with PD who are known to have FOG. Visual stimuli that might cause FOG were shown to them while the speed adaptation controller adjusted treadmill speed to follow the subjects' intention. Two of the three subjects showed FOG during the treadmill walking.

Fast visual prediction and slow optimization of preferred walking speed

People prefer walking speeds that minimize energetic cost. This may be accomplished by directly sensing metabolic rate and adapting gait to minimize it, but only slowly due to the compounded effects of sensing delays and iterative convergence. Visual and other sensory information is available more rapidly and could help predict which gait changes reduce energetic cost, but only approximately because it relies on prior experience and an indirect means to achieve economy. We used virtual reality to manipulate visually presented speed while 10 healthy subjects freely walked on a self-paced treadmill to test whether the nervous system beneficially combines these two mechanisms. Rather than manipulating the speed of visual flow directly, we coupled it to the walking speed selected by the subject and then manipulated the ratio between these two speeds. We then quantified the dynamics of walking speed adjustments in response to perturbations of the visual speed. For step changes in visual speed, subjects responded with rapid speed adjustments (lasting <2 s) and in a direction opposite to the perturbation and consistent with returning the visually presented speed toward their preferred walking speed, when visual speed was suddenly twice (one-half) the walking speed, subjects decreased (increased) their speed. Subjects did not maintain the new speed but instead gradually returned toward the speed preferred before the perturbation (lasting >300 s). The timing and direction of these responses strongly indicate that a rapid predictive process informed by visual feedback helps select preferred speed, perhaps to complement a slower optimization process that seeks to minimize energetic cost.