Foot contact forces can be used to personalize a wearable robot during human walking.
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ABSTRACT:
SUBMITTER: Jacobson M
PROVIDER: S-EPMC9243054 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Handholding can naturally occur between two walkers. When people walk side-by-side, either with or without hand contact, they often synchronize their steps. However, despite the importance of haptic interaction in general and the natural use of hand contact between humans during walking, few studies have investigated forces arising from physical interactions. Eight pairs of adult subjects participated in this study. They walked on side-by-side treadmills at 4 km/h independently and with hand contact. Only hand contact-related sensory information was available for unintentional synchronization, while visual and auditory communication was obstructed. Subjects walked at their natural cadences or following a metronome. Limb kinematics, hand contact 3D interaction forces and EMG activity of 12 upper limb muscles were recorded. Overall, unintentional step frequency locking was observed during about 40% of time in 88% of pairs walking with hand contact. On average, the amplitude of contact arm oscillations decreased while the contralateral (free) arm oscillated in the same way as during normal walking. Interestingly, EMG activity of the shoulder muscles of the contact arm did not decrease, and their synergistic pattern remained similar. The amplitude of interaction forces and of trunk oscillations was similar for synchronized and non-synchronized steps, though the synchronized steps were characterized by significantly more regular orientations of interaction forces. Our results further support the notion that gait synchronization during natural walking is common, and that it may occur through interaction forces. Conservation of the proximal muscle activity of the contact (not oscillating) arm is consistent with neural coupling between cervical and lumbosacral pattern generation circuitries ("quadrupedal" arm-leg coordination) during human gait. Overall, the findings suggest that individuals might integrate force interaction cues to communicate and coordinate steps during walking.
| S-EPMC5850283 | biostudies-literature
Project description:BACKGROUND:A robotic exoskeleton device is an intelligent system designed to improve gait performance and quality of life for the wearer. Robotic technology has developed rapidly in recent years, and several robot-assisted gait devices were developed to enhance gait function and activities of daily living in elderly adults and patients with gait disorders. In this study, we investigated the effects of the Gait-enhancing Mechatronic System (GEMS), a new wearable robotic hip-assist device developed by Samsung Electronics Co, Ltd., Korea, on gait performance and foot pressure distribution in elderly adults. METHODS:Thirty elderly adults who had no neurological or musculoskeletal abnormalities affecting gait participated in this study. A three-dimensional (3D) motion capture system, surface electromyography and the F-Scan system were used to collect data on spatiotemporal gait parameters, muscle activity and foot pressure distribution under three conditions: free gait without robot assistance (FG), robot-assisted gait with zero torque (RAG-Z) and robot-assisted gait (RAG). RESULTS:We found increased gait speed, cadence, stride length and single support time in the RAG condition. Reduced rectus femoris and medial gastrocnemius muscle activity throughout the terminal stance phase and reduced effort of the medial gastrocnemius muscle throughout the pre-swing phase were also observed in the RAG condition. In addition, walking with the assistance of GEMS resulted in a significant increase in foot pressure distribution, specifically in maximum force and peak pressure of the total foot, medial masks, anterior masks and posterior masks. CONCLUSION:The results of the present study reveal that GEMS may present an alternative way of restoring age-related changes in gait such as gait instability with muscle weakness, reduced step force and lower foot pressure in elderly adults. In addition, GEMS improved gait performance by improving push-off power and walking speed and reducing muscle activity in the lower extremities. TRIAL REGISTRATION:NCT02843828 .
| S-EPMC5706419 | biostudies-literature
Project description:Obese children exhibit altered gait mechanics compared to healthy-weight children and have an increased prevalence of hip pain and pathology. This study sought to determine the relationships between body mass and compressive and shear hip joint contact forces during walking. Kinematic and kinetic data were collected during treadmill walking at 1ms(-1) in 10 obese and 10 healthy-weight 8-12 year-olds. We estimated body composition, segment masses, lower-extremity alignment, and femoral neck angle via radiographic images, created personalized musculoskeletal models in OpenSim, and computed muscle forces and hip joint contact forces. Hip extension at mid-stance was 9° less, on average, in the obese children (p<0.001). Hip abduction, knee flexion, and body-weight normalized peak hip moments were similar between groups. Normalized to body-weight, peak contact forces were similar at the first peak and slightly lower at the second peak between the obese and healthy-weight participants. Total body mass explained a greater proportion of contact force variance compared to lean body mass in the compressive (r(2)=0.89) and vertical shear (perpendicular to the physis acting superior-to-inferior) (r(2)=0.84) directions; lean body mass explained a greater proportion in the posterior shear direction (r(2)=0.54). Stance-average contact forces in the compressive and vertical shear directions increased by 41N and 48N, respectively, for every kilogram of body mass. Age explained less than 27% of the hip loading variance. No effect of sex was found. The proportionality between hip loads and body-weight may be implicated in an obese child?s increased risk of hip pain and pathology.
| S-EPMC4885751 | biostudies-literature
Project description:The adjunctive use of biofeedback systems with exoskeletons may accelerate post-stroke gait rehabilitation. Wearable patient-oriented human-robot interaction-based biofeedback is proposed to improve patient-exoskeleton compliance regarding the interaction torque's direction (joint motion strategy) and magnitude (user participation strategy) through auditory and vibrotactile cues during assisted gait training, respectively. Parallel physiotherapist-oriented strategies are also proposed such that physiotherapists can follow in real-time a patient's motor performance towards effective involvement during training. A preliminary pre-post controlled study was conducted with eight healthy participants to conclude about the biofeedback's efficacy during gait training driven by an ankle-foot exoskeleton and guided by a technical person. For the study group, performance related to the interaction torque's direction increased during (p-value = 0.07) and after (p-value = 0.07) joint motion training. Further, the performance regarding the interaction torque's magnitude significantly increased during (p-value = 0.03) and after (p-value = 68.59×10-3) user participation training. The experimental group and a technical person reported promising usability of the biofeedback and highlighted the importance of the timely cues from physiotherapist-oriented strategies. Less significant improvements in patient-exoskeleton compliance were observed in the control group. The overall findings suggest that the proposed biofeedback was able to improve the participant-exoskeleton compliance by enhancing human-robot interaction; thus, it may be a powerful tool to accelerate post-stroke ankle-foot deformity recovery.
| S-EPMC7589198 | biostudies-literature
Project description:Humans employ a high degree of redundancy in joint actuation, with different combinations of muscle and tendon action providing the same net joint torque. Both the resolution of these redundancies and the energetics of such systems depend on the dynamic properties of muscles and tendons, particularly their force-length relations. Current walking models that use stock parameters when simulating muscle-tendon dynamics tend to significantly overestimate metabolic consumption, perhaps because they do not adequately consider the role of elasticity. As an alternative, we posit that the muscle-tendon morphology of the human leg has evolved to maximize the metabolic efficiency of walking at self-selected speed. We use a data-driven approach to evaluate this hypothesis, utilizing kinematic, kinetic, electromyographic (EMG), and metabolic data taken from five participants walking at self-selected speed. The kinematic and kinetic data are used to estimate muscle-tendon lengths, muscle moment arms, and joint moments while the EMG data are used to estimate muscle activations. For each subject we perform an optimization using prescribed skeletal kinematics, varying the parameters that govern the force-length curve of each tendon as well as the strength and optimal fiber length of each muscle while seeking to simultaneously minimize metabolic cost and maximize agreement with the estimated joint moments. We find that the metabolic cost of transport (MCOT) values of our participants may be correctly matched (on average 0.36±0.02 predicted, 0.35±0.02 measured) with acceptable joint torque fidelity through application of a single constraint to the muscle metabolic budget. The associated optimal muscle-tendon parameter sets allow us to estimate the forces and states of individual muscles, resolving redundancies in joint actuation and lending insight into the potential roles and control objectives of the muscles of the leg throughout the gait cycle.
| S-EPMC4866735 | biostudies-literature
Project description:When humans walk on slopes, the ankle, knee, and hip joints modulate their mechanical work to accommodate the mechanical demands. Yet, it is unclear if the foot modulates its work output during uphill and downhill walking. Therefore, we quantified the mechanical work performed by the foot and its subsections of twelve adults walked on five randomized slopes (-10°, -5°, 0°, +5°, +10°). We estimated the work of distal-to-hindfoot and distal-to-forefoot structures using unified deformable segment analysis and the work of the midtarsal, ankle, knee, and hip joints using a six-degree-of-freedom model. Further, using a geometric model, we estimated the length of the plantar structures crossing the longitudinal arch while accounting for the first metatarsophalangeal wrapping length. We hypothesized that compared to level walking, downhill walking would increase negative and net-negative work magnitude, particularly at the early stance phase, and uphill walking would increase the positive work, particularly at the mid-to-late stance phase. We found that downhill walking increased the magnitude of the foot's negative and net-negative work, especially during early stance, highlighting its capacity to absorb impacts when locomotion demands excessive energy dissipation. Notably, the foot maintained its net dissipative behavior between slopes; however, the ankle, knee, and hip shifted from net energy dissipation to net energy generation when changing from downhill to uphill. Such results indicate that humans rely more on joints proximal to the foot to modulate the body's total mechanical energy. Uphill walking increased midtarsal's positive and distal-to-forefoot negative work in near-equal amounts. That coincided with the prolonged lengthening and delayed shortening of the plantar structures, resembling a spring-like function that possibly assists the energetic demands of locomotion during mid-to-late stance. These results broaden our understanding of the foot's mechanical function relative to the leg's joints and could inspire the design of wearable assistive devices that improve walking capacity.
| S-EPMC10495022 | biostudies-literature
Project description:Though walking impairments are prevalent in society, clinical treatments are often ineffective at restoring lost function. For this reason, researchers have begun to explore the use of patient-specific computational walking models to develop more effective treatments. However, the accuracy with which models can predict internal body forces in muscles and across joints depends on how well relevant model parameter values can be calibrated for the patient. This study investigated how knowledge of internal knee contact forces affects calibration of neuromusculoskeletal model parameter values and subsequent prediction of internal knee contact and leg muscle forces during walking. Model calibration was performed using a novel two-level optimization procedure applied to six normal walking trials from the Fourth Grand Challenge Competition to Predict In Vivo Knee Loads. The outer-level optimization adjusted time-invariant model parameter values to minimize passive muscle forces, reserve actuator moments, and model parameter value changes with (Approach A) and without (Approach B) tracking of experimental knee contact forces. Using the current guess for model parameter values but no knee contact force information, the inner-level optimization predicted time-varying muscle activations that were close to experimental muscle synergy patterns and consistent with the experimental inverse dynamic loads (both approaches). For all the six gait trials, Approach A predicted knee contact forces with high accuracy for both compartments (average correlation coefficient r = 0.99 and root mean square error (RMSE) = 52.6 N medial; average r = 0.95 and RMSE = 56.6 N lateral). In contrast, Approach B overpredicted contact force magnitude for both compartments (average RMSE = 323 N medial and 348 N lateral) and poorly matched contact force shape for the lateral compartment (average r = 0.90 medial and -0.10 lateral). Approach B had statistically higher lateral muscle forces and lateral optimal muscle fiber lengths but lower medial, central, and lateral normalized muscle fiber lengths compared to Approach A. These findings suggest that poorly calibrated model parameter values may be a major factor limiting the ability of neuromusculoskeletal models to predict knee contact and leg muscle forces accurately for walking.
| S-EPMC4913205 | biostudies-literature
Project description:In order to determine optimal training parameters for robot-assisted treadmill walking, it is essential to understand how a robotic device interacts with its wearer, and thus, how parameter settings of the device affect locomotor control. The aim of this study was to assess the effect of different levels of guidance force during robot-assisted treadmill walking on cortical activity. Eighteen healthy subjects walked at 2 km.h-1 on a treadmill with and without assistance of the Lokomat robotic gait orthosis. Event-related spectral perturbations and changes in power spectral density were investigated during unassisted treadmill walking as well as during robot-assisted treadmill walking at 30%, 60% and 100% guidance force (with 0% body weight support). Clustering of independent components revealed three clusters of activity in the sensorimotor cortex during treadmill walking and robot-assisted treadmill walking in healthy subjects. These clusters demonstrated gait-related spectral modulations in the mu, beta and low gamma bands over the sensorimotor cortex related to specific phases of the gait cycle. Moreover, mu and beta rhythms were suppressed in the right primary sensory cortex during treadmill walking compared to robot-assisted treadmill walking with 100% guidance force, indicating significantly larger involvement of the sensorimotor area during treadmill walking compared to robot-assisted treadmill walking. Only marginal differences in the spectral power of the mu, beta and low gamma bands could be identified between robot-assisted treadmill walking with different levels of guidance force. From these results it can be concluded that a high level of guidance force (i.e., 100% guidance force) and thus a less active participation during locomotion should be avoided during robot-assisted treadmill walking. This will optimize the involvement of the sensorimotor cortex which is known to be crucial for motor learning.
| S-EPMC4617721 | biostudies-literature
Project description:Human-like features, like toe-off, heel-strike can enhance the performance of bipedal robots. However, few studies have considered the anthropomorphism of walking planning. Fewer studies have achieved their toe-off, heel-strike gait planning framework in a child-sized humanoid robot platform. This paper presents a human-like walking control framework based on the Divergent Component of Motion (DCM) com planning method that enables a child-sized humanoid robot to walk with a humanoid pattern with a speed of 0.6 s per step a strike of 30 cm. The control framework consists of three parts: the human-like gait generation of the center of mass (CoM) and swings foot trajectory, the dynamic replan in phase switch and the upper body stabilization controller. The dynamic replanning of the CoM and foot trajectory can efficiently decrease the vibration in the step-phase switch. The up-body stabilization controller can reduce the up-body swing in walking and increase the robot's stability while walking. The robot uses a mems-based inertial measurement unit (IMU) and joint position encoders to estimate the current state of the robot and use force-sensitive resistors (FSR) on the robot foot to identify the actual step phase of the robot. None of these solutions is high-cost or difficult to integrate with a child-size robot. Software simulations and walking experiments are using to verify the motion control algorithm. The effectiveness of the pattern generation and the controller can realize more human-like walking styles in a child-size robot are confirmed.
| S-EPMC9044359 | biostudies-literature
Project description:Bipedal walking while keeping the upper body upright is a complex task. One strategy to cope with this task is to direct the ground reaction forces toward a point above the centre of mass of the whole body, called virtual pivot point (VPP). This behaviour could be observed in various experimental studies for human and animal walking, but not for the humanoid robot LOLA. The question arose whether humans still show a VPP when walking like LOLA. For this purpose, ten participants imitated LOLA in speed, posture, and mass distribution (LOLA-like walking). It could be found that humans do not differ from LOLA in spatio-temporal parameters for the LOLA-like walking, in contrast to upright walking with preferred speed. Eight of the participants show a VPP in all conditions (R2 > 0.90 ± 0.09), while two participants had no VPP for LOLA-like walking (R2 < 0.52). In the latter case, the horizontal ground reaction forces are not balanced around zero in the single support phase, which is presumably the key variable for the absence of the VPP.
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