Assistive Torque Research Articles

Biomechanical requirements of meat cutting tasks: A pilot study quantifying tasks sustainability and assistance required at the wrist

The meat processing industry is particularly affected by distal upper limb musculoskeletal disorders. This pilot study aims at proposing a methodology able to quantify biomechanical requirements of meat cutting tasks at butchers’ dominant wrist and, when necessary, at estimating the assistance needed to reach sustainability. Six professional butchers repeatedly cut pieces of pork. Joint angles were recorded using a motion capture system, cutting forces using an instrumented knife. Sustainability was computed by the maximal acceptable effort method. Assistance requirements were computed for isolated stressful exertions and for overall work cycle sustainability. Five butchers exceeded the sustainability threshold for wrist flexion. Ulnar or radial deviation torques were excessive for 2 and 3 of them, respectively. Extension torques were sustainable. The peak assistive torque for isolated exertions was at most 1.1Nm, 1.6Nm and 1.1Nm, and the percentage of assistance for overall sustainability was at most 60%, 56% and 56% for wrist flexion, ulnar and radial deviation, respectively.

Reducing Knee Hyperextension With an Exoskeleton in Children and Adolescents With Genu Recurvatum: A Feasibility Study.

Genu recurvatum, or knee hyperextension, is a complex gait pattern with a variety of etiologies, and is often connected with knee weakness, lack of motor control, and spasticity. Because of the atypical forces placed on the soft tissues, early treatment or prevention of knee hyperextension may help prevent further degradation of the knee joint. In this study, we assessed the feasibility of a knee exoskeleton to mitigate hyperextension and increase swing range of motion in five children/adolescents who presented with unilateral genu recurvatum. Over the course of three visits, each participant practiced walking with the exoskeleton, which provided torque assistance during both stance and swing based on an impedance control law. In final validation trials, the exoskeleton was effective in reducing knee hyperextension (0.2 ± 4.7° average peak knee extension without exo to 9.9 ± 10.3° with exo) and improving swing range of motion by 14.0 ± 4.5° increase on average. However, while the exoskeleton was effective in normalizing the kinematics, it did not lead to improved spatio-temporal asymmetry measures. This work showcases a promising potential application of a robotic knee exoskeleton for improving the kinematic characteristics of genu recurvatum gait.

Servo-controlled Semi-rigid Exoskeleton Designed for the Human Knee

Musculoskeletal injuries are occurring more and more frequently, with one of the main causes being the increasing number of new patients who sustain knee structure injuries. Currently, exoskeletons that assist the knee joint are either fully rigid or soft systems, which induce the risk of misalignments due to the complicated nature of the kinematics of the knee joint or require additional anchors or mechanical parts that may cause discomfort or force unnecessary weight upon the user. In this paper, a semi-rigid exoskeleton principle is introduced. This exoskeleton addresses the concerns of both rigid and soft exoskeletons while performing the same benefits by establishing a pre-determined route for the tendon. This exoskeleton can provide up to 37.26Nm assistive torque to the knee joint. The system’s effectiveness was validated through a series of experiments which included testing its range of motion, total tensile force, and accuracy and safety of the pose detection system. The prototype had successful results, and the overall system is efficient, flexible, and easy to use. Future work will focus more on a customizable system in which the users can determine the amount of assistive torque force they need to be applied to their knee joint depending on their current physical ability.

Occupational arm-support and back-support exoskeletons elicit changes in reactive balance after slip-like and trip-like perturbations on a treadmill

The purpose of this study was to investigate the effects of arm- and back-support exoskeletons on reactive balance after slip-like and trip-like perturbations on a treadmill. Twenty-eight participants used two arm-support exoskeletons and two back-support exoskeletons with support (i.e., assistive joint torque) activated or deactivated. In each exoskeleton condition, as well in as a control without any exoskeleton, participants were exposed to 12 treadmill perturbations during upright standing. The exoskeletons did not significantly increase the probability of a failed recovery after the perturbations compared to wearing no exoskeleton, but did elicit effects on kinematic variables that suggested balance recovery was more challenging. Moreover, reactive balance differed when wearing back-support and arm-support exoskeletons, and when wearing an activated exoskeleton compared to a deactivated exoskeleton. Together, our results suggest these exoskeletons may increase the risk of slip- and trip-induced falls. The potential mechanisms of this increased risk are discussed and include the added mass and/or motion restrictions associated with wearing these exoskeletons. Our results do not support the assistive hip/back extension moment provided by back-support exoskeletons adversely affecting fall risk.

Dynamic assessment for low back-support exoskeletons during manual handling tasks.

Exoskeletons can protect users' lumbar spine and reduce the risk of low back injury during manual lifting tasks. Although many exoskeletons have been developed, their adoptability is limited by their task- and movement-specific effects on reducing burden. Many studies have evaluated the safety and effectiveness of an exoskeleton using the peak/mean values of biomechanical variables, whereas the performance of the exoskeleton at other time points of the movement has not been investigated in detail. A functional analysis, which presents discrete time-series data as continuous functions, makes it possible to highlight the features of the movement waveform and determine the difference in each variable at each time point. This study investigated an assessment method for exoskeletons based on functional ANOVA, which made it possible to quantify the differences in the biomechanical variables throughout the movement when using an exoskeleton. Additionally, we developed a method based on the interpolation technique to estimate the assistive torque of an exoskeleton. Ten men lifted a 10-kg box under symmetric and asymmetric conditions five times each. Lumbar load was significantly reduced during all phases (flexion, lifting, and laying) under both conditions. Additionally, reductions in kinematic variables were observed, indicating the exoskeleton's impact on motion restrictions. Moreover, the overlap F-ratio curves of the lumbar load and kinematic variables imply that exoskeletons reduce the lumbar load by restricting the kinematic variables. The results suggested that at smaller trunk angles (<25°), an exoskeleton neither significantly reduces the lumbar load nor restricts trunk movement. Our findings will help increasing exoskeleton safety and designing effective products for reducing lumbar injury risks.

A compact hydro-mechanical transmission solution to wheel loader propulsion system and its control strategy

Given the need for high efficiency to wheel loader powertrain, hydro-mechanical transmission is a promising solution to wheel loader propulsion system since it enables efficient engine operations owing to its continuously variable transmission function. The current hydro-mechanical transmission consists of planetary gear set and two hydrostatic units, making it bulky and complex in controls. This study proposes a simple and compact hydro-mechanical transmission solution to wheel loader powertrain. It improves vehicle acceleration performance by providing hydraulic torque assistance at low vehicle speed. The steady-state characteristics of the proposed hydro-mechanical transmission are analyzed, and the mathematical models of proposed wheel loader powertrain are constructed. An optimization strategy is developed as a reference for the design of an engine-speed based control strategy. The simulation results of the key components of proposed powertrain are analyzed. Furthermore, the engine-speed based control strategy is evaluated by the optimization strategy in different forms of the loading cycles. The results demonstrate the effectiveness of proposed wheel loader powertrain and its control strategy.

A novel dual power-driven electric power steering system for electric commercial vehicles

To solve the power limitation problem faced by the development of EPS system for commercial vehicles and achieve the high-performance steering, this article presents a novel dual power-driven electric power steering system (DPEPS) for commercial vehicles by using the open winding permanent magnet synchronous motor (OPMSM) fed by dual inverter with high and low DC voltage supplies. First, the two-level control strategy is introduced for the developed DPEPS system, where the upper control is designed to make the actual steering follow the expected steering performance as determined by the assistant torque curve and to generate the appropriate target current according to the vehicle speed and steering torque. And then the lower control consists of the synthetical space vector control scheme and dual PI control loop is used to execute commands from the upper control, which can make the motor execute the appropriate power supply method according to the steering torque and assist current. Finally, a co-simulation model is carried out for an electric bus, and based on which the proposed DPEPS system is validated.

Neuromusculoskeletal model-informed machine learning-based control of a knee exoskeleton with uncertainties quantification.

Research interest in exoskeleton assistance strategies that incorporate the user's torque capacity is growing rapidly. However, the predicted torque capacity from users often includes uncertainty from various sources, which can have a significant impact on the safety of the exoskeleton-user interface. To address this challenge, this paper proposes an adaptive control framework for a knee exoskeleton that uses muscle electromyography (EMG) signals and joint kinematics. The framework predicted the user's knee flexion/extension torque with confidence bounds to quantify the uncertainty based on a neuromusculoskeletal (NMS) solver-informed Bayesian Neural Network (NMS-BNN). The predicted torque, with a specified confidence level, controlled the assistive torque provided by the exoskeleton through a TCP/IP stream. The performance of the NMS-BNN model was also compared to that of the Gaussian process (NMS-GP) model. Our findings showed that both the NMS-BNN and NMS-GP models accurately predicted knee joint torque with low error, surpassing traditional NMS models. High uncertainties were observed at the beginning of each movement, and at terminal stance and terminal swing in self-selected speed walking in both NMS-BNN and NMS-GP models. The knee exoskeleton provided the desired assistive torque with a low error, although lower torque was observed during terminal stance of fast walking compared to self-selected walking speed. The framework developed in this study was able to predict knee flexion/extension torque with quantifiable uncertainty and to provide adaptive assistive torque to the user. This holds significant potential for the development of exoskeletons that provide assistance as needed, with a focus on the safety of the exoskeleton-user interface.

Adaptations in Gait Mechanics When Walking in an Ankle Exoskeleton

Exoskeletons are robotic, brace-like devices that can apply assistive torques to joints, supplementing biological torques. For example, ankle exoskeletons are often designed to assist during the push-off phase of walking to reduce energy expenditure. However, the mechanism by which these exoskeletons reduce metabolic costs is often unclear due to complex human-machine interactions. Here, our purpose was to determine what lower-limb gait kinematic, kinetic, and muscle activity changes underly metabolic cost reductions during ankle exoskeleton-assisted walking. We had healthy participants (n=6) perform two, 12-minute walking trials, one without assistive torques applied (Exo Off) and one with assistive torques applied (Exo On). Participants walked on a force plate instrumented treadmill (Bertec) and were instrumented with optical motion capture (Qualisys) to measure lower-limb gait kinematics and kinetics using Opensim, electromyography (Delsys) to measure the muscle activity of nine lower-limb muscles of the dominant limb, and indirect calorimetry (Cosmed) to measure metabolic energy expenditure (Figure 1A). We aggregated the motion capture, electromyography, and metabolic data for a final analysis using custom scripts (Matlab). We found that metabolic energy expenditure was reduced by 9.52  1.25% (p=0.011; Figure 1B). This, however, did not coincide with any changes in biological ankle angle, torque, or power. However, there was a trending reduction in peak soleus activity (p=0.052). Surprisingly, we did find a reduction in knee power (p=7.3x10-3; Figure 1C) and an accompanying decrease in semitendinosus activity (p=5.9x10-3). Despite the exoskeleton acting at the ankle joint, we found the clearest benefits at the knee joint—highlighting that complex, multi-joint adaptations may underly cost savings. We are continuing data collection to increase our statistical power and better understand the mechanisms that underly exoskeleton assistance.

Design and analysis of a passive exoskeleton with its hip joint energy-storage.

A novel passive hip exoskeleton has been designed and built with the aim of reducing metabolic consumption during walking by a passive way of storing the negative mechanical energy in the deceleration phase and releasing it in the acceleration phase. A ratchet spiral spring mechanism with a set of double stable switches is designed inside the exoskeleton for the above purpose. An analysis is conducted on the mechanism and the switching timing for the energy management to automatically store or release the energy according to the biomechanics of walking. In addition, a gravity-balance mechanism embedded inside the exoskeleton is designed as well to minimize the influence of the lower limb weight on muscle work. Human-exoskeleton interaction has been studied using the Opensim software, and simulation results demonstrated the effectiveness of the exoskeleton in reducing metabolic consumption during walking. An exoskeleton prototype has been built and tested with experiments measuring assistive torque and surface electromyography signal, confirming the effectiveness of the gravity-balance mechanism and energy-storage method, as well as the exoskeleton's actual assistive effect.

A Completely Portable and Concealable, Lightweight Assistive Exosuit for Upper Limbs.

Exosuits are a relatively new trend in wearable robotics to answer the flaws of their exoskeleton counterparts, but they remain impractical as the lack of rigidity in their frames makes the integration of crucial components into a single unit a challenge. While some simple solutions exist, almost all current research focuses on the output performance of exosuits rather than the needs of potential beneficiaries of this technology. To address this, a novel mechanism of complete portability for exosuits was developed and tested to improve exosuit practicality and adoption. Designed for elbow flexion, the device produced 12.21-13.66Nm of assistive torque and could be mostly concealed by the wearer's clothing without impacting performance. The proof-of-concept design proved successful and demonstrated many advantages over current portability methods, particularly in size and convenience, weighing only 1.7kg. This device provides the sense of normalcy crucial for a technology to seamlessly integrate into the daily lives of its end users. It is extendable and upgradeable with access to advanced materials and manufacturing methods.Clinical Relevance- Exoskeletons are currently the only marketed wearable robotic device for full limb support. This research is the foundation for a new series of exosuits that could drastically enhance the adoptability, accessibility, and versatility of exosuits in physical rehabilitation and general physical enhancement, becoming a superior alternative or addition.

Elbow-sideWINDER (Elbow-side Wearable INDustrial Ergonomic Robot): design, control, and validation of a novel elbow exoskeleton.

Musculoskeletal Disorders associated with the elbow are one of the most common forms of work-related injuries. Exoskeletons have been proposed as an approach to reduce and ideally eliminate these injuries; however, exoskeletons introduce their own problems, especially discomfort due to joint misalignment. The Elbow-sideWINDER with its associated control strategy is a novel elbow exoskeleton to assist elbow flexion/extension during occupational tasks. This study describes the exoskeleton showing how this can minimize discomfort caused by joint misalignment, maximize assistive performance, and provide increased robustness and reliability in real worksites. The proposed medium-level control strategy can provide effective assistive torque using three control units as follows: an arm kinematics estimator, a load estimator, and a friction compensator. The combined hardware/software system of the Elbow-sideWINDER is tested in load-lifting tasks (2 and 7 kg). This experiment focuses on the reduction in the activation level of the biceps brachii and triceps brachii in both arms and the change in the range of motion of the elbow during the task. It is shown that using the Elbow-sideWINDER, the biceps brachii, responsible for the elbow flexion, was significantly less activated (up to 38.8% at 2 kg and 25.7% at 7 kg, on average for both arms). For the triceps brachii, the muscle activation was reduced by up to 37.0% at 2 kg and 35.1% at 7 kg, on average for both arms. When wearing the exoskeleton, the range of motion of the elbow was reduced by up to 13.0° during the task, but it was within a safe range and could be compensated for by other joints such as the waist or knees. There are extremely encouraging results that provide good indicators and important clues for future improvement of the Elbow-sideWINDER and its control strategy.

A Wire-Driven Series Elastic Mechanism Based on Ultrasonic Motor for Walking Assistive System

In order to improve the elderly people’s quality of life, supporting their walking behaviors is a promising technology. Therefore, based on one ultrasonic motor, a wire-driven series elastic mechanism for walking assistive system is proposed and investigated in this research. In contrast to tradition, it innovatively utilizes an ultrasonic motor and a wire-driven series elastic mechanism to achieve superior system performances in aspects of simple structure, high torque/weight ratio, quiet operation, quick response, favorable electromagnetic compatibility, strong shock resistance, better safety, and accurately stable force control. The proposed device is mainly composed of an ultrasonic motor, a linear spring, a steel wire, four pulleys and one rotating part. To overcome the ultrasonic motor’s insufficient output torque, a steel wire and pulleys are smartly combined to directly magnify the torque instead of using a conventional gear reducer. Among the pulleys, there is one tailored pulley playing an important role to keep the reduction ratio as 4.5 constantly. Meanwhile, the prototype is manufactured and its actual performance is verified by experimental results. In a one-second operating cycle, it only takes 86 ms for this mechanism to output an assistive torque of 1.6 N·m. At this torque, the ultrasonic motor’s speed is around 4.1 rad/s. Moreover, experiments with different operation periods have been conducted for different application scenarios. This study provides a useful idea for the application of ultrasonic motor in walking assistance system.

Security-Based Resilient Triggered Output Feedback Lane Keeping Control for Human–Machine Cooperative Steering Intelligent Heavy Truck Under Denial-of-Service Attacks

This paper addresses dynamic authority allocation strategy and security-based resilient event triggered output feedback lane keeping control (LKC) problem for human-machine cooperative (HMC) steering intelligent heavy truck subject to non-periodic energy bounded denial-of-service (DoS) attacks. For authority allocation strategy of considered LKC system, designed practical and easily-to-implement cooperative allocation factor is adaptively adjusted by the correlation characteristics between buffered interested states for the first time. For derived fuzzy model of networked LKC system with time-varying cooperative allocation factor and path tracking velocity, a new security-based resilient event triggered output feedback control with communication scheme consisting of adaptive adjusted auxiliary variable and attack-induced random but bounded uncertainty is proposed to reduce communication burden when free of attacks and simultaneously release necessary data for stability maintenance at the cost of predefined allowable control performance degradation when attack-induced uncertainty less than its upper bound. Furthermore, sufficient conditions are derived for exponentially stability of considered LKC system with <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$H\infty $</tex-math></inline-formula> performance, gain matrices for controller and trigger are co-designed and obtained by solving certain matrix inequalities. Benefiting from saved communication resource and more sparse but necessary assistant torque commands under resilient event triggered communication scheme, as well as dynamic authority allocation strategy with adaptive cooperative allocation factor, the obtained results illustrating fewer driving conflict, less driver effort and higher resistant ability to attack-induced yaw instability demonstrate the effectiveness of the proposed control strategy.

Evaluation of a Fused Sonomyography and Electromyography-Based Control on a Cable-Driven Ankle Exoskeleton

This article presents an assist-as-needed (AAN) control framework for exoskeleton assistance based on human volitional effort prediction via a Hill-type neuromuscular model. A sequential processing algorithm-based multirate observer is applied to continuously estimate muscle activation levels by fusing surface electromyography (sEMG) and ultrasound (US) echogenicity signals from the ankle muscles. An adaptive impedance controller manipulates the exoskeleton's impedance for a more natural behavior by following a desired intrinsic impedance model. Two neural networks provide robustness to uncertainties in the overall ankle joint-exoskeleton model and the prediction error in the volitional ankle joint torque. A rigorous Lyapunov-based stability analysis proves that the AAN control framework achieves uniformly ultimately bounded tracking for the overall system. Experimental studies on five participants with no neurological disabilities walking on a treadmill validate the effectiveness of the designed ankle exoskeleton and the proposed AAN approach. Results illustrate that the AAN control approach with fused sEMG and US echogenicity signals maintained a higher human volitional effort prediction accuracy, less ankle joint trajectory tracking error, and less robotic assistance torque than the AAN approach with the sEMG-based volitional effort prediction alone. The findings support our hypotheses that the proposed controller increases human motion intent prediction accuracy, improves the exoskeleton's control performance, and boosts voluntary participation from human subjects. The new framework potentially paves a foundation for using multimodal biological signals to control rehabilitative or assistive robots.

Real-Time Gait Phase and Task Estimation for Controlling a Powered Ankle Exoskeleton on Extremely Uneven Terrain.

Positive biomechanical outcomes have been reported with lower-limb exoskeletons in laboratory settings, but these devices have difficulty delivering appropriate assistance in synchrony with human gait as the task or rate of phase progression change in real-world environments. This paper presents a controller for an ankle exoskeleton that uses a data-driven kinematic model to continuously estimate the phase, phase rate, stride length, and ground incline states during locomotion, which enables the real-time adaptation of torque assistance to match human torques observed in a multi-activity database of 10 able-bodied subjects. We demonstrate in live experiments with a new cohort of 10 able-bodied participants that the controller yields phase estimates comparable to the state of the art, while also estimating task variables with similar accuracy to recent machine learning approaches. The implemented controller successfully adapts its assistance in response to changing phase and task variables, both during controlled treadmill trials (N=10, phase RMSE: 4.8 ± 2.4%) and a real-world stress test with extremely uneven terrain (N=1, phase RMSE: 4.8 ± 2.7%).

Subject specific optimal control of powered knee exoskeleton to assist human lifting tasks under controlled environment

AbstractWearable robots, sometimes known as exoskeletons, are incredible devices for improving human strength, reducing fatigue, and restoring impaired mobility. The control of powered exoskeletons, on the other hand, is still a challenge. This necessitates the development of a technique to simulate exoskeleton–wearer interaction. This study uses a two-dimensional human skeletal model with a powered knee exoskeleton to predict the optimal lifting motion and assistive torque. For lifting motion prediction, an inverse dynamics optimization formulation is utilized. In addition, the electromechanical dynamics of the exoskeleton DC motor are modeled in the lifting optimization formulation. The design variables are human joint angle profiles and exoskeleton motor current profiles. The human joint torque square is minimized subject to physical and lifting task constraints. Then, the lifting optimization problem is solved by the gradient-based sparse nonlinear optimizer (SNOPT). Furthermore, the optimal exoskeleton torque is implemented through a two-phase control strategy to provide optimal assistance in lifting. Experimental validations of the optimal control with 6 Nm and 16 Nm maximum assistive torque are presented. Both 6 Nm and 16 Nm maximum optimal assistance of the exoskeletons reduce the mean values of vastus lateralis, biceps femoris, and latissimus dorsi muscle activations compared to the lifting without the exoskeleton. However, the mean value of the vastus medialis activation is increased by a small amount for the exoskeleton case, although its peak value is reduced. Finally, the experimental results demonstrate that the proposed lifting optimization formulation and control strategy are promising for powered knee exoskeleton for lifting tasks.

Torque Measurement and Control for Electric-Assisted Bike Considering Different External Load Conditions

This paper proposes a novel torque measurement and control technique for cycling-assisted electric bikes (E-bikes) considering various external load conditions. For assisted E-bikes, the electromagnetic torque from the permanent magnet (PM) motor can be controlled to reduce the pedaling torque generated by the human rider. However, the overall cycling torque is affected by external loads, including the cyclist’s weight, wind resistance, rolling resistance, and the road slope. With knowledge of these external loads, the motor torque can be adaptively controlled for these riding conditions. In this paper, key E-bike riding parameters are analyzed to find a suitable assisted motor torque. Four different motor torque control methods are proposed to improve the E-bike’s dynamic response with minimal variation in acceleration. It is concluded that the wheel acceleration is important to determine the E-bike’s synergetic torque performance. A comprehensive E-bike simulation environment is developed with MATLAB/Simulink to evaluate these adaptive torque control methods. In this paper, an integrated E-bike sensor hardware system is built to verify the proposed adaptive torque control.

Event-Triggered Adaptive Hybrid Torque-Position Control (ET-AHTPC) for Robot-Assisted Ankle Rehabilitation

Ankle rehabilitation for increasing number of strokes is highly demanded, and robot-assisted approach has shown great potential. Since the required movement and force assistances will concurrently change during rehabilitation sessions, the robotic assistances are supposed to be adjusted accordingly. In order to achieve both adaptive torque and synchronous position control for the robot in practice, a novel event-triggered adaptive hybrid torque-position control (ET-AHTPC) is proposed for a developed ankle rehabilitation robot driven by pneumatic muscles (PM). In the novel adaptive torque control scheme, the assistive torque adapted to the patient&#x0027;s recovery state is adjusted by a designed robot-assisted rehabilitation index mapping from the clinical assessment scale. The robotic assistance output is online corrected by patient&#x0027;s performance, based on a correcting index calculated by interaction torque and tracking errors. Then a model-based event-triggered optimal position controller is established and a critic neural network (NN) is introduced to reduce the control law update frequency for fast trajectory tracking. The stability of the overall system is proved by Lyapunov theorem. A series of experiments were conducted on the ankle rehabilitation robot to validate the controller&#x0027;s fast trajectory tracking and adaptive assistance capacity, which can online adjust the robot&#x0027;s assistive torque and allowable movement range for patients at different recovery stages.

An Adaptive Pedaling Assistive Device for Asymmetric Torque Assistant in Cycling.

Dynamic loads have short and long-term effects in the rehabilitation of lower limb joints. However, an effective exercise program for lower limb rehabilitation has been debated for a long time. Cycling ergometers were instrumented and used as a tool to mechanically load the lower limbs and track the joint mechano-physiological response in rehabilitation programs. Current cycling ergometers apply symmetrical loading to the limbs, which may not reflect the actual load-bearing capacity of each limb, as in Parkinson's and Multiple Sclerosis diseases. Therefore, the present study aimed to develop a new cycling ergometer capable of applying asymmetric loads to the limbs and validate its function using human tests. The instrumented force sensor and crank position sensing system recorded the kinetics and kinematics of pedaling. This information was used to apply an asymmetric assistive torque only to the target leg using an electric motor. The performance of the proposed cycling ergometer was studied during a cycling task at three different intensities. It was shown that the proposed device reduced the pedaling force of the target leg by 19% to 40%, depending on the exercise intensity. This reduction in pedal force caused a significant reduction in the muscle activity of the target leg (p < 0.001), without affecting the muscle activity of the non-target leg. These results demonstrated that the proposed cycling ergometer device is capable of applying asymmetric loading to lower limbs, and thus has the potential to improve the outcome of exercise interventions in patients with asymmetric function in lower limbs.