Assistive Torque Research Articles

Customized stiffness control strategy for a six-bar linkage-based gait rehabilitation robot

Abstract Lower limb rehabilitation robots based on linkage-based mechanisms have recently drawn significant attention in the field due to their numerous advantages. The control of previously proposed linkage-based gait rehabilitation robotic orthoses has been achieved using constant speed control without consideration for the interaction forces. However, such an approach can be harmful to people with stroke since the level of disability varies among individuals, and it may cause potential injuries when excessive force is applied by the robot. To overcome this limitation and improve the rehabilitation process, it is necessary to recognize the force exerted by the person during walking and adjust the robot’s assistive torque accordingly, to provide synchronized motion. Thus, in this work, a human-cooperative approach based on a stiffness control strategy for the six-bar linkage-based gait rehabilitation robot is presented. The proposed methodology can serve as a solid foundation for developing a human-cooperative approach for linkage-based lower limb rehabilitation robotic orthoses. The control was validated and tested with eight healthy human subjects. As a result, customized robotic assistance with this mechanism can be provided during training to meet the individual needs of stroke patients, which can lead to increased engagement and contribution, thus improving treatment outcomes.

Artificial neural network-based control of powered knee exoskeletons for lifting tasks: design and experimental validation

Abstract This study introduces a hybrid model that utilizes a model-based optimization method to generate training data and an artificial neural network (ANN)-based learning method to offer real-time exoskeleton support in lifting activities. For the model-based optimization method, the torque of the knee exoskeleton and the optimal lifting motion are predicted utilizing a two-dimensional (2D) human–exoskeleton model. The control points for exoskeleton motor current profiles and human joint angle profiles from cubic B-spline interpolation represent the design variables. Minimizing the square of the normalized human joint torque is considered as the cost function. Subsequently, the lifting optimization problem is tackled using a sequential quadratic programming (SQP) algorithm in sparse nonlinear optimizer (SNOPT). For the learning-based approach, the learning-based control model is trained using the general regression neural network (GRNN). The anthropometric parameters of the human subjects and lifting boundary postures are used as input parameters, while the control points for exoskeleton torque are treated as output parameters. Once trained, the learning-based control model can provide exoskeleton assistive torque in real time for lifting tasks. Two test subjects’ joint angles and ground reaction forces (GRFs) comparisons are presented between the experimental and simulation results. Furthermore, the utilization of exoskeletons significantly reduces activations of the four knee extensor and flexor muscles compared to lifting without the exoskeletons for both subjects. Overall, the learning-based control method can generate assistive torque profiles in real time and faster than the model-based optimal control approach.

Design, Analysis, and Validation of a Passive Parallel Continuum Ankle Exoskeleton for Support and Walking Assistance

Abstract In this paper, we propose a novel passive parallel continuum ankle exoskeleton that can provide assistive torque during ankle plantar flexion. Due to the flexible branches arranged in compliance with ankle motion and shape, the compact design can also offer some vertical support. The proposed parallel mechanism consists of two types of branches. The first type is a pre-bent flexible rod, mainly used to apply assistive force/torque during ankle plantar flexion. The second type of branch consists of a bounded sphere joint, flexible rod, and bounded sphere joint (BFB), which is mainly used for support. We formulate the kinetostatic model of the BFB branch as a series of parallelizable unconstrained optimization problems to ensure efficient solvability. After that, we derive the kinetostatic model of the proposed mechanism. After calibration, the wrench error of the kinetostatic model is 9.07%. Simulation analysis based on the calibrated model shows that the designed mechanism has high supporting stiffness and low rotational stiffness. The assistive torque caused by the nonlinear rotational stiffness in the sagittal plane is similar to that of passive clutch-like mechanisms. These properties can still be maintained when the joint center changes within a small range. Besides, a walking experiment was conducted, and the results show that the proposed design can reduce gastrocnemius activity.

Mitigating Crouch Gait with an Autonomous Pediatric Knee Exoskeleton in the Neurologically Impaired.

Crouch gait is one of the most common compensatory walking patterns found in individuals with neurological disorders due to their limited physical capacity. Notable kinematic characteristics of crouch gait are excessive knee flexion during stance and reduced range of motion during swing. Knee exoskeletons have the potential to improve crouch gait by providing precisely controlled torque assistance directly to the knee joint. In this study, we implemented a finite-state machine-based impedance controller for a powered knee exoskeleton to provide assistance during both stance and swing for five children/young adults who exhibit chronic crouch gait. The assistance provided a strong orthotic effect, increasing stance phase knee extension by an average of 12°. The knee range of motion during swing was increased by an average of 15°. Changes to spatiotemporal outcomes, such as preferred walking speed and percent stance phase, were inconsistent across subjects and indicative of the underlying intricacies of user response to assistance. This study demonstrates the potential of knee exoskeletons operating in impedance control to mitigate the negative kinematic characteristics of crouch gait during both stance and swing phases of gait.

User-Centered Evaluation of the Wearable Walker Lower Limb Exoskeleton; Preliminary Assessment Based on the Experience Protocol.

Using lower limb exoskeletons provides potential advantages in terms of productivity and safety associated with reduced stress. However, complex issues in human-robot interactions are still open, such as the physiological effects of exoskeletons and the impact on the user's subjective experience. In this work, an innovative exoskeleton, the Wearable Walker, is assessed using the EXPERIENCE benchmarking protocol from the EUROBENCH project. The Wearable Walker is a lower-limb exoskeleton that enhances human abilities, such as carrying loads. The device uses a unique control approach called Blend Control that provides smooth assistance torques. It operates two models simultaneously, one in the case in which the left foot is grounded and another for the grounded right foot. These models generate assistive torques combined to provide continuous and smooth overall assistance, preventing any abrupt changes in torque due to model switching. The EXPERIENCE protocol consists of walking on flat ground while gathering physiological signals, such as heart rate, its variability, respiration rate, and galvanic skin response, and completing a questionnaire. The test was performed with five healthy subjects. The scope of the present study is twofold: to evaluate the specific exoskeleton and its current control system to gain insight into possible improvements and to present a case study for a formal and replicable benchmarking of wearable robots.

A randomized cross-over study protocol to evaluate long-term gait training with a pediatric robotic exoskeleton outside the clinical setting in children with movement disorders.

Individuals with neuromuscular disorders display a combination of motor control deficits and lower limb weakness contributing to knee extension deficiency characterized by exaggerated stance phase knee flexion. There is a lack of evidence for long-term improvement of knee extension deficiency with currently available clinical treatment programs. Our previous work testing a wearable robotic exoskeleton with precisely timed assistive torque applied at the knee showed immediate increases in knee extension during walking for children with cerebral palsy, which continued to improve over an acute practice period. When we applied interleaved assistance and resistance to knee extension, we observed improvements in knee extension and increased muscle activation indicating the potential for muscle strengthening when used over time. There is a need for additional, high-quality trials to assess the impact of dosage, intensity and volume of training necessary to see persistent improvement in lower limb function for these patient populations. This randomized crossover study (ClinicalTrials.gov: NCT05726591) was designed to determine whether 12 weeks of overground gait training with a robotic exoskeleton outside of the clinical setting, following an initial in clinic accommodation period, has a beneficial effect on walking ability, muscle activity and overall motor function. Participants will be randomized to either complete the exoskeleton intervention or continue their standard therapy for 12 weeks first, followed by a crossover to the other study component. The primary outcome measure is change in peak knee extension angle during walking; secondary outcome measures include gait speed, strength, and validated clinical scales of motor function and mobility. Assessments will be completed before and after the intervention and at 6 weeks post-intervention, and safety and compliance will be monitored throughout. We hypothesize that the 12-week exoskeleton intervention outside the clinical setting will show greater improvements in study outcome measures than the standard therapy.

Hip Exoskeleton for Cycling Assistance.

Cycling stands as one of the most widely embraced leisure activities and serves purposes such as exercise, rehabilitation, and commuting. This study aimed to assess the feasibility of assisting three unimpaired participants (age: 34.0 ± 7.9 years, height: 1.86 ± 0.02 m, weight: 75.7 ± 12.7 kg) using the GuroX hip exoskeleton, originally designed for walking assistance, during cycling against a resistance of 1 W/kg. The performance evaluation employed a sweep protocol that manipulated the timing of the exoskeleton's peak extension and flexion torque in addition to human-in-the-loop optimization to enhance these timings based on metabolic cost. Our findings indicate that with a peak assistance torque of approximately 10.3 Nm for extension and flexion, the GuroX substantially reduced the net metabolic cost of cycling by 31.4 ± 8.1% and 26.4 ± 14.1% compared to transparent and without exoskeleton conditions, respectively. This demonstrates the significant potential of a hip exoskeleton developed for walking assistance to profoundly benefit cycling. Additionally, customizing the assistance strategy proves beneficial in maximizing assistance. While we attribute the average motor power to be a major contributor to the reduced cycling effort, participant feedback suggests that user comfort and synchronization between the user and exoskeleton may have played integral roles. Further research should validate our initial findings by employing a larger participant pool in real-world conditions. Incorporating a more diverse set of parameters for the human-in-the-loop optimization could enhance individualized assistance strategies.

Modeling Neuromotor Adaptation to Pulsed Torque Assistance During Walking.

Multiple mechanisms of motor learning contribute to the response of individuals to robot-aided gait training, including error-based learning and use-dependent learning. Previous models described either of these mechanisms, but not both, and their relevance to gait training is unknown. In this paper, we establish the validity of existing models to describe the response of healthy individuals to robot-aided training of propulsion via a robotic exoskeleton, and propose a new model that accounts for both use-dependent and error-based learning. We formulated five state-space models to describe the stride-by-stride evolution of metrics of propulsion mechanics during and after robot-assisted training, applied by a hip/knee robotic exoskeleton for 200 consecutive strides. The five models included a single-state, a two-state, a two-state fast and slow, a use-dependent learning (UDL), and a newly-developed modified UDL model, requiring 4, 9, 5, 3, and 4 parameters, respectively. The coefficient of determination (R 2) and Akaike information criterion (AIC) values were calculated to quantify the goodness of fit of each model. Model fit was conducted both at the group and at the individual participant level. At the group level, the modified UDL model shows the best goodness-of-fit compared to other models in AIC values in 15/16 conditions. At the participant level, both the modified UDL model and the two-state model have significantly better goodness-of-fit compared to the other models. In summary, the modified UDL model is a simple 4-parameter model that achieves similar goodness-of-fit compared to a two-state model requiring 9 parameters. As such, the modified UDL model is a promising model to describe the effects of robot-aided gait training on propulsion mechanics.

Development and Validation of Robotic Ankle Exoskeleton With Parallel Nonlinear Elastic Actuator

Abstract This paper presents the development of a robotic ankle exoskeleton for human walking assistance. First, the biomechanical properties of a human ankle joint during walking are presented. Next, design of the robotic ankle exoskeleton is introduced. The exoskeleton is actuated by a novel parallel nonlinear elastic actuator. The cam-spring mechanism in the actuator can function as a parallel nonlinear spring with an adjustable stiffness, and the design of the cam profile curve is described. Additionally, an adaptive controller is proposed for the exoskeleton to generate a desired assistive torque according to the wearer's total weight. Finally, experiments are conducted to validate the effectiveness of the developed robotic ankle exoskeleton. The experimental results demonstrate that during a gait cycle, reductions of 42.7% and 40.1% of the peak and average currents of the driving motor in the actuator are observed, respectively, with the designed cam-spring mechanism. A peak assistive torque of 23.9 Nm can be provided for the wearers by the exoskeleton during walking. With the assistance provided by the exoskeleton, the average and peak soleus activities of the wearers during a gait cycle are decreased by 25.42% and 31.94%, respectively.

Development of Quasi-Passive Back-Support Exoskeleton with Compact Variable Gravity Compensation Module and Bio-Inspired Hip Joint Mechanism.

The back support exoskeletons have garnered significant attention to alleviate musculoskeletal injuries, prevalent in industrial settings. In this paper, we propose AeBS, a quasi-passive back-support exoskeleton developed to provide variable assistive torque across the entire range of hip joint motion, for tasks with frequent load changes. AeBS can adjust the assistive torque levels while minimizing energy for the torque variation without constraining the range of motion of the hip joint. To match the requisite assistance levels for back support, a compact variable gravity compensation module with reinforced elastic elements is applied to AeBS. Additionally, we devised a bio-inspired hip joint mechanism that mimics the configuration of the human hip axis to ensure the free body motion of the wearer, significantly affecting assistive torque transmission and wearing comfort. Benchtop testing showed that AeBS has a variable assistive torque range of 5.81 Nm (ranging from 1.23 to 7.04 Nm) across a targeted hip flexion range of 135°. Furthermore, a questionnaire survey revealed that the bio-inspired hip joint mechanism effectively facilitates the transmission of the intended assistive torque while enhancing wearer comfort.

Soft Artificial Muscle Based on Pre-Detwinned Shape Memory Alloy Spring Actuator Achieving High Passive Assistive Torque for Wearable Robot.

For designing the assistive wearable rehabilitation robots, it is challenging to design the robot as energy efficient because the actuators have to be capable of overcoming human loads such as gravity of the body and spastic torque continuously during the assistance. To address these challenges, we propose a novel design of soft artificial muscle that utilizes shape memory alloy (SMA) spring actuators with pre-detwinning process. The SMA spring was fabricated through a process called pre-detwinning, which enhances the linearity of the SMA spring in martensite phase and unpowered restoring force, which is called passive force. The fabricated SMA spring can contract >60%. Finally, the soft wearable robot that can assist not only the gravitational torque exerted on the elbow by passive force, but also the elbow movements with active force was designed with a soft artificial muscle. A soft artificial muscle consists of the bundles of pre-detwinned SMA springs integrated with the stretchable coolant vessel. The stiffness of the muscle was measured as 1125 N/m in martensite phase and 1732 N/m in austenite phase. In addition, the muscle showed great actuation frequency performances, the bandwidth of which was measured as 0.5 Hz. The proposed wearable mechanism can fully compensate the gravitational torque for all the angles in passive mode. In addition, the proposed mechanism can produce high torque up to 3.5 Nm and movements in active mode.

Optimizing Exoskeleton Assistance: Muscle Synergy-Based Actuation for Personalized Hip Exoskeleton Control

Exoskeleton robots hold promising prospects for rehabilitation training in individuals with weakened muscular conditions. However, achieving improved human–machine interaction and delivering customized assistance remains a challenging task. This paper introduces a muscle synergy-based human-in-the-loop (HIL) optimization framework for hip exoskeletons to offer more personalized torque assistance. Initially, we propose a muscle synergy similarity index to quantify the similarity of synergy while walking with and without the assistance of an exoskeleton. By integrating surface electromyography (sEMG) signals to calculate metrics evaluating muscle synergy and iteratively optimizing assistance parameters in real time, a muscle synergy-based HIL optimized torque configuration is presented and tested on a portable hip exoskeleton. Iterative optimization explores the optimal and suboptimal assistance torque profiles for six healthy volunteers, simultaneously testing zero torque and predefined assistance configurations, and verified the corresponding muscle synergy similarity indices through experimental testing. In our validation experiments, the assistance parameters generated through HIL optimization significantly enhance muscle synergy similarity during walking with exoskeletal assistance, with an optimal average of 0.80 ± 0.04 (mean ± std), marking a 6.3% improvement over prior assistive studies and achieving 96.4% similarity compared with free walking. This demonstrates that the proposed muscle synergy-based HIL optimization can ensure robotic exoskeleton-assisted walking as “natural” as possible.

Optimizing exoskeleton assistance to improve walking speed and energy economy for older adults

BackgroundWalking speed and energy economy tend to decline with age. Lower-limb exoskeletons have demonstrated potential to improve either measure, but primarily in studies conducted on healthy younger adults. Promising techniques like optimization of exoskeleton assistance have yet to be tested with older populations, while speed and energy consumption have yet to be simultaneously optimized for any population.MethodsWe investigated the effectiveness of human-in-the-loop optimization of ankle exoskeletons with older adults. Ten healthy adults > 65 years of age (5 females; mean age: 72 ± 3 yrs) participated in approximately 240 min of training and optimization with tethered ankle exoskeletons on a self-paced treadmill. Multi-objective human-in-the-loop optimization was used to identify assistive ankle plantarflexion torque patterns that simultaneously improved self-selected walking speed and metabolic rate. The effects of optimized exoskeleton assistance were evaluated in separate trials.ResultsOptimized exoskeleton assistance improved walking performance for older adults. Both objectives were simultaneously improved; self-selected walking speed increased by 8% (0.10 m/s; p = 0.001) and metabolic rate decreased by 19% (p = 0.007), resulting in a 25% decrease in energetic cost of transport (p = 8e-4) compared to walking with exoskeletons applying zero torque. Compared to younger participants in studies optimizing a single objective, our participants required lower exoskeleton torques, experienced smaller improvements in energy use, and required more time for motor adaptation.ConclusionsOur results confirm that exoskeleton assistance can improve walking performance for older adults and show that multiple objectives can be simultaneously addressed through human-in-the-loop optimization.

Abduction/Adduction Assistance From Powered Hip Exoskeleton Enables Modulation of User Step Width During Walking.

As the first step to show its potential, the objective of this study was to investigate how human's step width reacted to hip exoskeleton's admittance control parameter changes during walking. Ten non-disabled individuals walked on a treadmill at a self-selected speed, while wearing our bilateral robotic hip exoskeleton. We used two equilibrium positions to define the direction of assistance. We studied the influence of multiple stiffness values in the admittance control on the participants' step width, step length, and electromyographic (EMG) activity of the gluteus medius. Step width were significantly modulated by the change of stiffness in exoskeleton control, while step length did not show significant changes. When the stiffness changed from zero to our studied stiffness values, the participants' step width started to modulate immediately. Within 4 consecutive heel strikes right after a stiffness change, the step width showed a significant change. Interestingly, EMG activity of the gluteus medius did not change significantly regardless the applied stiffness and powered direction. Tuning of stiffness in admittance control of a hip exoskeleton, acting in mediolateral direction, can be a viable way for controlling step width in normal walking. Unvaried gluteus medius activity indicates that the increase in step width were mainly caused by the assistive torque applied by the exoskeleton. Our study results pave a new way for future design and control of wearable robotics in enhancing mediolateral walking balance for various rehabilitation applications.

A Novel Passive Occupational Shoulder Exoskeleton With Adjustable Peak Assistive Torque Angle For Overhead Tasks.

Overhead tasks are a primary inducement to work-related musculoskeletal disorders. Aiming to reduce shoulder physical loads, passive shoulder exoskeletons are increasingly prevalent in the industry due to their lightweight, affordability, and effectiveness. However, they can only handle specific tasks and struggle to balance compactness with a sufficient range of motion effectively. We proposed a novel passive occupational shoulder exoskeleton designed to handle various overhead tasks at different arm elevation angles, ensuring sufficient ROM while maintaining compactness. By formulating kinematic models and simulations, an ergonomic shoulder structure was developed. Then, we presented a torque generator equipped with an adjustable peak assistive torque angle to switch between low and high assistance phases through a passive clutch mechanism. Ten healthy participants were recruited to validate its functionality by performing the screwing task. Measured range of motion results demonstrated that the exoskeleton can ensure a sufficient ROM in both sagittal (164°) and horizontal (158°) flexion/extension movements. The experimental results of the screwing task showed that the exoskeleton could reduce muscle activation (up to 49.6%), perceived effort and frustration, and provide an improved user experience (scored 79.7 out of 100). These results indicate that the proposed exoskeleton can guarantee natural movements and provide efficient assistance during overhead work, and thus have the potential to reduce the risk of musculoskeletal disorders. The proposed exoskeleton provides insights into multi-task adaptability and efficient assistance, highlighting the potential for expanding the application of exoskeletons.

Walking and scuba diving assisted amphibious exoskeleton robots: the designing of power assist control and myoelectricity based wearers' fatigue evaluation.

Exoskeleton robots have the potential to augment human motor capabilities. however, current control strategies often require task-specific control laws tailored for different scenarios, which limits the applicability of exoskeletons. In this study, we propose a control strategy for exoskeleton robots that is adaptable across various scenarios. We employ adaptive oscillators (AO) with feedback control to rapidly estimate the wearer's motion phase and subsequently provide torque assistance to the wearer's hip joint based on a TCN-LSTM model. During experiments, we collected surface electromyographic (sEMG) signals from the tibialis anterior, gastrocnemius, and rectus muscles of seven groups of subjects performing treadmill walking and inclined treadmill exercises. We utilized the short-time Fourier transform to extract frequency characteristics of the signals and statistically analyzed the rate of frequency change in each muscle group under different strategies. The results indicate that when wearing the exoskeleton, the overall muscle frequency changes more slowly, suggesting that subjects can maintain activity for a longer duration before fatigue sets in. This control strategy effectively reduces the energetic cost of lower limb work for the wearer and enhances the exoskeleton's versatility in various applications.

Motion-Based Control Strategy of Knee Actuated Exoskeletal Gait Orthosis for Hemiplegic Patients: A Feasibility Study

In this study, we developed a unilateral knee actuated exoskeletal gait orthosis (KAEGO) for hemiplegic patients to conduct gait training in real-world environments without spatial limitations. For this purpose, it is crucial that the controller interacts with the patient’s gait intentions. This study newly proposes a simple gait control strategy that detects the gait state and recognizes the patient’s gait intentions using only the motion information of the lower limbs obtained from an embedded inertial measurement units (IMU) sensor and a knee angle sensor without employing ground reaction force (GRF) sensors. In addition, a torque generation method based on negative damping was newly applied as a method to determine the appropriate amount of assistive torque to support flexion or extension movements of the knee joint. To validate the performance of the developed KAEGO and the effectiveness of our proposed gait control strategy, we conducted walking tests with a hemiplegic patient. These tests included verifying the accuracy of gait recognition and comparing the metabolic cost of transport (COT). The experimental results confirmed that our gait control approach effectively recognizes the patient’s gait intentions without GRF sensors and reduces the metabolic cost by approximately 8% compared to not wearing the device.

A Comparative Analysis of Optimal and Biomechanical Torque Control Strategies for Powered Knee Exoskeletons in Squat Lifting

Abstract Exoskeletons have the ability to aid humans in physically demanding and injury-prone activities, such as lifting loads while squatting. However, despite their immense potential, the control of powered exoskeletons remains a persistent challenge. In this study, we first predict the human lifting motion and knee joint torque using an inverse dynamics optimization formulation with a two-dimensional (2D) human skeletal model. The design variables are human joint angle profiles. The normalized human joint torque squared is minimized subject to physical and lifting task constraints. After that, the biomechanical assistive knee exoskeleton torque is obtained by scaling the predicted human knee joint torque. Second, we also present a 2D human skeletal model with a powered knee exoskeleton for predicting the optimal assistive torque and lifting motion. The design variables are human joint angle profiles and exoskeleton motor current profiles. Then, the biomechanical and optimal exoskeleton torques are implemented in a powered knee exoskeleton in real-time to provide external assistance in human lifting motion. Finally, the biomechanical and optimal assistive exoskeleton torque controls for lifting are compared. It is observed that both control methods have a significant impact on reducing muscle activations for the specific muscle groups compared to the cases without the exoskeleton. Especially, peak activations of erector spinae and rectus femoris muscles are reduced by 57.79% and 47.26% with biomechanical assistive torque. Likewise, vastus medialis and vastus lateralis activations drop by 46.82% and 52.24% with optimal assistive torque.

Actuator optimization and deep learning-based control of pediatric knee exoskeleton for community-based mobility assistance

Lightweight and smart exoskeletons offer the potential to improve mobility in children. State-of-the-art pediatric exoskeletons are typically clinic-based since they are either tethered or portable but cumbersome and their design is often not optimized across a range of environments and users. To facilitate pediatric exoskeleton in community settings, we first proposed an actuator optimization framework that identified the optimal design parameters for both motor and transmission while minimizing the actuator mass and satisfying the output torque, speed, bandwidth, and resistance torque requirements. Guided by the optimization results, we customized a simple, lightweight actuator that met all mechatronic constraints for our portable exoskeleton (1.78 kg unilateral). Secondly, we adopted deep learning (Long Short Term Memory) based on gait phase estimation to facilitate stable control for community use. The models accurately estimated the gait phase on irregular walking patterns (accuracy 94.60%) without explicit training in children (typically developing and with cerebral palsy). The controller results demonstrated an elevated ability to adapt to the irregular gait patterns of the child with cerebral palsy. The experimental results in the child with typical development and four healthy adults demonstrated accurate assistive torque tracking performance (accuracy 97.00%) at different walking speeds (i.e., under uncertain torque to wearers). This work presented a holistic solution that includes both hardware innovation (actuator optimization framework) and software innovation (deep learning-based control) towards the paradigm shift of pediatric exoskeletons from clinic to community setting.

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.