Joint Torque Research Articles

Torque modulation mechanism of the knee joint during balance recovery

Exploring the torque modulation mechanisms of human joints is critical for analyzing the human balance control system and developing natural human-machine interactions for balance support. However, the knee joint is often overlooked in biomechanical models because of its limited range of motion during balance recovery. This poses a challenge in establishing mathematical models for the knee joint's torque modulation mechanisms using computer simulations based on the inverted pendulum model. This study aims to provide a simplified linear feedback model inspired by sensorimotor transformation theory to reveal the torque modulation mechanism of the knee joint. The model was validated using data from experiments involving support-surface translation perturbations. The goodness-of-fit metrics of the model, including R2 values and root mean square errors (RMSE), demonstrated strong explanatory power (R2 ranged from 0.77 to 0.90) and low error (RMSE ranging from 0.035 to 0.072) across different perturbation magnitudes and directions. Through pooling samples across various perturbation conditions and conducting multiple fits, this model revealed that knee torque is modulated using a direction-specific strategy with adaptable feedback gains. These results suggest that the proposed simplified linear model can be used to develop assistive systems and retrieve insights on balance recovery mechanisms.

Ultracompact Joint Torque Sensor Units With Enhanced Resolution for Collaborative Robots

Ultracompact Joint Torque Sensor Units With Enhanced Resolution for Collaborative Robots

A novel Bayesian optimization prediction framework for four-axis industrial robot joint motion state

Robot joints are the main structure for controlling the motion of the machine body, where the motion state of them directly affects the performance of the industrial robot. Due to the difficulty of obtaining the joint torque information of industrial robots, it is very hard to monitor the motion state of them. Based on the velocity and force driven by current of motors, we propose a novel Bayesian optimization framework to predict the joint motion state of industrial robot in this paper. Based on the temporal correlation of joint current and the correlation between the current and motion state of joint, we use the LSTM and BiLSTM to regressing prediction of the current and state of joint motor first. Then, the Bayesian optimization method is used to adjust the hyperparameters of our network, which realize the analysis of the joint motor current under different motion states and improve the accuracy of the prediction of joint motion states. Finally, we design the joint current acquisition platform of industrial robot based on Hall current sensors, which can collect joint currents without contact and generate experimental dataset. Comparing with the popular intelligent methods, the results show that our Bayesian optimization framework realizes a more accurate prediction of motion state for the four-axis industrial robot on the basis of contact-less current acquisition.

Investigation of the Effect of Physical Ability on the Fall Mitigation Motion Using the Combination of Experiment and Simulation

The simulation of fall plays a critical role in estimating injuries caused by fall. However, implementing human fall mitigation motions on a simulator proves challenging due to the complexity and variability of fall movement. Our simulator estimates fall motion by extrapolating the motion observed in fall experiments. By incorporating actual fall motion data for the upper limbs, we enhanced the realism of the fall simulation. The application of forward dynamics control to the lower limbs allowed for the adjustment of mitigation motions, taking into account individual physical capabilities. In this study, fall simulations were conducted under the constraints of maximum joint torque and maximum torque change rate, emulating the physical capabilities of both the elderly and young adults. Our results successfully demonstrated the mitigation motion facilitated by the stance leg reduced the descent velocity of the center of mass by 0.75 m/s for elderly individuals and by 1.25 m/s for young adults, compared to a zero torque condition. This indicates that our study introduced a novel method for quantifying the impact of the lower limbs’ physical capabilities on fall velocity. Such a method represents a significant advancement in understanding how mitigation motions can influence fall injury simulations.

Soft Robotic Glove Modulating Joint Torque Through Novel Passive Extensor Mechanisms

Soft Robotic Glove Modulating Joint Torque Through Novel Passive Extensor Mechanisms

Hybrid Adaptive Impedance and Admittance Control Based on the Sensorless Estimation of Interaction Joint Torque for Exoskeletons: A Case Study of an Upper Limb Rehabilitation Robot

Physiotherapy is the treatment to recover a patient’s mobility and limb function after an injury, illness, or disability. Rehabilitation robots can be used to replace human physiotherapists. To ensure safety during robot physical therapy, the patient’s limb needs to be controlled to track a desired joint trajectory, and the torque due to interaction force/torque needs to be measured and regulated. Therefore, hybrid impedance and admittance with position control (HIPC) is required to track the trajectory and simultaneously regulate the contact torque. The literature describes two structures of HIPC: (1) a switched framework between admittance and impedance control operating in parallel (HIPCSW); and (2) a series connection between admittance and impedance control without switching. In this study, a hybrid adaptive impedance and position-based admittance control (HAIPC) in series is developed, which consists of a proportional derivative-based admittance position controller with gravitational torque compensation and an adaptive impedance controller. An extended state observer is used to estimate the interaction joint torque due to human stiff contact with the exoskeleton without the use of force/torque sensor, which is then used in the adaptive algorithm to update the stiffness and damping gains of the adaptive impedance controller. Simulation results obtained using MATLAB show that the proposed HAIPC significantly reduces the mean absolute values of the actuation torques (control inputs) required for the shoulder and elbow joints in comparison with HIPC and HIPCSW.

Hierarchical approximate optimal interaction control of human-centered modular robot manipulator systems: A Stackelberg differential game-based approach

A Stackelberg game-based approximate optimal interaction control approach is presented for human-centered modular robot manipulator (MRM) systems. Joint torque feedback (JTF) technique is utilized to form the MRM dynamic model. The major objective of optimal control with human–robot collaboration (HRC) is transformed into approximating Stackelberg equilibrium by adopting Stackelberg game governed between the human and the MRM that are regarded as players with different hierarchical level in interaction process. On the basis of the adaptive dynamic programming (ADP), the approximate optimal interaction control policy with HRC task is developed via critic neural network (NN)-based Stackelberg game manner for addressing Hamilton–Jacobian (HJ) equations. The position tracking error is ultimately uniformly bounded (UUB) according to the Lyapunov theory. Experiment results demonstrate the effectiveness of the proposed method.

A general energy modeling network for serial industrial robots integrating physical mechanism priors

Industrial robots (IRs), as the core equipment of intelligent manufacturing, play increasingly important roles in various industrial scenarios such as assembly, welding, handling, and spraying, significantly improving production efficiency and product quality. The massive popularization and application of IRs have brought about a sharp increase in energy consumption (EC), and the modeling and optimization of EC is becoming imperative. In this paper, a general energy modeling network DM-PLM for serial IRs based on Dynamic Model (DM) and Power Loss Model (PLM) is proposed by integrating the prior knowledge of IR power composition and dynamic mechanism, enabling efficient and accurate modeling of dynamics, power, and EC under multi-load conditions. Considering the force transmission characteristics of serial robots, this paper proposes an improved bidirectional recurrent neural network (BiRNN) to model the joint dynamics. Additionally, a power loss model based on the ResNet convolutional neural network is employed. Experiments are carried out with a KUKA KR210 heavy-duty robot and a UR5 collaborative robot. The results show that the DM-PLM model incorporating the physical mechanism priors achieves 97 %, 98 %, and 99 % modeling accuracy in joint torques, total power, and EC for both robots under multi-load conditions. In addition, the proposed DM-PLM model is applied to the EC optimization of KUKA KR210 through trajectory planning, which achieves over 30 % EC reduction with the genetic algorithm, providing an effective approach to improving the energy efficiency of serial IRs.

Synthetic control with target sticking for on-orbit capturing using a dual-arm space robot

On-orbit capturing is a crucial step in the application of dual-arm space robots, aiming to accurately grasp a moving target and avoid damage to the arms terminal parts (i.e. the end effectors) due to contact force saturation. This paper presents a synthetic control method with target sticking for on-orbit capturing using a dual-arm space robot system from the approaching phase to pre-grasping phase. In the approaching phase, an online trajectory planning method based on visual servoing is proposed to obtain the desired trajectories for end effectors in work space. Then the joint torques are designed by the inverse kinematics and inverse dynamics to track the desired trajectories. Different from most of the current research, a new sticking phase is proposed after the approaching phase and before the pre-grasping phase. In the sticking phase, a force and motion control method is designed to maintain a close relative distance between end effectors and the target, which can avoid saturation of contact forces and avoid damage to the end effectors. In what follows, an impedance control method is proposed in the pre-grasping phase to absorb the impact energy and grasp the target accurately. The synthetic control strategy integrates the controllers of all the phases mentioned above. Automatic switching among the phases is realized by using logic judgment according to the system real states, which is more consistent with the real capturing environment. Finally, numerical simulation results demonstrate the effectiveness of the proposed synthetic control scheme. The results can be applied to the trajectory planning and control of on-orbit capturing, avoiding contact force saturation and ensuring the safety of the system.

Effects of Stationary Bikes and Elliptical Machines on Knee Joint Kinematics during Exercise.

Background and Objectives: This study examined the influence of stationary bikes and elliptical machines on knee movement and joint load during exercise. Materials and Methods: Twelve healthy male participants engaged in pedaling exercises on stationary bikes and elliptical machines at speeds of 50 and 70 revolutions per minute (rpm). Knee movement and joint load were assessed using a motion analysis system. Results: The results indicated that elliptical machines induced higher knee joint torque compared to stationary bikes. Notably, peak torque occurred at different joint angles, with stationary bikes reaching an earlier peak at 70°-110° and elliptical machines showing a later peak at 135°-180°. Increased pedaling speed correlated with higher peak knee joint torque on both machines. With the elliptical machine, a higher pedaling frequency correlated with increased peak forces on the knee and ankle joints, as well as vertically. Interestingly, both types of equipment were associated with enhanced peak knee joint torques during high-speed pedaling. Conversely, constant pedaling on elliptical machines limited the ankle angle and could induce inward rotation. Conclusions: This study focused on knee joint torque variations during pedaling on indoor stationary bicycles and elliptical machines. Elliptical machines showed higher peak values of forces and torque, particularly during the propulsive and recovery phases, indicating potential challenges to the knee joint. Notably, peak pedal angles occurred earlier on indoor stationary bicycles, emphasizing the impact of equipment choice on joint kinetics.

Predicting preferred motorcycle riding postures to support human factors/ergonomic trade-off analyses within a multi-objective optimisation-based digital human model

Digital human models (DHM) can predict how users might interact with new vehicle geometry during early-stage design, an important precursor to conducting trade-off analyses. However, predicting human postures requires assumptions about which performance criteria best predict realistic postures. Focusing on the design of motorcycles, we do not know what performance criteria drive preferred riding postures. Addressing this gap, we aimed to identify which performance criteria and corresponding weightings best predicted preferred motorcycle riding postures when using a DHM. To address our aim, we surveyed the literature to find experimental data specifying joint angles that correspond to preferred riding postures. We then deployed a response surface methodology to determine which performance criteria and weightings optimally predicted the preferred riding postures when using a DHM. Weighting the minimisation of the discomfort performance criteria (an aggregate of joint range of motion, displacement from neutral and joint torque) best predicted preferred motorcycle riding postures.

Device for Measuring Forces and Torques in Flexible Connection Joints for Parabolic Trough Collector

Measurement of forces and torques in flexible connection joints for parabolic trough collectors (PTC) during their life time is important to prevent damage or breakage of these elements. Plataforma Solar de Almería (PSA) has developed and patented a device for measuring these forces and torques in flexible connection joints installed in solar power plants. The device consists of three dynamometers and one torque transducer coupled to a rotation assembly that can be externally coupled to a ball joint installed in interconnections of parabolic-troughs, with no interference in the hydraulic circuit. To calibrate the device and perform initial performance checks at lab scale, a test bench was prepared for applying forces and torques on a set-up composed of a multicomponent sensor connected in series to a standard rotary ball joint and measuring simultaneously the forces and torques by mean of the designed device. Calibration tests have been performed applying a range of forces and torques to the multicomponent sensor-ball joint at different rotation positions. Multicomponent sensor and developed device measurements have been compared to obtain a calibration matrix for the last one. Results show good performance of the device once calibrated, but that will be improved measuring angular deviations from reference axes position of each of the dynamometers that compose the device during the operation, to increase the accuracy of the measurements.

Simulation Analysis of Frog-Inspired Take-Off Performance Based on Different Structural Models.

The frog-inspired jumping robot is an interesting topic in the field of biomechanics and bionics. However, due to the frog's explosive movement and large range of joint motion, it is very difficult to make their structure completely bionic. To obtain the optimal jumping motion model, the musculoskeletal structure, jumping movement mechanism, and characteristics of frogs are first systematically analyzed, and the corresponding structural and kinematic parameters are obtained. Based on biological characteristics, a model of the articular bone structure is created, which can fully describe the features of frog movement. According to the various factors affecting the frog's jumping movement, mass and constraints are added, and the complex biological joint structure is simplified into four different jumping structure models. The jumping ground reaction force, velocity, and displacement of the center of mass, joint torque, and other motion information of these four models are obtained through ADAMS simulation to reveal the jumping movement mechanism and the influencing factors of frogs. Finally, various motion features are analyzed and compared to determine the optimal structural model of the comprehensive index, which provides a theoretical basis for the design of the frog-inspired jumping robot.

Hysteresis identification of joint with harmonic drive transmission based on Monte Carlo method

In this study, we analyze the hysteresis behavior of robotic joints equipped with harmonic drivers under various speeds and loads, focusing on a range of hysteresis models including the Bouc–Wen (BW), Fractional Order Bouc–Wen (FOBW), and their integration with the Krasnoselskii–Pokrovskii (KP) model. This integration, which forms the KP-FOBW model, is a novel aspect of our research, offering an enhanced understanding of non-linear and hysteresis behaviors in robotic joints. We employ the Monte Carlo method, particularly focusing on the Stochastic Gradient Hamiltonian Monte Carlo (SGHMC), for precise parameter identification. Our results demonstrate that the FOBW model, especially when combined with the KP model, provides a more accurate representation of the hysteresis curves under varying operating conditions. The KP-FOBW combination emerges as a powerful tool to predict the output torque in robotic joints. This study contributes to a deeper understanding of hysteresis in joints with harmonic drivers, showcasing its potential for complex dynamic modeling in robotics.

A Fast Calibration Method for an sEMG-Based Lower Limb Joint Torque Estimation Model

The joint torque estimation model based on surface electromyography (sEMG) signals needs to recalibrate the model parameters when used for joint torque estimation at different volunteers. However, the feature transferability drops significantly in higher task-specific layers, which reduce the performance of the model. The generalization of joint torque estimation models among different volunteers has become a challenge. In this paper, a fast calibration method based on a deep adaptive regression network is proposed to reduce the frequency and time of model recalibration when volunteers change. The proposed method associates source domain (SD) data with target domain (TD) data through migration learning. The maximum mean difference (MMD) adaptive method is used to migrate the model trained in the SD dataset to the TD dataset, which avoids the recalibration required in the joint torque estimation model. The experimental results show that the proposed method can improve the migration ability of the model used for estimating joint torque and achieve the generalization application of the model on different volunteer datasets. Moreover, the proposed method can reduce the calibration operations and iterations of the model caused by volunteer changes and improve the speed of joint torque estimation. The optimal normalized root mean square error (NRMSE) and Pearson correlation coefficient (ρ) of knee extension/flexion joint torque estimation reached 0.02198/0.02565 and 0.9892/0.9839, respectively.

Effects of attentional focus strategy on drop jump for athletes with different experience levels: Performance, kinetics and kinematics

The attentional focus strategy (AFS) affects drop jump (DJ) performance; however, its effects on DJ kinetics and kinematics are unclear. This study examines the effects of AFS on DJ performance, kinetics and kinematics. Forty collegiate males were divided into a DJ experienced group and a DJ inexperienced group, and they performed two trials of DJs after listening to instructions designed to elicit internal (INT), external (EXT) or neutral (NEUT) focus of attention. In the experienced group, the reactive strength index (RSI) was larger with the NEUT than with the INT. Hip joint torque and positive hip joint power in the concentric phase was smaller with the NEUT than with the INT, and the hip joint angle at the lowest centre of mass was larger with the NEUT than with the INT ( p < .05). In the inexperienced group, RSI was larger with the EXT than with the INT. Further, the hip joint torque in the concentric phase was smaller with the EXT than with the INT; positive ankle joint power was larger with the EXT than with the INT; and the hip joint angles at the lowest centre of mass and take-off were larger with the EXT than with the INT ( p < .05). These results showed that the AFS affected the DJ performance, kinetics and kinematics and suggested that effective DJ training may be achieved with the NEUT for DJ experienced and with the EXT for DJ inexperienced.

Optimal hip capsular release for joint exposure in hip resurfacing via the direct anterior approach.

Surgical approaches that claim to be minimally invasive, such as the direct anterior approach (DAA), are reported to have a clinical advantage, but are technically challenging and may create more injury to the soft-tissues during joint exposure. Our aim was to quantify the effect of soft-tissue releases on the joint torque and femoral mobility during joint exposure for hip resurfacing performed via the DAA. Nine fresh-frozen hip joints from five pelvis to mid-tibia cadaveric specimens were approached using the DAA. A custom fixture consisting of a six-axis force/torque sensor and motion sensor was attached to tibial diaphysis to measure manually applied torques and joint angles by the surgeon. Following dislocation, the torques generated to visualize the acetabulum and proximal femur were assessed after sequential release of the joint capsule and short external rotators. Following initial exposure, the ischiofemoral ligament (7 to 8 o'clock) was the largest restrictor of exposure of the acetabulum, contributing to a mean 25% of overall external rotational restraint. The ischiofemoral ligament (10 to 12 o'clock) was the largest restrictor of exposure of the proximal femur, contributing to 25% of overall extension restraint. Releasing the short external rotators had minimal contribution in torque generated during joint exposure (≤ 5%). Adequate exposure of both proximal femur and acetabulum may be achieved with minimal torque by performing a full proximal circumferential capsulotomy while preserving short external rotators. The joint torque generated and exposure achieved is dependent on patient factors; therefore, some cases may necessitate further releases.

Motion Picture Analysis: A Mechanical Study of Tennis Players during Forehand and Backhand Strokes

Objectives: The purpose of this article is to utilize video images for the examination of lower limb biomechanics in tennis players while executing forehand and backhand strokes, providing a reference for training. Methods: This article provides a brief introduction to forehand and backhand strokes in the sport of tennis. Subsequently, a biomechanical analysis of the lower limbs during forehand and backhand strokes was conducted on ten level 2 tennis players and ten specialized tennis students at XX Sports University. Findings: Level 2 athletes who have undergone a long training exhibited higher linear velocity and joint torque in the lower-limb joints during the preparatory and striking phases of forehand and backhand strokes. Additionally, they exhibited more pronounced surface electromyographic signals in the rectus femoris muscle of the lower limbs. Novelty:The novelty of this article lies in the use of video imagery, a non-contact and non-intrusive method that does not affect the athletes' movements, to study the biomechanics of their lower limbs. Doi: 10.28991/HIJ-2024-05-01-07 Full Text: PDF

Analysis of the comparison between concentric and eccentric muscle strength in the bilateral knee joint of elite female volleyball players

<p>目的：本研究目的為探討優秀女子排球選手在雙側膝關節伸展與屈曲動作肌力與肌力平衡特徵之差異。方法：以等速肌力測量儀檢測參與者雙側膝關節之力矩，研究參與者為 16 名大專公開一級女子排球選手。統計分析以成對樣本t-tset比較女子排球選手在雙側膝關節伸屈肌力矩之差異及傳統式腿後肌與四頭肌比值 (hamstring to quadriceps strength ratio, H/Q 比值) 與功能性 H/Q 比值的差異，顯著水準訂為α ＝ .05。結果：排球選手在雙側膝關節的伸屈肌向心最大力矩中，只有在 60 °/s 時的伸肌未達顯著差異，其餘向心最大力矩皆有達顯著差異，且慣用側大於非慣用側；在雙側膝關節肌力之伸屈肌離心最大力矩與傳統式 H/Q 比值皆未達顯著差異，傳統式 H/Q 比值雖未達顯著差異，但都低於理想的安全值；在功能性比值方面，60 °/s 時伸、屈動作皆未達顯著差異，而 180 °/s 時伸展與屈曲動作則皆達到顯著差異，且非慣用側大於慣用側。結論：參與者應加強雙側的腿後肌群向心力矩，以提高傳統式 H/Q 比值，降低受傷的風險。功能性比值在伸展與屈曲動作的爆發力矩皆出現差異，這與排球攻擊動作落地時以非慣用側著地緩衝的特性有關。因此，應重視非慣用側的肌力訓練，以降低受傷的風險，更進一步提升選手攻擊的能力。</p> <p> </p><p>Purpose: The purpose of this study was to investigate the differences in muscular strength and muscle balance characteristics in bilateral knee joint flexion-extension movements of elite female volleyball players. Methods: The study utilized the isokinetic dynamometer to measure the torque of the knee joint in 16 collegiate division Ⅰ female volleyball players. Statistical analysis was us-ing paired sample t-tests to compare the differences in knee joint flexion-extension torque, tradi-tional H/Q ratio(hamstring to quadriceps strength ratio, H/Q ratio) and functional H/Q ratio be-tween the dominant and non-dominant sides, with a significance level set at α = .05. Results: The study found that in the concentric maximum torque of knee joint flexion-extension muscles, sig-nificant differences were observed at all angular velocities except for the extension muscle at 60°/s. The dominant side exhibited greater torque than the non-dominant side. However, there were no significant differences in eccentric maximum torque and traditional H/Q ratio of knee joint muscles. Although the traditional H/Q ratio did not show significant differences, it remained below the ideal safety value. Regarding functional H/Q ratio, there were no significant differences in both flexion and extension movements at 60°/s, while at 180°/s, significant differences were observed in both flexion and extension movements, with the non-dominant side exhibiting greater values than the dominant side. Conclusion: Participants should enhance the concentric force of the traditional H/Q ratio to reduce the risk of injury. Discrepancies in functional ratios are evident in the torque generated during extension and flexion movements, attributed to the characteristic landing pattern, which involves buffering on the non-dominant side during volleyball attacking actions. Therefore, prioritizing strength training on the non-dominant side is crucial to mitigate injury risks and further enhance athletes’ attacking capabilities.</p> <p> </p>

A Hybrid Method Combining Data-Driven and Model-Based Algorithms for External Force-Sensing and Haptics Control of Cable-Pulley-Driven Surgical Robotic Manipulator

Abstract The implementation of the high-precision tracking control and external force-sensing ability of a manipulator is important for achieving refined surgical robot operation. In this paper, a hybrid method based on data-driven and model-based algorithms is proposed for the manipulator of a cable-pulley-driven surgical robot. This method integrates an artificial neural network and a dynamic model rotation angle estimation, and a full closed-loop control architecture is further constructed. The algorithm compensates for the hysteresis of the joint angle and effectively improves the tracking control precision. Based on the architecture, the external force estimator (EFE) using a joint torque disturbance observer and the force interaction teleoperation control strategy using a direct force feedback framework (DFF) are implemented. In the force loading experiment, it was shown that the EFE performs well for static and dynamic force estimation, and the teleoperated haptic control experiment showed that the DFF-EFE-based system has a high position-tracking accuracy with real-time external force-sensing ability.