Research on a Calculation Model of Ankle-Joint-Torque-Based sEMG.

The purpose of this article is to establish a prediction model of joint movements and realize the prediction of joint movemenst, and the research results are of reference value for the development of the rehabilitation equipment. This will be carried out by analyzing the impact of surface electromyography (sEMG) on ankle movements and using the Hill model as a framework for calculating ankle joint torque. The table and scheme used in the experiments were based on physiological parameters obtained through the model. Data analysis was performed on ankle joint angle signal, movement signal, and sEMG data from nine subjects during dorsiflexion/flexion, varus, and internal/external rotation. The Hill model was employed to determine 16 physiological parameters which were optimized using a genetic algorithm. Three experiments were carried out to identify the optimal model to calculate torque and root mean square error. The optimized model precisely calculated torque and had a root mean square error of under 1.4 in comparison to the measured torque. Ankle movement models predict torque patterns with accuracy, thereby providing a solid theoretical basis for ankle rehabilitation control. The optimized model provides a theoretical foundation for precise ankle torque forecasts, thereby improving the efficacy of rehabilitation robots for the ankle.

Estimation of Ground Reaction Forces during Sports Movements by Sensor Fusion from Inertial Measurement Units with 3D Forward Dynamics Model.

Rotational jumps are crucial techniques in sports competitions. Estimating ground reaction forces (GRFs), a constituting component of jumps, through a biomechanical model-based approach allows for analysis, even in environments where force plates or machine learning training data would be impossible. In this study, rotational jump movements involving twists on land were measured using inertial measurement units (IMUs), and GRFs and body loads were estimated using a 3D forward dynamics model. Our forward dynamics and optimization calculation-based estimation method generated and optimized body movements using cost functions defined by motion measurements and internal body loads. To reduce the influence of dynamic acceleration in the optimization calculation, we estimated the 3D orientation using sensor fusion, comprising acceleration and angular velocity data from IMUs and an extended Kalman filter. As a result, by generating cost function-based movements, we could calculate biomechanically valid GRFs while following the measured movements, even if not all joints were covered by IMUs. The estimation approach we developed in this study allows for measurement condition- or training data-independent 3D motion analysis.

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.

Lower Limb Joint Torque Prediction Using Long Short-Term Memory Network and Gaussian Process Regression.

The accurate prediction of joint torque is required in various applications. Some traditional methods, such as the inverse dynamics model and the electromyography (EMG)-driven neuromusculoskeletal (NMS) model, depend on ground reaction force (GRF) measurements and involve complex optimization solution processes, respectively. Recently, machine learning methods have been popularly used to predict joint torque with surface electromyography (sEMG) signals and kinematic information as inputs. This study aims to predict lower limb joint torque in the sagittal plane during walking, using a long short-term memory (LSTM) model and Gaussian process regression (GPR) model, respectively, with seven characteristics extracted from the sEMG signals of five muscles and three joint angles as inputs. The majority of the normalized root mean squared error (NRMSE) values in both models are below 15%, most Pearson correlation coefficient (R) values exceed 0.85, and most decisive factor (R2) values surpass 0.75. These results indicate that the joint prediction of torque is feasible using machine learning methods with sEMG signals and joint angles as inputs.

Feasibility of Overground Gait Training Using a Joint-Torque-Assisting Wearable Exoskeletal Robot in Children with Static Brain Injury.

Pediatric gait disorders are often chronic and accompanied by various complications, which challenge rehabilitation efforts. Here, we retrospectively analyzed the feasibility of overground robot-assisted gait training (RAGT) using a joint-torque-assisting wearable exoskeletal robot. In this study, 17 children with spastic cerebral palsy, cerebellar ataxia, and chronic traumatic brain injury received RAGT sessions. The Gross Motor Function Measure (GMFM), 6-min walk test (6 MWT), and 10-m walk test (10 MWT) were performed before and after intervention. The oxygen rate difference between resting and training was performed to evaluate the intensity of training in randomly selected sessions, while the Quebec User Evaluation of Satisfaction with assistive Technology 2.0 assessment was performed to evaluate its acceptability. A total of four of five items in the GMFM, gait speed on the 10 MWT, and total distance on the 6 MWT showed statistically significant improvement (p < 0.05). The oxygen rate was significantly higher during the training versus resting state. Altogether, six out of eight domains showed satisfaction scores more than four out of five points. In conclusion, overground training using a joint-torque-assisting wearable exoskeletal robot showed improvement in gross motor and gait functions after the intervention, induced intensive gait training, and achieved high satisfaction scores in children with static brain injury.

Concurrent Validity of Lower Limb Muscle Strength by Handheld Dynamometry in Children 7 to 11 Years Old.

CONTEXT: The assessment of pediatric muscle strength is necessary in a range of applications, including rehabilitation programs. Handheld dynamometry (HHD) is considered easy to use, portable, and low cost, but validity to measure lower limb muscle strength in children has not been assessed. OBJECTIVE: To determine the concurrent validity of lower limb torque from HHD compared with isokinetic dynamometry (ID) in children aged from 7 to 11 years old. DESIGN: A descriptive assessment of concurrent validity of lower limb joint torques from HHD compared with ID. METHODS: Sixty-one typically developing children underwent assessment of maximal hip, knee, and ankle isometric torque by HHD and ID using standardized protocols. Joint positions were selected to represent maximal strength and were replicated between devices. Concurrent validity was determined by Pearson correlation, limits of agreement, and Bland-Altman plots. RESULTS: Correlations between HHD and ID were moderate to large for knee extension (r 95% CI, .39 to .73), small to large for plantar flexion (r 95% CI, .29 to .67), knee flexion (r 95% CI, .16 to .59), hip flexion (r 95% CI, .21 to .57), hip extension (r 95% CI, .18 to .54), and hip adduction (r 95% CI, .12 to .56), and small to moderate for dorsiflexion (r 95% CI, -.11 to .39) and hip abduction (r 95% CI, -.02 to .46). Limits of agreement for all joint torques were greater than 10% indicating large error in HHD measured torque compared with ID. A positive proportional bias was detected for plantarflexion, indicating that HHD underestimated torque to a greater extent in participants with higher torque values. CONCLUSIONS: Maximal torque values from HHD and ID are consistent with those previously reported in the literature. Poor concurrent validity of HHD may have arisen from issues around joint position, joint stabilization, and the experience of the tester to prevent an isokinetic contraction. Pediatric lower limb muscle strength assessed by HHD should be interpreted with caution.

[Dynamics analysis of knee joint during sit-stand movement].

Sit-stand movement is one of the most common movement behaviors of the human body. The knee joint is the main bearing joint of this movement. Thus, the dynamic analysis of knee joint during this movement has deeply positive influences. According to the principle of moment balance, the dynamics of the knee joint during the movement were analyzed. Furthermore, combined with the data obtained from optical motion capture and six-dimensional ground reaction force test, the curve of knee joint torque was calculated. To verify the accuracy of the analysis of dynamic, the human body model was established, the polynomial equations of angle and angular velocity were fitted according to the experimental data, and the knee joint simulation of the movement was carried out. The result revealed that in terms of range and trend, the theoretical data and simulation data were consistent. The relationship between knee joint torque and ground reaction force was revealed based on the variation law of knee joint torque. During the sit-stand movement, the knee joint torque and the ground reaction force were directly proportional to each other, and the ratio was 5 to 6. In the standing process, the acceleration first increased and then decreased and finally increased in reverse, and the maximum knee torque occurred at an angle of about 140°. In the sitting process, the torque was maximized in the initial stage. The results of the dynamics analysis of knee joint during sit-stand movement are beneficial to the optimal design and force feedback control of seated rehabilitation aids, and can provide theoretical guidance for knee rehabilitation training.

Joint Torque Prediction via Hybrid Neuromusculoskeletal Modelling during Gait Using Statistical Ground Reaction Estimates: An Exploratory Study.

Joint torques of lower extremity are important clinical indicators of gait capability. This parameter can be quantified via hybrid neuromusculoskeletal modelling that combines electromyography-driven modelling and static optimisation. The simulations rely on kinematics and external force measurements, for example, ground reaction forces (GRF) and the corresponding centres of pressure (COP), which are conventionally acquired using force plates. This bulky equipment, however, hinders gait analysis in real-world environments. While this portability issue could potentially be solved by estimating the parameters through machine learning, the effect of the estimation errors on joint torque prediction with biomechanical models remains to be investigated. This study first estimated GRF and COP through feedforward artificial neural networks, and then leveraged them to predict lower-limb sagittal joint torques via (i) inverse dynamics and (ii) hybrid modelling. The approach was evaluated on five healthy subjects, individually. The predicted torques were validated with the measured torques, showing that hip was the most sensitive whereas ankle was the most resistive to the GRF/COP estimates for both models, with average metrics values being 0.70 < R2 < 0.97 and 0.069 < RMSE < 0.15 (Nm/kg). This study demonstrated the feasibility of torque prediction based on personalised (neuro)musculoskeletal modelling using statistical ground reaction estimates, thus providing insights into potential real-world mobile joint torque quantification.

Relationship Between Body Segment Mass and Running Performance in Well-Trained Endurance Runners.

This study examined the relationship between body segment mass and running performance in endurance runners. The total (muscle, fat, and bone masses), lean (muscle mass), and fat masses of the leg, arm, and trunk segments in 37 well-trained endurance runners were measured using dual-energy X-ray absorptiometer. The relative segment mass was calculated by normalizing the absolute mass to body mass. There were no significant correlations between absolute total, lean, and fat masses of all 3 segments and personal best 5000-m race time. No significant correlations were also observed between all 3 relative masses of the arm segment and personal best 5000-m race time. In contrast, medium positive correlations were observed between the relative total and lean masses of the leg segment and personal best 5000-m race time (r = .387 and .335, respectively, both P ≤ .031). Furthermore, large negative correlations were observed between the relative total and lean masses of the trunk segment and personal best 5000-m race time (r = -.500 and -.548, respectively, both P ≤ .002). These findings suggest that a mass distribution with smaller leg mass and greater trunk mass may be advantageous for achieving better running performance in endurance runners.

Differences in muscle mechanics underlie divergent optimality criteria between feeding and locomotor systems.

Tetrapod musculoskeletal diversity is usually studied separately in feeding and locomotor systems. However, direct comparisons between these systems promise important insight into how natural selection deploys the same basic musculoskeletal toolkit-connective tissues, bones, nerves, and skeletal muscle-to meet the differing performance criteria of feeding and locomotion. Recent studies using this approach have proposed that the feeding system is optimized for precise application of high forces and the locomotor system is optimized for wide and rapid joint excursions for minimal energetic expenditure. If this hypothesis is correct, then it stands to reason that other anatomical and biomechanical variables within the feeding and locomotor systems should reflect these diverging functions. To test this hypothesis, we compared muscle moment arm lengths, mechanical advantages, and force vector orientations of two jaw elevator muscles (m. temporalis and m. superficial masseter), an elbow flexor (m. brachialis) and extensor (m. triceps- lateral head), and a knee flexor (m. biceps femoris-short head) and extensor (m. vastus lateralis) across 18 species of primates. Our results show that muscles of the feeding system are more orthogonally oriented relative to the resistance arm (mandible) and operate at relatively large moment arms and mechanical advantages. Moreover, these variables show relatively little change across the range of jaw excursion. In contrast, the representative muscles of the locomotor system have much smaller mechanical advantages and, depending on joint position, smaller muscle moment arm lengths and almost parallel orientations relative to the resistance arm. These patterns are consistent regardless of phylogeny, body mass, locomotor mode, and feeding specialization. We argue that these findings reflect fundamental functional dichotomies between tetrapod locomotor and feeding systems. By organizing muscles in a manner such that moment arms and mechanical advantage are relatively small, the locomotor system can produce broad joint excursions and high angular velocities with only small muscular contraction. As such, the anatomical organization of muscles within the limbs allows striding animals to move relatively rapidly and with minimal energetic expenditure. In contrast, the anatomical configuration of muscles in the feeding system, at least m. superficial masseter and m. temporalis, favors their force-producing capacity at the expense of excursion and velocity.

Inertial measurement unit-based hip flexion test as an indicator of sprint performance.

This study aimed 1) to examine the validity of inertial measurement unit (IMU)-based hip flexion strength test, and 2) to investigate the hip flexion strength test as an indicator of sprint performance. Eight males performed five repeated hip flexion-extension, while leg motion was recorded using an IMU and a motion capture system (Mocap). As the second experiment, 24 male athletes performed the IMU-based hip flexion strength test and sprinted 50 m, during which step-to-step ground reaction force (GRF) was recorded. The strength test variables were calculated using IMU and Mocap data including angular impulse, mean moment, and positive and negative work and power. Using GRF data, step-to-step spatiotemporal variables were obtained. The results showed high intra-class correlation coefficient and correlation coefficient (both >0.909) between IMU and Mocap for angular impulse, mean moment, positive work and power. The hip flexion mean moment showed significant correlation with running speed from the 5th-8th step section onwards. The angular impulse, mean moment, positive work and power are recommended to be used for the IMU-based hip flexion strength test variables in terms of accuracy and validity. Moreover, the proposed IMU-based hip flexion strength test can be an indicator for better sprinting performance.

Dependent-Gaussian-Process-Based Learning of Joint Torques Using Wearable Smart Shoes for Exoskeleton.

Estimating the joint torques of lower limbs in human gait is a highly challenging task and of great significance in developing high-level controllers for lower-limb exoskeletons. This paper presents a dependent Gaussian process (DGP)-based learning algorithm for joint-torque estimations with measurements from wearable smart shoes. The DGP was established to perform data fusion, and serves as the mathematical foundation to explore the correlations between joint kinematics and joint torques that are embedded deeply in the data. As joint kinematics are used in the training phase rather than the prediction process, the DGP model can realize accurate predictions in outdoor activities by using only the smart shoe, which is low-cost, nonintrusive for human gait, and comfortable to wearers. The design methodology of dynamic specific kernel functions is presented in accordance to prior knowledge of the measured signals. The designed composite kernel functions can be used to model multiple features at different scales, and cope with the temporal evolution of human gait. The statistical nature of the proposed DGP model and the composite kernel functions offer superior flexibility for time-varying gait-pattern learning, and enable accurate joint-torque estimations. Experiments were conducted with five subjects, whose results showed that it is possible to estimate joint torques under different trained and untrained speed levels. Comparisons were made between the proposed DGP and Gaussian process (GP) models. Obvious improvements were achieved when all DGP r2 values were higher than those of GP.

The Relationship Between Surface Electromyographic Activity and Torque Production of the Infraspinatus Muscle in Shoulder Rehabilitation Exercises.

In current rehabilitation practice, exercise selection is commonly based on the amount of muscle recruitment demonstrated by electromyographic (EMG) analysis. A preponderance of evidence supports the concept that EMG of a muscle and torque output are positively correlated. This study was designed to investigate the relationship between surface EMG activity of the infraspinatus and torque production during exercises involving shoulder external rotation (ER). A total of 30 participants (average age = 24.6 y) performed maximum voluntary isometric contraction of ER at 5 points within the range of motion of 3 shoulder exercise positions with concomitant surface EMG recording. As a maximal internally rotated position was approached, maximum ER torque and minimum or near-minimum EMG recruitment were demonstrated. Conversely, at maximally externally rotated positions, EMG activity was greatest and torque values were lowest. An inverse relationship between joint torque output and EMG activity was established in each of the 3 exercises. The inverse relationship between EMG activity and torque output during Shoulder ER suggests that there may be additional factors warranting consideration during exercise selection. Further research may be needed to determine the relative value of electrical activity versus torque output to optimize the selection of rehabilitative exercises.

Influences of Lateral Jump Smash Actions in Different Situations on the Lower Extremity Load of Badminton Players.

Badminton atypical actions and hitting movements often occur during the game; therefore, many special footwork methods have been developed to facilitate the rapid movements required to hit the shuttlecock, including quick turning and jumping and quick directional change movements. Studies have shown that the majority of badminton sport injuries occur in the lower extremity joints of athletes. The purpose of this study was to investigate the influences of hitting motion and unanticipated hitting direction on landing mechanics after backhand lateral jump smashing and landing to analyze joint stiffness and torque changes in three lower extremity joints. Recruited sixteen badminton athletes.The capture frequency of the Vicon Motion System (300Hz), Kistler force platform (1500Hz) and Vicon Nexus Version 1.8.5 software were used simultaneously to capture the kinematic and kinetic parameter of backhand side lateral jump smash footwork. The swing actions were divided into two situations, shadow (footwork and racket swinging practice without targets) and hitting (footwork and stroke shuttlecock) actions, whereas the directions were divided into directional and non-directional. Two-way repeated measures ANOVA with the LSD correction was used to compare the differences among the four conditions. The significance level was set to a = 0.05. Results shown that, at the peak of torque, the ankle plantar flexion of the non-directional shadow (p < 0.05) were greater than that of directional shadow (p < 0.05); meantime, ankle torque change of non-directional shadow (p < 0.05) and directional hitting (p < 0.05) was lower than that of non-directional hitting, but the non-directional hitting was larger compared to non-directional shadow (p < 0.05) at the maximum vertical GRF. The hip extension at peak of torque of directional hitting were larger than that of non-directional shadow (p < 0.05). The shadow actions hip flexion angle was larger than that of directional hitting at initial contact, but the non-directional hitting hip abduction was has the significant difference among all the conditioning. The hip flexion angle of non-directional shadow was larger than that of directional hitting (p < 0.05), the hip abduction angle of the non-directional hitting was greater than that of non-directional shadow (p < 0.05) at the peak VGRF. Elite badminton players execute different training movements; the joint stiffness was in the same state. In the hitting actions has greater ankle and hip joint torque than shadow actions. The badminton player was change joint range of motion to adjust lower limbs stiffness.

Motor control of an insect leg during level and incline walking.

During walking, the leg motor system must continually adjust to changes in mechanical conditions, such as the inclination of the ground. To understand the underlying control, it is important to know how changes in leg muscle activity relate to leg kinematics (movements) and leg dynamics (forces, torques). Here, we studied these parameters in hindlegs of stick insects (Carausius morosus) during level and uphill/downhill (±45 deg) walking, using a combination of electromyography, 3D motion capture and ground reaction force measurements. We find that some kinematic parameters including leg joint angles and body height vary across walking conditions. However, kinematics vary little compared with dynamics: horizontal leg forces and torques at the thorax-coxa joint (leg protraction/retraction) and femur-tibia joint (leg flexion/extension) tend to be stronger during uphill walking and are reversed in sign during downhill walking. At the thorax-coxa joint, the different mechanical demands are met by adjustments in the timing and magnitude of antagonistic muscle activity. Adjustments occur primarily in the first half of stance after the touch-down of the leg. When insects transition from level to incline walking, the characteristic adjustments in muscle activity occur with the first step of the leg on the incline, but not in anticipation. Together, these findings indicate that stick insects adjust leg muscle activity on a step-by-step basis so as to maintain a similar kinematic pattern under different mechanical demands. The underlying control might rely primarily on feedback from leg proprioceptors signaling leg position and movement.

Biomechanical parameters of the elbow stretch reflex in chronic hemiparetic stroke.

We sought to determine the relative velocity sensitivity of stretch reflex threshold angle and reflex stiffness during stretches of the paretic elbow joint in individuals with chronic hemiparetic stroke, and to provide guidelines to streamline spasticity assessments. We applied ramp-and-hold elbow extension perturbations ranging from 15 to 150°/s over the full range of motion in 13 individuals with hemiparesis. After accounting for the effects of passive mechanical resistance, we modeled velocity-dependent reflex threshold angle and torque-angle slope to determine their correlation with overall resistance to movement. Reflex stiffness exhibited substantially greater velocity sensitivity than threshold angle, accounting for ~ 74% (vs. ~ 15%) of the overall velocity-dependent increases in movement resistance. Reflex stiffness is a sensitive descriptor of the overall velocity-dependence of movement resistance in spasticity. Clinical spasticity assessments can be streamlined using torque-angle slope, a measure of reflex stiffness, as their primary outcome measure, particularly at stretch velocities greater than 100°/s.

Using Torque-Angle and Torque-Velocity Models to Characterize Elbow Mechanical Function: Modeling and Applied Aspects.

Characterization of muscle mechanism through the torque-angle and torque-velocity relationships is critical for human movement evaluation and simulation. in vivo determination of these relationships through dynamometric measurements and modeling is based on physiological and mathematical aspects. However, no investigation regarding the effects of the mathematical model and the physiological parameters underneath these models was found. The purpose of the current study was to compare the capacity of various torque-angle and torque-velocity models to fit experimental dynamometric measurement of the elbow and provide meaningful mechanical and physiological information. Therefore, varying mathematical function and physiological muscle parameters from the literature were tested. While a quadratic torque-angle model seemed to increase predicted to measured elbow torque fitting, a new power-based torque-velocity parametric model gave meaningful physiological values to interpret with similar fitting results to a classical torque-velocity model. This model is of interest to extract modeling and clinical knowledge characterizing the mechanical behavior of such a joint.

Comparison of vibrotactile and joint-torque feedback in a myoelectric upper-limb prosthesis.

BACKGROUND: Despite the technological advancements in myoelectric prostheses, body-powered prostheses remain a popular choice for amputees, in part due to the natural sensory advantage they provide. Research on haptic feedback in myoelectric prostheses has delivered mixed results. Furthermore, there is limited research comparing various haptic feedback modalities in myoelectric prostheses. In this paper, we present a comparison of the feedback intrinsically present in body-powered prostheses (joint-torque feedback) to a commonly proposed feedback modality for myoelectric prostheses (vibrotactile feedback). In so doing, we seek to understand whether the advantages of kinesthetic feedback present in body-powered prostheses translate to myoelectric prostheses, and whether there are differences between kinesthetic and cutaneous feedback in prosthetic applications. METHODS: We developed an experimental testbed that features a cable-driven, voluntary-closing 1-DoF prosthesis, a capstan-driven elbow exoskeleton, and a vibrotactile actuation unit. The system can present grip force to users as either a flexion moment about the elbow or vibration on the wrist. To provide an equal comparison of joint-torque and vibrotactile feedback, a stimulus intensity matching scheme was utilized. Non-amputee participants (n=12) were asked to discriminate objects of varying stiffness with the prosthesis in three conditions: no haptic feedback, vibrotactile feedback, and joint-torque feedback. RESULTS: Results indicate that haptic feedback increased discrimination accuracy over no haptic feedback, but the difference between joint-torque feedback and vibrotactile feedback was not significant. In addition, our results highlight nuanced differences in performance depending on the objects' stiffness, and suggest that participants likely pay less attention to incidental cues with the addition of haptic feedback. CONCLUSION: Even when haptic feedback is not modality matched to the task, such as in the case of vibrotactile feedback, performance with a myoelectric prosthesis can improve significantly. This implies it is possible to achieve the same benefits with vibrotactile feedback, which is cheaper and easier to implement than other forms of feedback.

Simultaneous Floating-Base Estimation of Human Kinematics and Joint Torques.

The paper presents a stochastic methodology for the simultaneous floating-base estimation of the human whole-body kinematics and dynamics (i.e., joint torques, internal and external forces). The paper builds upon our former work where a fixed-base formulation had been developed for the human estimation problem. The presented approach is validated by presenting experimental results of a health subject equipped with a wearable motion tracking system and a pair of shoes sensorized with force/torque sensors while performing different motion tasks, e.g., walking on a treadmill. The results show that joint torque estimates obtained by using floating-base and fixed-base approaches match satisfactorily, thus validating the present approach.

A Clamping Force Estimation Method Based on a Joint Torque Disturbance Observer Using PSO-BPNN for Cable-Driven Surgical Robot End-Effectors.

The ability to sense external force is an important technique for force feedback, haptics and safe interaction control in minimally-invasive surgical robots (MISRs). Moreover, this ability plays a significant role in the restricting refined surgical operations. The wrist joints of surgical robot end-effectors are usually actuated by several long-distance wire cables. Its two forceps are each actuated by two cables. The scope of force sensing includes multidimensional external force and one-dimensional clamping force. This paper focuses on one-dimensional clamping force sensing method that do not require any internal force sensor integrated in the end-effector's forceps. A new clamping force estimation method is proposed based on a joint torque disturbance observer (JTDO) for a cable-driven surgical robot end-effector. The JTDO essentially considers the variations in cable tension between the actual cable tension and the estimated cable tension using a Particle Swarm Optimization Back Propagation Neural Network (PSO-BPNN) under free motion. Furthermore, a clamping force estimator is proposed based on the forceps' JTDO and their mechanical relations. According to comparative analyses in experimental studies, the detection resolutions of collision force and clamping force were 0.11 N. The experimental results verify the feasibility and effectiveness of the proposed clamping force sensing method.