An Improved Extreme Learning Machine (ELM) Algorithm for Intent Recognition of Transfemoral Amputees With Powered Knee Prosthesis.

To overcome the challenges posed by the complex structure and large parameter requirements of existing classification models, the authors propose an improved extreme learning machine (ELM) classifier for human locomotion intent recognition in this study, resulting in enhanced classification accuracy. The structure of the ELM algorithm is enhanced using the logistic regression (LR) algorithm, significantly reducing the number of hidden layer nodes. Hence, this algorithm can be adopted for real-time human locomotion intent recognition on portable devices with only 234 parameters to store. Additionally, a hybrid grey wolf optimization and slime mould algorithm (GWO-SMA) is proposed to optimize the hidden layer bias of the improved ELM classifier. Numerical results demonstrate that the proposed model successfully recognizes nine daily motion modes including low-, mid-, and fast-speed level ground walking, ramp ascent/descent, sit/stand, and stair ascent/descent. Specifically, it achieves 96.75% accuracy with 5-fold cross-validation while maintaining a real-time prediction time of only 2 ms. These promising findings highlight the potential of onboard real-time recognition of continuous locomotion modes based on our model for the high-level control of powered knee prostheses.

The Fundamental Property of Human Leg During Walking: Linearity and Nonlinearity.

Leg properties have been involved in the broad study of human walking from mechanical energy to motion prediction of robotics. However, the variable leg elasticities and their functions during gait have not been fully explored. This study presented that the fundamental leg properties during human walking comprise axial stiffness, rest leg length, tangential stiffness and force-free leg angles. We measured the axial force-leg length and tangential force-leg angle data in eight participants (mean ± s.d. age 24.6 ± 3.0 years, mass 68.2 ± 6.8 kg, height 177.5 ± 5.2 cm) at three self-selected walking speeds (slow: 1.25 ± 0.22, normal: 1.48 ± 0.28, fast: 1.75 ± 0.32 m/s) on two different contact conditions (fixed and moving). After obtaining these gait measurements, we extracted the linear and nonlinear leg elasticities during human walking by using a minimum root-mean-square fitting. We found that the axial stiffness of nonlinear elasticity (fixed condition: 7.1-8.0, moving condition: 21.3-22.6) is higher than that of the linear elasticity (fixed condition: 5.0-5.7, moving condition: 15.2-16.5). The tangential stiffness behaves different during four stance phases of gait, with the highest (linear: 2.52-3.72, nonlinear: 1.71-2.01, in moving condition) occurred at early stance and second highest at late stance, followed by two stiffnesses in mid-stance. For both linearity and nonlinearity, the axial stiffness and rest length are independent of walking speeds in both contact conditions, while the tangential stiffness and contact angles are independent of walking speeds only in moving condition. Regardless of walking speed, elasticity and contact condition, the force-free contact angle at mid-stance is maintained at average of 82.2 °. This paper first demonstrates the mechanical walking leg property from both axial and tangential aspects. The findings provide insight into the fundamental properties including linearity and nonlinearity of human leg during locomotion for stability analysis and precise motion prediction of robotics and rehabilitation exoskeletons.

X-crossing pneumatic artificial muscles.

Artificial muscles are promising in soft exoskeletons, locomotion robots, and operation machines. However, their performance in contraction ratio, output force, and dynamic response is often imbalanced and limited by materials, structures, or actuation principles. We present lightweight, high-contraction ratio, high-output force, and positive pressure-driven X-crossing pneumatic artificial muscles (X-PAMs). Unlike PAMs, our X-PAMs harness the X-crossing mechanism to directly convert linear motion along the actuator axis, achieving an unprecedented 92.9% contraction ratio and an output force of 207.9 Newtons per kilogram per kilopascal with excellent dynamic properties, such as strain rate (1603.0% per second), specific power (5.7 kilowatts per kilogram), and work density (842.9 kilojoules per meter cubed). These properties can overcome the slow actuation of conventional PAMs, providing robotic elbow, jumping robot, and lightweight gripper with fast, powerful performance. The robust design of X-PAMs withstands extreme environments, including high-temperature, underwater, and long-duration actuation, while being scalable to parallel, asymmetric, and ring-shaped configurations for potential applications.

Modified Nonlinear Hysteresis Approach for a Tactile Sensor.

Soft tactile sensors based on piezoresistive materials have large-area sensing applications. However, their accuracy is often affected by hysteresis which poses a significant challenge during operation. This paper introduces a novel approach that employs a backpropagation (BP) neural network to address the hysteresis nonlinearity in conductive fiber-based tactile sensors. To assess the effectiveness of the proposed method, four sensor units were designed. These sensor units underwent force sequences to collect corresponding output resistance. A backpropagation network was trained using these sequences, thereby correcting the resistance values. The training process exhibited excellent convergence, effectively adjusting the network's parameters to minimize the error between predicted and actual resistance values. As a result, the trained BP network accurately predicted the output resistances. Several validation experiments were conducted to highlight the primary contribution of this research. The proposed method reduced the maximum hysteresis error from 24.2% of the sensor's full-scale output to 13.5%. This improvement established the approach as a promising solution for enhancing the accuracy of soft tactile sensors based on piezoresistive materials. By effectively mitigating hysteresis nonlinearity, the capabilities of soft tactile sensors in various applications can be enhanced. These sensors become more reliable and more efficient tools for the measurement and control of force, particularly in the fields of soft robotics and wearable technology. Consequently, their widespread applications extend to robotics, medical devices, consumer electronics, and gaming. Though the complete elimination of hysteresis in tactile sensors may not be feasible, the proposed method effectively modifies the hysteresis nonlinearity, leading to improved sensor output accuracy.

Design, Manufacture, and Experimental Validation of a Hydraulic Semi-Active Knee Prosthesis.

In this article, a new hydraulic semi-active knee (HSAK) prosthesis is proposed. Compared with knee prostheses driven by hydraulic-mechanical coupling or electromechanical systems, we novelly combine independent active and passive hydraulic subsystems to solve the incompatibility between low passive friction and high transmission ratio of current semi-active knees. The HSAK not only has the low friction to follow the intentions of users, but also performs adequate torque output. Moreover, the rotary damping valve is meticulously designed to effectively control motion damping. The experimental results demonstrate the HSAK combines the advantages of both passive and active prostheses, including the flexibility of passive prostheses, as well as the stability and the sufficient active torque of active prostheses. The maximum flexion angle in level walking is about 60°, and the peak output torque in stair ascent is greater than 60Nm. Relative to the daily use of prosthetics, the HSAK improves gait symmetry on the affected side and contributes to the amputees better maintain daily activities.

Energy Flow and Functional Behavior of Individual Muscles at Different Speeds During Human Walking.

Understanding the distinct functions of human muscles could not only help professionals obtain insights into the underlying mechanisms that we accommodate compromised neuromuscular system, but also assist engineers in developing rehabilitation devices. This study aims to determine the contribution of major muscle and the energy flow in the human musculoskeletal system at four sub-phases (collision, rebound, preload, push-off) during the stance of walking at different speeds. Gait experiments were performed with three self-selected speeds: slow, normal, and fast. Muscle forces and mechanical work were calculated by using a subject-specified musculoskeletal model. The functions of individual muscles were characterized as four functional behaviors (strut, spring, motor, damper), which were determined based on the mechanical energy. The results showed that during collision, hip flexors (iliacus and psoas major) and ankle dorsiflexors (anterior tibialis) were the most dominant muscles in buffering the stride with energy absorption; during rebound, the posterior muscles (gluteus maximus, gastrocnemius, posterior tibialis, soleus) contributed the most to energy generation; during preload, energy for preparing push-off was mainly absorbed by the muscles surrounding knee (vastus, semimembranosus, semitendinosus); during push-off, ankle plantar flexors (gastrocnemius, soleus, posterior tibialis, peroneus muscles, flexor digitorum, flexor hallucis) mainly behaved to generate energy for forward propulsion. With increased walking speed, additional energy (almost 400%) from harder stride was mainly absorbed by the flexor muscles. Hip extensors and adductors transferred more energy (around 150%) to the distal segments during rebound. Soleus and gastrocnemius muscles generated more energy (about 75%) to the proximal segments for propulsion. Along with our previous study of joint-level energy analysis, these findings could assist better understanding of human musculoskeletal behaviors during locomotion and provide principles for the bio-design of related assistive devices from motors performance enhancement to rehabilitation such as exoskeleton and prosthesis.

Mechanisms and component design of prosthetic knees: A review from a biomechanical function perspective.

Prosthetic knees are state-of-the-art medical devices that use mechanical mechanisms and components to simulate the normal biological knee function for individuals with transfemoral amputation. A large variety of complicated mechanical mechanisms and components have been employed; however, they lack clear relevance to the walking biomechanics of users in the design process. This article aims to bridge this knowledge gap by providing a review of prosthetic knees from a biomechanical perspective and includes stance stability, early-stance flexion and swing resistance, which directly relate the mechanical mechanisms to the perceived walking performance, i.e., fall avoidance, shock absorption, and gait symmetry. The prescription criteria and selection of prosthetic knees depend on the interaction between the user and prosthesis, which includes five functional levels from K0 to K4. Misunderstood functions and the improper adjustment of knee prostheses may lead to reduced stability, restricted stance flexion, and unnatural gait for users. Our review identifies current commercial and recent studied prosthetic knees to provide a new paradigm for prosthetic knee analysis and facilitates the standardization and optimization of prosthetic knee design. This may also enable the design of functional mechanisms and components tailored to regaining lost functions of a specific person, hence providing individualized product design.

Analysis and validation of a 3D finite element model for human forearm fracture.

Most researchers have performed finite element (FE) analysis of the human forearm fracture by exploring the strength and load transmission of the bones. However, few studies concentrated a complete simulation of the whole forearm complex including ligaments. This paper aims to investigate the load transmission through the bones, contact stress at the joints and strain in the ligaments by using an elaborate FE model, further validating the fracture condition for human forearm. The interosseous ligament was separated into three regions based on the distance to the proximal and distal ends. The FE simulation results were slightly more or less than a previous experimental data in the literature, but generally provided a close approximation of the bone and ligament behaviors. Compared with the experiment results under different loading conditions, maximum contact stress at the proximal radio ulnar joint (PRUJ) and distal radio ulnar joint (DRUJ) of the simulations was higher with an average of 13.4%, and peak strain in the interosseous ligament (IOL) was lower with an average of 11.0%. Under 10 kg load, the maximum stress in the radius (2.25 MPa) was less than double the value in the ulna (1.43 MPa). Finally, the FE model has been validated with the onset and location of the Colles' fracture in the literature. This study will provide a great benefit in terms of surgical and medical applications related to forearm fracture that require an extensive knowledge of the behavior of the bones and ligaments under various loading conditions.

From Skin Mechanics to Tactile Neural Coding: Predicting Afferent Neural Dynamics During Active Touch and Perception.

First order cutaneous neurons allow object recognition, texture discrimination, and sensorimotor feedback. Their function is well-investigated under passive stimulation while their role during active touch or sensorimotor control is understudied. To understand how human perception and sensorimotor controlling strategy depend on cutaneous neural signals under active tactile exploration, the finite element (FE) hand and Izhikevich neural dynamic model were combined to predict the cutaneous neural dynamics and the resulting perception during a discrimination test. Using in-vivo microneurography generated single afferent recordings, 75% of the data was applied for the model optimization and another 25% was used for validation. By using this integrated numerical model, the predicted tactile neural signals of the single afferent fibers agreed well with the microneurography test results, achieving the out-of-sample values of 0.94 and 0.82 for slowly adapting type I (SAI) and fast adapting type I unit (FAI) respectively. Similar discriminating capability with the human subject was achieved based on this computational model. Comparable performance with the published numerical model on predicting the cutaneous neural response under passive stimuli was also presented, ensuring the potential applicability of this multi-level numerical model in studying the human tactile sensing mechanisms during active touch. The predicted population-level 1st order afferent neural signals under active touch suggest that different coding strategies might be applied to the afferent neural signals elicited from different cutaneous neurons simultaneously.

Reproduction of the Mechanical Behavior of Ligament and Tendon for Artificial Joint Using Bioinspired 3D Braided Fibers.

The level of joint laxity, which is an indicator of accurate diagnosis for musculoskeletal conditions is manually determined by a physician. Studying joint laxity via artificial joints is an efficient and economical way to improve patient experience and joint proficiency. However, most of study focus on the joint geometry but are inadequate with regard to the tailored mechanical properties of soft tissues. On the basis of collagen fibril deformation, this study proposes bioinspired 3D fibers braided from polyethene multifilament for the reproduction of the controlled nonlinear behavior of ligaments and tendons. Four braided bands are designed, all showing biological behaviors. Two knot-based bands exhibit large toe strains of 10.98% and 5.33% but low linear modulus of 239.84 MPa and 826.05 MPa. The other two bands without knots exhibit lower toe strains of 1.61% and 1.52% but high linear modulus of 2605.27 MPa and 2050.74 MPa. Empirical formulas for braiding parameters (wales and courses) and mechanical properties are expressed to provide a theoretical basis for the mimicry of different tissues in the human body by artificial joints. All parameters have significant effects on the linear region of the load-displacement curve of a fiber due to braided structure, while changing the number of wales facilitates a major contribution to the toe region. A biofidelic human knee has been successfully reconstructed by using bioinspired 3D braided fibers. This study demonstrates that the nonlinear mechanical properties of soft tissues can be replicated by bioinspired 3D braided fibers, further yielding the design of more biomechanically realistic artificial joints.

Biomechanical Analysis of the Effect of the Finger Extensor Mechanism on Hand Grasping Performance.

Quantifying the effect of routing and topology of the inter-connected finger extensor mechanism on hand grasping performances is a long-standing research problem for the better clinical diagnosis, surgical planning and biomimetic hand development. However, it is technically demanding to measure the hand performance parameters such as the contact forces and contact area during hand manipulation. It is also difficult to replicate human hand performance through the physical hand model due to its sophisticated musculotendinous structure. In this study, an experimental validated subject-specific finite element (FE) human hand model was used for the first time to quantify the influence of different tendon topologies and material properties on hand grasping quality. It is found that the grasping quality is reduced by 15.94% and 8.54% if there are no extensor hood and lateral band respectively, and the former plays a more important role in transmitting forces and maintaining grasping qualities than the latter. Excluding extensor hood in the topology causes more reductions in hand contact pressure and contact area than omitting lateral band. 7.5% of the grasping quality is lost due to a softened tendon with half of its original Young's Modulus. Hardened extensor tendon does increase the grasping quality, but the enhancing effect tends to level off once the tendon Young's Modulus is increased by more than 50%. These results prove that the lateral band and extensor hood are critical components for maintaining grasping quality. The dexterity and grasping quality of robotic and prosthetic hands could be improved by integrating these two components. There is also no need to use very stiff tendon material as it won't help to effectively enhance the grasping quality.

Biomechanical analysis of the effect of finger joint configuration on hand grasping performance: rigid vs flexible.

Human finger joints are conventionally simplified as rigid joints in robotic hand design and biomechanical hand modelling, due to their anatomic and morphologic complexity. However, our understanding of the effect of the finger joint configuration on the resulting hand performance is still primitive. In this study, we systematically investigate the grasping performance of the hands with the conventional rigid joints and the biomechanical flexible joints based on a computational human hand model. The measured muscle electromyography (EMG) and hand kinematic data during grasping are used as inputs for the grasping simulations. The results show that the rigid joint configuration currently used in most robotic hands leads to large reductions in hand contact force, contact pressure and contact area, compared to the flexible joint configuration. The grasping quality could be reduced up to 40% and 36% by the rigid joint configuration in terms of algebraic properties of grasping matrix and finger force limit respectively. Further investigation reveals that these reductions are caused by the weak rotational stiffness of the rigid joint configuration. This study implies that robotic/prosthetic hand performance could be improved by exploiting flexible finger joint design. Hand contact parameters and grasping performance may be underestimated by the rigid joint simplification in human hand modelling.

Design and Performance Investigation of a Robot-Assisted Flexible Ureteroscopy System.

Flexible ureteroscopy (FURS) has been developed and has become a preferred routine procedure for both diagnosis and treatment of kidney stones and other renal diseases inside the urinary tract. The traditional manual FURS procedure is highly skill-demanding and easily brings about physical fatigue and burnout for surgeons. The improper operational ergonomics and fragile instruments also hinder its further development and patient safety enhancement. A robotic system is presented in this paper to assist the FURS procedure. The system with a master-slave configuration is designed based on the requirement analysis in manual operation. A joint-to-joint mapping strategy and several control strategies are built to realize intuitive and safe operations. Both phantom and animal experiments validate that the robot has significant advantages over manual operations, including the easy-to-use manner, reduced intraoperative time, and improved surgical ergonomics. The proposed robotic system can solve the major drawbacks of manual FURS. The test results demonstrate that the robot has great potential for clinical applications.

Biology and bioinspiration of soft robotics: Actuation, sensing, and system integration.

Organisms in nature grow with senses, nervous, and actuation systems coordinated in ingenious ways to sustain metabolism and other essential life activities. The understanding of biological structures and functions guide the construction of soft robotics with unprecedented performances. However, despite the progress in soft robotics, there still remains a big gap between man-made soft robotics and natural lives in terms of autonomy, adaptability, self-repair, durability, energy efficiency, etc. Here, the actuation and sensing strategies in the natural biological world are summarized along with their man-made counterparts applied in soft robotics. The development trends of bioinspired soft robotics toward closed loop and embodiment are proposed. Challenges for obtaining autonomous soft robotics similar to natural organisms are outlined to provide a perspective in this field.

Bioinspired actuators with intrinsic muscle-like mechanical properties.

Humans and animals can achieve agile and efficient movements because the muscle can operate in different modes depending on its intrinsic mechanical properties. For bioinspired robotics and prosthetics, it is highly desirable to have artificial actuators with muscle-like properties. However, it still remains a challenge to realize both intrinsic muscle-like force-velocity and force-length properties in one single actuator simultaneously. This study presents a bioinspired soft actuator, named HimiSK (highly imitating skeletal muscle), designed by spatially arranging a set of synergistically contractile units in a flexible matrix similar to skeletal musculature. We have demonstrated that the actuator presents both intrinsic force-velocity and force-length characteristics that are very close to biological muscle with inherent self-stability and robustness in response to external perturbations. These outstanding properties result from the bioinspired architecture and the adaptive morphing of the flexible matrix material, which adapts automatically to mechanically diverse tasks without reliance on sensors and controllers.

Speed-Related Energy Flow and Joint Function Change During Human Walking.

During human walking, mechanical energy transfers between segments via joints. Joint mechanics of the human body are coordinated with each other to adapt to speed change. The aim of this study is to analyze the functional behaviors of major joints during walking, and how joints and segments alter walking speed during different periods (collision, rebound, preload, and push-off) of stance phase. In this study, gait experiment was performed with three different self-selected speeds. Mechanical works of joints and segments were determined with collected data. Joint function indices were calculated based on net joint work. The results show that the primary functional behaviors of joints would not change with altering walking speed, but the function indices might be changed slightly (e.g., strut functions decrease with increasing walking speed). Waist acts as strut during stance phase and contributes to keep stability during collision when walking faster. Knee of stance leg does not contribute to altering walking speed. Hip and ankle absorb more mechanical energy to buffer the strike during collision with increasing walking speed. What is more, hip and ankle generate more energy during push-off with greater motion to push distal segments forward with increasing walking speed. Ankle also produces more mechanical energy during push-off to compensate the increased heel-strike collision of contralateral leg during faster walking. Thus, human may utilize the cooperation of hip and ankle during collision and push-off to alter walking speed. These findings indicate that speed change in walking leads to fundamental changes to joint mechanics.

The Impact of Locomotor Speed on the Human Metatarsophalangeal Joint Kinematics.

This paper aims to further our previous study to investigate the effect of speed on the human metatarsophalangeal (MP) joint kinematics during running on level ground. The 3D motion of the foot segments was captured by a twelve-camera motion analysis system, and the ground reaction forces and moments were recorded by using a six-force plate array. The relative movement between the tarsometatarsi (hindfoot) and phalanges (forefoot) segments were recorded to obtain the 3D orientation and position of the functional axis (FA) of the MP joint. The results show that the FA locates about an average of 19% foot length (FL) anterior to the anatomical axis (AA) across all running speeds, and is also 4.8% FL inferior to the AA during normal and fast run. Similar to walking, the functional axis is more oblique than the anatomical axis with a more anterior-inferior orientation across all the running speeds. This suggests that representing MP joint with the AA may mislead the calculation of joint moment/power and muscle moment arms in both running and walking gait. Compared with previous study, we found that walking and running speeds have statistically significant effects on the position of the FA. The functional axis moves frontward to a more anterior position when the speed increases during walking and running. It transfers upward in the superior direction with increasing speed of walking, but moves more toward the inferior position when the velocity increased further to running. Also, the orientation of FA in sagittal plane became more oblique toward the vertical direction as the speed increased. This may help in moderating the muscular effort, increase the muscle EMA and improve the locomotor performance. These results would contribute to understanding the in vivo biomechanical function of the MP joint and also the foot propulsion during human locomotion.

Gyroscope Sensor Based In Vivo Finger Axes of Rotation Identification Using Screw Displacement.

This paper presents a low-cost, efficient, and portable in vivo method for identifying axes of rotation of the proximal interphalangeal and distal interphalangeal joints in an index finger. The approach is associated with the screw displacement representation of rigid body motion. Using the matrix exponential method, a detailed derivation of general spatial displacement of a rigid body in the form of screw displacement including the Rodrigues' formulae for rotation is presented. Then, based on a gyroscope sensor, a test framework for determining axes of rotation of finger joints is established, and experiments on finding the directions of joint axes of the PIP and DIP joints are conducted. The results obtained highly agree with those presented in literature through traditional but complex methods.

Textile-Based Capacitive Sensor for Physical Rehabilitation via Surface Topological Modification.

Wearable sensor technologies, especially continuous monitoring of various human health conditions, are attracting increased attention. However, current rigid sensors present obvious drawbacks, like lower durability and poor comfort. Here, a strategy is proposed to efficiently yield wearable sensors using cotton fabric as an essential component, and conductive materials conformally coat onto the cotton fibers, leading to a highly electrically conductive interconnecting network. To improve the conductivity and durability of conductive coatings, a topographical modification approach is developed with genus-3 and genus-5 structures, and topological genus structures enable cage metallic seeds on the surface of substrates. A textile-based capacitive sensor with flexible, comfortable, and durable properties has been demonstrated. High sensitivity and convenience of signal collection have been achieved by the excellent electrical conductivity of this sensor. Based on results of deep investigation on capacitance, effects of distance and angles between two conductive fabrics contribute to the capacitive sensitivity. In addition, the textile-based capacitive sensor has successfully been used for real-time monitoring human breathing, speaking, blinking, and joint motions during physical rehabilitation exercises.

Subject-Specific Finite Element Modelling of the Human Hand Complex: Muscle-Driven Simulations and Experimental Validation.

This paper aims to develop and validate a subject-specific framework for modelling the human hand. This was achieved by combining medical image-based finite element modelling, individualized muscle force and kinematic measurements. Firstly, a subject-specific human hand finite element (FE) model was developed. The geometries of the phalanges, carpal bones, wrist bones, ligaments, tendons, subcutaneous tissue and skin were all included. The material properties were derived from in-vivo and in-vitro experiment results available in the literature. The boundary and loading conditions were defined based on the kinematic data and muscle forces of a specific subject captured from the in-vivo grasping tests. The predicted contact pressure and contact area were in good agreement with the in-vivo test results of the same subject, with the relative errors for the contact pressures all being below 20%. Finally, sensitivity analysis was performed to investigate the effects of important modelling parameters on the predictions. The results showed that contact pressure and area were sensitive to the material properties and muscle forces. This FE human hand model can be used to make a detailed and quantitative evaluation into biomechanical and neurophysiological aspects of human hand contact during daily perception and manipulation. The findings can be applied to the design of the bionic hands or neuro-prosthetics in the future.