Search Results (54)

Background and Clinical Significance: Deep thalamic and periventricular lesions are uncommon in adults but can result in significant loss of function because of their convergence on three interdependent processes: thalamocortical state regulation, throughput of periventricular long association systems, and ventricular compartmental compliance. The resulting combination of executive control collapse, retrieval-weighted language fragility, and load-sensitive gait instability may occur early after a lesion forms an atrial/posterior horn interface, and pressure-linked autonomic symptoms may be late to develop. Screening deficits will likely be minimal and therefore underreported. Objective/Aim: To present a thalamic–atrial/posterior horn tumor case with quantified load-sensitive cognitive–language–gait dysfunction and to detail a physiology-guided, sequence-driven decompression approach emphasizing ventricular relaxation and perforator-preserving, interface-limited thalamic resection. Case Presentation: A 56-year-old female patient experienced a 3-month, rapidly progressive decline in her cognitive and language abilities. The clinical progression was not stepwise or punctuated by a single “sentinel” event. She had a moderate level of cognitive impairment consistent with both Broca’s and Wernicke’s aphasias (MoCA: 22/30) and suffered from significant interference effects and increased cost of task-switching. Her ability to generate novel responses and name objects was significantly impaired; however, she was able to repeat words and phrases appropriately. In addition, she exhibited a severe sustained attention signature and a high error rate during dual-task performance, indicating severe gait instability, although her overall global anchors were nearly neutral (GCS 15; FOUR 15/16; NIHSS 2). Nausea and vomiting occurred simultaneously with the cognitive and language decline, suggesting decreased intracranial compliance. MRI revealed a heterogeneous left-sided thalamic tumor extending into the posterior horn of the lateral ventricle. The tumor caused deformation of the lateral ventricle and midline displacement. The patient underwent microsurgical intervention using a physiology-conscious sequence of graded cerebrospinal fluid (CSF) equilibration and primary mechanical removal of the tumor from the ventricular system. Additionally, decompression of the thalamus was performed in a manner that was cognizant of the boundaries formed by the perforating arteries of the thalamus. Early resolution of pressure symptoms was noted postoperatively. Objective measures demonstrated significant improvement in the patient’s executive functioning, language skills, attentional errors, and dual-task performance stability. The patient remained functionally independent at discharge and at subsequent follow-up visits. Surveillance imaging did not demonstrate any evidence of tumor recurrence. Conclusions: The clinical presentation described above is supportive of a model in which the synergy between deep network damage and distortion of the posterior ventricular compartment amplifies network dysfunction. Additionally, the use of quantitative stress-phenotyping makes it possible to identify deep network pathology early in its course. Finally, the physiology-guided decompression approach that was used in this case has the potential to increase functional reserve in patients with pathology that requires millimeter transitions. Full article

Exploring the lunar complex and extreme terrain presents formidable challenges for conventional lunar rovers. To address these limitations, this study proposes a novel hexapod jumping hybrid robot that incorporates a “figure-of-eight” (butterfly-shaped) six-branched wheel-legged mechanism and a jumping system that stores elastic energy via deformation of its elastic body. Inspired by the multimodal locomotion of grasshoppers, the robot dynamically switches between two operational modes: high-efficiency wheeled locomotion on relatively flat surfaces and agile jumping to traverse steep slopes and surmount large obstacles. A bio-inspired gait, inspired by the crawling patterns of a hexapod insect, is implemented using a Central Pattern Generator (CPG)-based controller to produce coordinated, rhythmic limb movements. Dynamic simulations of the jumping mechanism were conducted to optimize the critical parameters of the elastic structure and its associated control strategy. Experiments on a physical prototype were conducted to validate the robot’s wheeled mobility and jumping performance. The results demonstrate that the robot exhibits excellent adaptability to rugged terrains and obstacle-dense environments. The integration of multimodal locomotion and adaptive gait control significantly enhances the robot’s operational robustness and survivability in the harsh lunar environment, opening new possibilities for future lunar exploration missions. Full article

To address the complex surface curvature, massive dimensions, and variable pitch angles of wind turbine blades, this paper proposes a climbing robot design based on a variable-cell mechanism. By dynamically adjusting the support span and body posture, the robot adapts to the geometric features of different blade regions, enabling stable and efficient non-destructive inspection operations. Two reconfigurable configurations—a planar quadrilateral and a regular hexagon—are proposed based on the geometric characteristics of different blade regions. The configuration switching conditions and multi-leg cooperative control mechanisms are investigated. Through static stability margin analysis, the stable gait space and maximum stride length for each configuration are determined, optimizing the robot’s motion performance on surfaces with varying curvature. Simulation and experimental results demonstrate that the proposed multi-configuration gait planning strategy exhibits excellent adaptability and climbing stability across segments of varying curvature. This provides a theoretical foundation and methodological support for the engineering application of robots in wind turbine blade maintenance. Full article

Lower-limb exoskeletons have become an effective tool for gait rehabilitation by enabling precise and repetitive joint movements for individuals with motor impairments. Nevertheless, the nonlinear and uncertain nature of human–robot interaction dynamics requires effective control strategies that are both robust and smooth. Conventional sliding mode control (SMC) provides robustness against disturbances but, in effect, is prone to chattering, which can adversely cause mechanical vibrations and reduce user comfort. This paper proposes a novel hybrid sliding mode control integrated with integral resonant control (SMC + IRC), strategy addressing a gap in 3-DOF exoskeleton control where structural resonance and chattering mitigation are simultaneously required while maintaining robustness and trajectory accuracy. The IRC component in this work uses a resonant damping mechanism to filter high-frequency switching elements in the SMC signal, resulting in smoother actuator torques without compromising system stability, robustness or responsiveness. The proposed control framework here is implemented on a lower-limb exoskeleton with hip, knee, and ankle joints and compared to classical SMC and Super-Twisting SMC (STSMC) methods. Upon simulation, results showed that the SMC + IRC approach significantly reduces chattering as well as produces smoother torque profiles while maintaining high tracking precision. Quantitative analyses using RMSE and chattering index metrics prove the superior performance of the proposed controller over the previous ones, establishing it as a practical and effective solution for safe and comfortable rehabilitation motion in real-time exoskeleton systems. Full article

Attempting to make machines mimic human walking, grasping, balancing, and other behaviors is a deep exploration of cognitive science and biological principles. Due to the existing prediction lag problem, an error compensation mechanism that integrates historical motion data is proposed. By constructing a humanoid autonomous walking control system, this paper aims to use a three-dimensional linear inverted pendulum model to plan the general framework of motion. Firstly, the landing point coordinates of the single foot support period are preset through gait cycle parameters. In addition, it is substituted into dynamic equation to solve the centroid (COM) trajectory curve that conforms to physical constraints. A hierarchical whole-body control architecture is designed, with a task priority based on quadratic programming solver used at the bottom to decompose high-level motion instructions into joint space control variables and fuse sensor data. Furthermore, the numerical iterative algorithm is used to solve the sequence of driving angles for each joint, forming the control input parameters for driving the robot’s motion. This algorithm solves the limitations of traditional inverted pendulum models on vertical motion constraints by optimizing the centroid motion trajectory online. At the same time, it introduces a contact phase sequence prediction mechanism to ensure a smooth transition of the foot trajectory during the switching process. Simulation results demonstrate that the proposed framework improves disturbance rejection capability by over 30% compared to traditional ZMP tracking and achieves a real-time control loop frequency of 1 kHz, confirming its enhanced robustness and computational efficiency. Full article

Biped robots based on parallel mechanisms hold great potential for applications in complex terrains. Based on a 4-UPU parallel mechanism, this paper proposes a novel biped robot that achieves alternating bipedal locomotion and turning with only six actuators by employing fixed/moving platform switching and following an “upper platform + lower foot” continuous gait strategy. Using the influence coefficient method, the first order and second order kinematic influence coefficient matrices of the biped robot were derived. Based on the principle of virtual work, a dynamic model of the robot was formulated, and its validity was verified through numerical simulations. The dynamic performance of the robot was further evaluated using the Dynamic Manipulability Ellipsoid (DME) index, while its stability during step-climbing and turning was analyzed using the Zero-Moment Point (ZMP) method. The results demonstrate that the dual-platform biped robot features a rational structure and exhibits robust stability during step-climbing and turning. Full article

This paper proposes a novel intelligent switching control strategy for a five-bar lower limb exoskeleton. First, during the support phase, terminal sliding mode control (TSMC) is employed to ensure robust stability and high-torque amplification capabilities. Then, during the swing phase, a hybrid controller combining proportional-integral-derivative (PID) control and the adaptive neuro-fuzzy inference system (ANFIS) is implemented to generate natural and compliant leg movements. Finally, to achieve smooth transitions between phases, an intelligent switching algorithm based on multi-sensor information fusion is proposed. Simulation results demonstrate that the proposed strategy keeps trajectory tracking errors below 0.05 across all gait phases and achieves stable torque amplification ratios ranging from 1:6 to 1:10. This performance significantly reduces the user’s physical exertion. These findings validate the effectiveness of this control framework in improving the stability and comfort of human–machine interaction. Full article

Based on fundamental mechanics, movement and force associate head and pelvic movement asymmetry with asymmetry of force production. We investigate, how often racehorses undergoing strenuous training regimens show evidence of switching between “preferred” limbs, i.e. one limb producing increased force, when assessed at monthly intervals? We hypothesize that clinical asymmetry thresholds designed for “detecting lameness” are frequently exceeded and that when applying previously established Thoroughbred-specific repeatability values, horses rarely switch between showing left- and right-sided asymmetry. Monthly gait assessments (inertial sensors) were conducted in 256 Thoroughbred racehorses at least twice per horse (up to 16 times per horse). Descriptive statistics for absolute differences for head and pelvic movement were compared to published Thoroughbred-specific repeatability values. The percentage of left–right switches between repeat assessments was calculated in comparison to three different levels of pre-defined thresholds (perfect symmetry, clinical lameness thresholds, previously established Thoroughbred-specific repeatability values) and switch frequencies compared between the three thresholds. Ranges containing 95% of monthly differences were higher than published daily and weekly values except for pelvic vertical range of motion. Approximately 30% of monthly differences in individual symmetry parameters showed left–right switches around “perfect symmetry”. Utilizing clinical lameness thresholds for categorizing left–right switches, a significantly (p < 0.001) reduced percentage of 4–11% of measurements for head movement and 7–17% for pelvic movement showed switches. Using daily repeatability values for categorization, a further significantly (p < 0.001) reduced percentage of switches was observed: 0.3–3.6% for head movement and 0.6–7.0% for pelvic movement. While racehorses in training regularly switch between small left- or right-sided movement symmetries, they less frequently switch between more pronounced left- and right-sided movement symmetries defined based on daily variations. Further studies should investigate the reasons for these rare switches. Full article

This study, in response to the optimization needs of fall risks for the elderly in the context of cultural and tourism integration in Hebei Province, China, established a quantitative correlation system between ten gait parameters and ten types of spatial risk factors. By collecting gait data (Qualisys infrared motion capture system, sampling rate 200 Hz) and spatial parameters from 30 elderly subjects (with mild, moderate, and severe functional impairments), a multi-level regression model was established. This study revealed that step frequency, step width, and step length were nonlinearly associated with corridor length, door opening width, and step depth (R² = 0.53–0.68). Step speed, ankle dorsiflexion, and foot pressure were key predictive factors (OR = 0.04–8.58, p < 0.001), driving the optimization of core spatial factors such as threshold height, handrail density, and friction coefficient. Step length, cycle, knee angle, and lumbar moment, respectively, affected bed height (45–60 cm), switch height (1.2–1.4 m), stair riser height (≤35 mm), and sink height adjustment range (0.7–0.9 m). The prediction accuracy of the ten optimized values reached 86.7% (95% CI: 82.1–90.3%), with Hosmer–Lemeshow goodness-of-fit x² = 7.32 (p = 0.412) and ROC curve AUC = 0.912. Empirical evidence shows that the graded optimization scheme reduced the fall risk by 42–85%, and the estimated fall incidence rate decreased by 67% after the renovation. The study of the “abnormal gait—spatial threshold—graded optimization” quantitative residential layout optimization provides a systematic solution for the data-quantified model of elderly-friendly residential renovations. Full article

Quadruped robots have shown significant potential in disaster relief applications, where they have to navigate complex terrains for search and rescue or reconnaissance operations. However, their deployment is hindered by limited adaptability in highly uncertain environments, especially when relying solely on vision-based sensors like cameras or LiDAR, which are susceptible to occlusions, poor lighting, and environmental interference. To address these limitations, this paper proposes a novel sensor-enhanced hierarchical switching model predictive control (MPC) framework that integrates proprioceptive sensing with a bi-level hybrid dynamic model. Unlike existing methods that either rely on handcrafted controllers or deep learning-based control pipelines, our approach introduces three core innovations: (1) a situation-aware, bi-level hybrid dynamic modeling strategy that hierarchically combines single-body rigid dynamics with distributed multi-body dynamics for modeling agility and scalability; (2) a three-layer hybrid control framework, including a terrain-aware switching MPC layer, a distributed torque controller, and a fast PD control loop for enhanced robustness during contact transitions; and (3) a multi-IMU-based proprioceptive feedback mechanism for terrain classification and adaptive gait control under sensor-occluded or GPS-denied environments. Together, these components form a unified and computationally efficient control scheme that addresses practical challenges such as limited onboard processing, unstructured terrain, and environmental uncertainty. A series of experimental results demonstrate that the proposed method outperforms existing vision- and learning-based controllers in terms of stability, adaptability, and control efficiency during high-speed locomotion over irregular terrain. Full article

Legged robots face inherent challenges in energy efficiency and stability at high speeds due to the repetitive acceleration–deceleration cycles of swing-based locomotion. To address these limitations, this paper presents a motion strategy that uses rolling gait instead of swing gait to improve the energy efficiency and stability. First, a wheel-legged quadruped robot, R-Taichi, is developed, which is capable of switching to legged, wheeled, and RHex mobile modes. Second, the mechanical structure of the transformable two-degree-of-freedom leg is introduced, and the kinematics is analyzed. Finally, experiments are conducted to generate wheeled, legged, and RHex motion in both swing and rolling gaits, and the energy efficiency is further compared. The experimental results show that the rolling motion can ensure stable ground contact and mitigate cyclic collisions, reducing specific resistance by up to 30% compared with conventional swing gaits, achieving a top speed of 0.7 m/s with enhanced stability (root mean square error (RMSE) reduction of 22% over RHex mode). Furthermore, R-Taichi exhibits robust multi-terrain adaptability, successfully traversing gravel, grass, and obstacles up to 150 mm in height. Full article

This paper presents a novel design for a bionic knee exoskeleton equipped with a variable stiffness actuator based on rope-driven artificial muscles. To meet the varying stiffness requirements of the knee joint across different gait modes, the actuator dynamically switches between multiple rope bundle configurations, thereby enabling effective stiffness modulation. A mathematical model of the knee exoskeleton is developed, and the mechanical properties of the selected flexible aramid fiber ropes under tensile loading are analyzed through both theoretical and experimental approaches. Furthermore, a control framework for the exoskeleton system is proposed. Wearable experiments are conducted to evaluate the effectiveness of the variable stiffness actuation in improving compliance and comfort across various gait patterns. Electromyography (EMG) results further demonstrate that the exoskeleton provides a compensatory effect on the rectus femoris muscle. Full article

This research study proposes a heuristic hybrid deep neural network (DNN) gait sub-phase recognition model based on multi-source heterogeneous motion data fusion which quantifies gait phases and is applied in balance disorder rehabilitation control, achieving a recognition accuracy exceeding 99%. Building upon this model, a motion control strategy for a novel rehabilitation training robot is designed and developed. For patients with some degree of independent movement, an active training strategy is introduced; it combines gait recognition with a variable admittance control strategy. This strategy provides assistance during the stance phase and moderate support during the swing phase, effectively enhancing the patient’s autonomous movement capabilities and increasing engagement in the rehabilitation process. The gait phase recognition system not only provides rehabilitation practitioners with a comprehensive tool for patient assessment but also serves as a theoretical foundation for collaborative control in rehabilitation robots. Through the innovative active–passive training control strategy and its application in the novel rehabilitation robot, this research study overcomes the limitations of traditional rehabilitation robots, which typically operate in a single functional mode, thereby expanding their functional boundaries and enabling more precise, personalized rehabilitation training programs tailored to the needs of patients in different stages of recovery. Full article

Legged robots often encounter the problem that the foot-end steps into empty spaces due to terrain collapse in complex environments such as mine tunnels and coal shafts, which in turn causes body instability. Aiming at this problem, this paper takes the hexapod robot as the research object and proposes a multi-segmented electrically driven single-leg compliance control strategy for robots with tripod and quadrupedal gaits, to reduce the impact when the foot-end touches the ground, and thus to improve the stability of the robot. First, this paper analyzes the kinematic and dynamic models of the multi-segmented electrically driven single leg of the hexapod robot. Then, the minimum tipping angle of the fuselage is obtained based on force-angle stability margin (FASM) and used as the index to design the single-leg pit-probing control algorithm based on position impedance control and the single-leg touchdown force adjustment control algorithm based on inverse dynamics control. Finally, this paper designs a finite state machine to switch between different control strategies of the multi-segmented electrically driven single leg of the hexapod robot, and the vertical dynamic impact characteristic index is applied to evaluate the effect of single-leg impedance control. The simulation and prototype test results show that the proposed method significantly reduces the foot-end touchdown force and improves the walking stability of the hexapod robot in complex environments compared with the multi-segmented electrically driven single leg without the compliance control strategy. Full article

Background: Exoskeleton robots are emerging as a transformative technology in healthcare, rehabilitation, and industrial settings, providing significant benefits such as improving gait restoration and preventing injuries. These robots enhance mobility for individuals with neuromuscular disorders by providing muscular assistance and reducing physical strain, while also supporting workers in physically demanding tasks. They improve gait efficiency, muscle activation, and overall physical function, contributing to both rehabilitation and occupational health. Objective: This study aims to investigate the impact of exoskeleton use on muscle activation patterns, fatigue levels, and gait parameters in healthy individuals. Methods: Thirty-six participants engaged in a randomized sequence gait experiment on a treadmill for 30 min, both with and without an exoskeleton, with electromyography (EMG) and OptoGait measurements collected during the sessions. A one-week washout period was implemented before participants switched conditions. Results: In the Maximum voluntary contraction (MVC) analysis, significant differences were observed in the Rectus femoris (RF) and gastrocnemius(GM) when wearing the exoskeleton robot compared to not wearing it. At 10 min, 20 min, and 30 min, the differences were statistically significant (p < 0.05) for all muscles. In the muscle fatigue analysis, significant differences were observed in RF, GM, vastus medialis (VM), and hamstring(HS) at 10 min, 20 min, and 30 min (p < 0.05). In the step length and stride length analysis, significant differences were observed at 10 min and 30 min, but no differences were found at 20 min (p < 0.05). Conclusions: This study demonstrates that the use of the exoskeleton robot significantly impacts muscle activation, muscle fatigue, and gait parameters. The results emphasize the potential benefits of exoskeletons in enhancing mobility and reducing muscle strain, providing important insights for rehabilitation and occupational applications Full article