Robotic Ankle Research Articles

Ankle dorsiflexion training with a newly developed Hybrid Assistive Limb for a patient with foot drop caused by common peroneal nerve palsy: a case report

[Purpose] An ankle disorder (foot drop) caused by common peroneal nerve palsy or cerebrovascular accident (stroke) interferes with patients’ ability to walk and hinders in activities of daily living. A new robotic ankle, the Hybrid Assistive Limb, has been developed for the treatment of foot drop caused by common peroneal nerve palsy or sequelae of stroke. The purpose in this study was to report and examine the efficacy and feasibility of a case who was treated with voluntary ankle dorsiflexion training with the ankle Hybrid Assistive Limb. [Participant and Method] A 60-year-old man with foot drop due to peroneal nerve palsy that occurred without a contributory cause was treated via ankle dorsiflexion training with the use of a new robotic ankle, the “Ankle Hybrid Assistive Limb”. [Results] Following total ankle rehabilitation training with the Ankle Hybrid Assistive Limb, improvements in ankle dorsiflexor strength, gait, and sensory function of the lower leg and foot were observed. [Conclusion] The newly developed ankle Hybrid Assistive Limb could be an effective training tool for foot drop caused by common peroneal nerve palsy.

Design and Hierarchical Force-Position Control of Redundant Pneumatic Muscles-Cable-Driven Ankle Rehabilitation Robot

Ankle dysfunction is common in the public following injuries, especially for stroke patients. Most of the current robotic ankle rehabilitation devices are driven by rigid actuators and have problems such as limited degrees of freedom, lack of safety and compliance, and poor flexibility. In this letter, we design a new type of compliant ankle rehabilitation robot redundantly driven by pneumatic muscles (PMs) and cables to provide full range of motion and torque ability for the human ankle with enhanced safety and adaptability, attributing to the PM's high power/mass ratio, good flexibility and lightweight advantages. The ankle joint can be compliantly driven by the robot with full three degrees of freedom to perform the dorsiflexion/plantarflexion, inversion/ eversion, and adduction/abduction training. In order to keep all PMs and cables in tension which is essential to ensure the robot's controllability and patient's safety, Karush-Kuhn-Tucker (KKT) theorem and analytic-iterative algorithm are utilized to realize a hierarchical force-position control (HFPC) scheme with optimal force distribution for the redundant compliant robot. Experiment results demonstrate that all PMs are kept in tension during the control while the position tracking accuracy of the robot is acceptable, which ensures controllability and stability throughout the compliant robot-assisted rehabilitation training.

Actuation Timing Perception of a Powered Ankle Exoskeleton and Its Associated Ankle Angle Changes During Walking.

Robotic ankle exoskeletons have the potential to extend human ability, and actuation timing serves as one of the critical parameters in its controller design. While many experiments have investigated the optimal actuation timing values to achieve different objective functions (e.g. minimizing metabolic cost), studies on users' perception of control parameters are gaining interest as it gives information on people's comfort, coordination, and trust in using devices, as well as providing foundations on how the sensorimotor system detects the exoskeleton behavior changes. The purpose of this study was to evaluate people's sensitivity to changes in exoskeleton actuation timing and its associated exoskeleton ankle angle changes during walking. Participants (n =15) with little or no prior experience with ankle exoskeletons were recruited and performed a psychophysical experiment to characterize their just-noticeable difference (JND) thresholds for actuation timing. Participants wore a bilateral active ankle exoskeleton and compared pairs of torque profiles with different actuation timings and low peak torque (0.225 Nm/kg) while walking on the treadmill. The mean timing JND across participants was 2.8±0.6% stride period. Individuals exhibited different sensitivity towards actuation timing, and their associated exoskeleton ankle angle changes also varied. The variance in ankle angle changes might be explained by their differences in ankle stiffness and different ankle torques provided during walking. The results provide insights into how people perceive the changes in exoskeleton control parameters and show individual differences in exoskeleton usage. The actuation timing JND found in this study can also help determine the necessary controller precision.

Comparison of Deep Neural Network Models and Effectiveness of EMG Signal Feature Value for Estimating Dorsiflexion

Robotic ankle–foot orthoses (AFO) are often used for gait rehabilitation. Our research focuses on the design and development of a robotic AFO with minimum number of sensor inputs. However, this leads to degradation of gait estimation accuracy. To prevent degradation of accuracy, we compared a few neural network models in order to determine the best network when only two input channels are being used. Further, the EMG signal feature value of average rate of change was used as input. LSTM showed the highest accuracy. However, MLP with a small number of hidden layers showed results similar to LSTM. Moreover, the accuracy for all models, with the exception of LSTM for one subject (SD), increased with the addition of feature value (average rate of change) as input. In conclusion, time-series networks work best with a small number of sensor inputs. However, depending on the optimizer being used, even a simple network can outrun a deep learning network. Furthermore, our results show that applying EMG signal feature value as an input tends to increase the estimation accuracy of the network.

Usability and performance validation of an ultra-lightweight and versatile untethered robotic ankle exoskeleton

BackgroundAnkle exoskeletons can improve walking mechanics and energetics, but few untethered devices have demonstrated improved performance and usability across a wide range of users and terrains. Our goal was to design and validate a lightweight untethered ankle exoskeleton that was effective across moderate-to-high intensity ambulation in children through adults with and without walking impairment.MethodsFollowing benchtop validation of custom hardware, we assessed the group-level improvements in walking economy while wearing the device in a diverse unimpaired cohort (n = 6, body mass = 42–92 kg). We also conducted a maximal exertion experiment on a stair stepping machine in a small cohort of individuals with cerebral palsy (CP, n = 5, age = 11–33 years, GMFCS I-III, body mass = 40–71 kg). Device usability metrics (device don and setup times and System Usability Score) were assessed in both cohorts.ResultsThere was a 9.9 ± 2.6% (p = 0.012, range = 0–18%) reduction in metabolic power during exoskeleton-assisted inclined walking compared to no device in the unimpaired cohort. The cohort with CP was able to ascend 38.4 ± 23.6% (p = 0.013, range = 3–132%) more floors compared to no device without increasing metabolic power (p = 0.49) or perceived exertion (p = 0.50). Users with CP had mean device don and setup times of 3.5 ± 0.7 min and 28 ± 6 s, respectively. Unimpaired users had a mean don time of 1.5 ± 0.2 min and setup time of 14 ± 1 s. The average exoskeleton score on the System Usability Scale was 81.8 ± 8.4 (“excellent”).ConclusionsOur battery-powered ankle exoskeleton was easy to use for our participants, with initial evidence supporting effectiveness across different terrains for unimpaired adults, and children and adults with CP.Trial registration Prospectively registered at ClinicalTrials.gov (NCT04119063) on October 8, 2019.

Multivariable passive ankle impedance in stroke patients: A preliminary study

Multivariable ankle mechanical impedance was estimated in four stroke survivors, in coupled dorsi- plantarflexion and inversion–eversion. We applied external torque perturbation with an ankle robot and used multi-input, multi-output stochastic system identification methods to estimate impedance, in both paretic and nonparetic limbs. Subjects were instructed to remain at rest throughout the four trials performed on each leg. Impedance projected onto the directions of maximum and minimum stiffness was fit to a 2nd order linear model, including inertia, viscosity and stiffness. For most trials, stiffness and damping in dorsi-plantarflexion are increased on the paretic side. However, for two subjects, overall impedance is not increased in the absence of sustained involuntary tonic contraction, registering values comparable to the non-paretic side. Thus, we speculate that the intrinsic properties of the paretic ankle remained unaffected at the evaluated pose. Spasticity (hyperflexive stretch reflex) would have systematically increased stiffness and damping, even in the absence of involuntary contraction. Hence, we speculate that these two subjects did not exhibit spasticity, while the remaining two subjects did, since impedance was increased, with no involuntary tonic muscle contraction. Regarding inversion–eversion, impedance in this direction remained unaffected by stroke. We evaluated two volunteers before and after the application of botulinum toxin. Surprisingly, ankle stiffness was not reduced, but anisotropy was normalized.

Variable Damping Control for pHRI: Considering Stability, Agility, and Human Effort in Controlling Human Interactive Robots

This article presents a multi-degree-of-freedom variable damping controller to manage the trade-off between stability and agility and to reduce user effort in physical human-robot interaction. The controller accounts for the human body's inherent impedance properties and applies a range of robotic damping from negative (energy injection) to positive (energy dissipation) values based on the user's intent of motion. To evaluate the effectiveness of the proposed controller in balancing the trade-off between stability/agility and reducing user effort, two studies are performed on both the human upper-extremity and lower-extremity to represent both industrial and rehabilitation applications of the proposed controller. These studies required subjects to perform a series of multidimensional target reaching tasks while the human user interacted with either the end-effector of a robotic arm for the upper-extremity study or a wearable ankle robot for the lower-extremity study. Stability, agility, and user effort are quantified by a variety of performance metrics. Stability is quantified by both overshoot and stabilization time. Mean and maximum speed are used to quantify agility. To quantify the user effort, both overall and maximum muscle activation, and mean and maximum root-mean-squared interaction force are calculated. The results of both the upper- and lower-extremity studies demonstrate that the controller is able to reduce user effort while increasing agility at a negligible cost to stability.

Redesign of a Biomechanical Energy Regeneration-based Robotic Ankle Prosthesis using Indonesian Gait Data

In this research, the robotic ankle design from Arizona State University (ASU) known as SPARKy was redesigned to accommodate the specific needs of Indonesian people. Most active prosthetic legs are designed based on gait parameters for people from Western countries, which may differ for people from other cultures that have a different anthropometry and economic background. Indonesians have smaller actuating power characteristics compared to people from Western cultures due to their smaller average weight and body height. Thus, the applied design strategy took advantage of a biomechanical energy regeneration scheme to reduce the actuator input power requirement and the relatively smaller mechanical power of the typical Indonesian ankle to create a potentially affordable robotic ankle with a smaller actuator that meets the technical specifications. The specifications of the powered prosthetic ankle were determined through the same methods used by SPARKy. Only one low-level control system, to actuate normal walking, was designed and tested on a fully assembled robotic ankle. The test results indicated a promising low-level control, where the robotic ankle can follow the predetermined trajectory required to actuate normal walking based on Indonesian gait data.

Intramuscular Coherence of the Lower Flexor Muscles during Robotic Ankle-Assisted Gait

A close-fitting assisted walking device (RE-Gait) designed to assist ankle movements might be a novel approach for acquiring the forefoot rocker function in the gait cycle. The purpose of the present study was to investigate the effects of using RE-Gait by evaluating the intramuscular coherence (IMC) of the two parts of the tibialis anterior muscles (TA), which could indicate whether a common synaptic drive is present. Seventeen healthy volunteers walked on a treadmill at a comfortable speed before, during, and immediately after 15-minute RE-Gait intervention. After RE-Gait intervention, IMC of the two parts of the TA muscles in the beta frequency band in the initial swing phase was significantly enhanced during RE-Gait intervention. In addition, IMCs in the beta and low-gamma frequency bands were significantly correlated with the enhancement ratio of the step length. These results suggest that robotic ankle plantar flexion and dorsiflexion assistance in the initial swing phase may be effective for improving gait function with enhancement of the functioning of the sensorimotor loop.

Entrainment During Human Locomotion Using a Soft Wearable Ankle Robot

An entrainment study was conducted with a novel soft robotic ankle-foot orthosis (SR-AFO) consisting of a pair of flat fabric pneumatic artificial muscles (ff-PAM). Entrainment capabilities of a lighter soft robotic orthosis were compared with heavy rigid robotic counterparts reported previously. To measure the SR-AFO's capacity to manifest gait entrainment, periodic pneumatic plantarflexion perturbations equal to the calculated increase from the subject's preferred gait frequency were applied to the ankle. Two days of experiments were conducted. In the Day 1 experiment, perturbations were applied from the baseline to a 15% increase in the gait frequency with steps of 3% at a fixed treadmill speed of the subject's preferred walking speed. In the Day 2 experiment, in order to investigate the maximum entrainment capability with the SR-AFO, perturbations were applied from the baseline with steps of 5% with proportionally increasing walking speed until subjects failed to maintain phase locking for 50 or more consecutive steps. In the Day 1 experiment, all 10 subjects were entrained at the highest 15% condition. In the Day 2 experiments, the average basin of entrainment was 39.3 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\pm$</tex-math></inline-formula> 9.2%. Importantly, phase locking was always observed in the push-off phase of the gait cycle in both days of experiments. The observed basin of entrainment with the SR-AFO was substantially higher than the previously reported value (+7%) with a heavy rigid ankle robot, confirming the potential of the SR-AFO to significantly extend the effectiveness of the entrainment paradigm in gait adaptation and rehabilitation.

Neuromechanics and Energetics of Walking With an Ankle Exoskeleton Using Neuromuscular-Model Based Control: A Parameter Study.

Powered ankle exoskeletons that apply assistive torques with optimized timing and magnitude can reduce metabolic cost by ∼10% compared to normal walking. However, finding individualized optimal control parameters is time consuming and must be done independently for different walking modes (e.g., speeds, slopes). Thus, there is a need for exoskeleton controllers that are capable of continuously adapting torque assistance in concert with changing locomotor demands. One option is to use a biologically inspired, model-based control scheme that can capture the adaptive behavior of the human plantarflexors during natural gait. Here, based on previously demonstrated success in a powered ankle-foot prosthesis, we developed an ankle exoskeleton controller that uses a neuromuscular model (NMM) comprised of a Hill type musculotendon driven by a simple positive force feedback reflex loop. To examine the effects of NMM reflex parameter settings on (i) ankle exoskeleton mechanical performance and (ii) users’ physiological response, we recruited nine healthy, young adults to walk on a treadmill at a fixed speed of 1.25 m/s while donning bilateral tethered robotic ankle exoskeletons. To quantify exoskeleton mechanics, we measured exoskeleton torque and power output across a range of NMM controller Gain (0.8–2.0) and Delay (10–40 ms) settings, as well as a High Gain/High Delay (2.0/40 ms) combination. To quantify users’ physiological response, we compared joint kinematics and kinetics, ankle muscle electromyography and metabolic rate between powered and unpowered/zero-torque conditions. Increasing NMM controller reflex Gain caused increases in average ankle exoskeleton torque and net power output, while increasing NMM controller reflex Delay caused a decrease in net ankle exoskeleton power output. Despite systematic reduction in users’ average biological ankle moment with exoskeleton mechanical assistance, we found no NMM controller Gain or Delay settings that yielded changes in metabolic rate. Post hoc analyses revealed weak association at best between exoskeleton and biological mechanics and changes in users’ metabolic rate. Instead, changes in users’ summed ankle joint muscle activity with powered assistance correlated with changes in their metabolic energy use, highlighting the potential to utilize muscle electromyography as a target for on-line optimization in next generation adaptive exoskeleton controllers.

Variable Impedance Control for pHRI: Impact on Stability, Agility, and Human Effort in Controlling a Wearable Ankle Robot

This letter introduces a variable impedance controller which dynamically modulates both its damping and stiffness to improve the trade-off between stability and agility in coupled human-robot systems and reduce the human user's effort. The controller applies a range of robotic damping from negative to positive values to either inject or dissipate energy based on the user's intent of motion. The controller also estimates the user's intent of direction and applies a variable stiffness torque to stabilize the user towards an estimated ideal trajectory. To evaluate the controller's ability to improve the stability/agility trade-off and reduce human effort, a study was designed for human subjects to perform a 2D target reaching task while coupled with a wearable ankle robot. A constant impedance condition was selected as a control with which to compare the variable impedance condition. The position, speed, and muscle activation responses were used to quantify the user's stability, agility, and effort, respectively. Stability was quantified spatially and temporally, with both overshoot and stabilization time showing no statistically significant difference between the two experimental conditions. Agility was quantified using mean and maximum speed, with both increasing from the constant impedance to variable impedance condition by 29.8% and 59.9%, respectively. Effort was quantified by the overall and maximum muscle activation data, both of which showed a ~10% reduction in effort. Overall, the study demonstrated the effectiveness of the variable impedance controller.

Optimizing the Rigid or Compliant Behavior of a Novel Parallel-Actuated Architecture for Exoskeleton Robot Applications.

The purpose of this work is to optimize the rigid or compliant behavior of a new type of parallel-actuated robot architecture developed for exoskeleton robot applications. This is done in an effort to provide those that utilize the architecture with the means to maximize, minimize, or simply adjust its stiffness property so as to optimize it for particular tasks, such as augmented lifting or impact absorption. This research even provides the means to produce non-homogeneous stiffness properties for applications that may require non-homogeneous dynamic behavior. In this work, the new architecture is demonstrated in the form of a shoulder exoskeleton. An analytical stiffness model for the shoulder exoskeleton is created and validated experimentally. The model is then used, along with a method of bounded nonlinear multi-objective optimization to configure the parallel substructures for desired rigidity, compliance or nonhomogeneous stiffness behavior. The stiffness model and its optimization can be applied beyond the shoulder to any embodiment of the new parallel architecture, including hip, wrist and ankle robot applications. In order to exemplify this, we present the rigidity optimization for a theoretical hip exoskeleton.

Effects of wearable ankle robotics for stair and over-ground training on sub-acute stroke: a randomized controlled trial

BackgroundWearable ankle robotics could potentially facilitate intensive repetitive task-specific gait training on stair environment for stroke rehabilitation. A lightweight (0.5 kg) and portable exoskeleton ankle robot was designed to facilitate over-ground and stair training either providing active assistance to move paretic ankle augmenting residual motor function (power-assisted ankle robot, PAAR), or passively support dropped foot by lock/release ankle joint for foot clearance in swing phase (swing-controlled ankle robot, SCAR). In this two-center randomized controlled trial, we hypothesized that conventional training integrated with robot-assisted gait training using either PAAR or SCAR in stair environment are more effective to enhance gait recovery and promote independency in early stroke, than conventional training alone.MethodsSub-acute stroke survivors (within 2 months after stroke onset) received conventional training integrated with 20-session robot-assisted training (at least twice weekly, 30-min per session) on over-ground and stair environments, wearing PAAR (n = 14) or SCAR (n = 16), as compared to control group receiving conventional training only (CT, n = 17). Clinical assessments were performed before and after the 20-session intervention, including functional ambulatory category as primary outcome measure, along with Berg balance scale and timed 10-m walk test.ResultsAfter the 20-session interventions, all three groups showed statistically significant and clinically meaningful within-group functional improvement in all outcome measures (p < 0.005). Between-group comparison showed SCAR had greater improvement in functional ambulatory category (mean difference + 0.6, medium effect size 0.610) with more than 56% independent walkers after training, as compared to only 29% for CT. Analysis of covariance results showed PAAR had greater improvement in walking speed than SCAR (mean difference + 0.15 m/s, large effect size 0.752), which was in line with the higher cadence and speed when wearing the robot during the 20-session robot-assisted training over-ground and on stairs.ConclusionsRobot-assisted stair training would lead to greater functional improvement in gait independency and walking speed than conventional training in usual care. The active powered ankle assistance might facilitate users to walk more and faster with their paretic leg during stair and over-ground walking.Trial registration: ClinicalTrials.gov NCT03184259. Registered on 12 June 2017.

Intensive In-Bed Sensorimotor Rehabilitation of Early Subacute Stroke Survivors With Severe Hemiplegia Using a Wearable Robot.

Rehabilitation for stroke survivors with severe motor impairment remains challenging. Early motor rehabilitation is critical for improving mobility function post stroke, but it is often delayed due to limited resources in clinical practice. The objectives of this study were to investigate the feasibility and effectiveness of early in-bed sensorimotor rehabilitation on acute stroke survivors with severe hemiplegia using a wearable ankle robot. Eighteen patients (9 in the study group and 9 in the control group) with severe hemiplegia and no active ankle movement were enrolled in acute/subacute phase post stroke. During a typical 3-week hospital stay, patients in the study group received ankle robot-guided in-bed training (50 minutes/session, 5 sessions/week), including motor relearning under real-time visual feedback of re-emerging motor output, strong passive stretching under intelligent control, and game-based active movement training with robotic assistance. Whereas the control group received passive ankle movement in the mid-range of motion and attempted active ankle movement without robotic assistance. After multi-session training, the study group achieved significantly greater improvements in Fugl-Meyer Lower Extremity motor score (p = 0.007), plantarflexor strength (p = 0.009), and active range of motion (p = 0.011) than controls. The study group showed earlier motor recovery for plantarflexion and dorsiflexion than the control group (p < 0.05). This study showed that in-bed sensorimotor rehabilitation guided by awearable ankle robot through combining motor relearning in real-time feedback, strong passive stretching, and active movement training facilitated early motor recovery for stroke survivors with severe hemiplegia in the acute/subacute phase.

Development of Robotic Ankle–Foot Orthosis With Series Elastic Actuator and Magneto-Rheological Brake

Abstract This paper illustrates the development and experimental validation of a robotic ankle–foot orthosis (AFO) with a series elastic actuator (SEA) and a magneto-rheological (MR) brake. First, the biomechanics of a human ankle joint during walking is explained. Next, the hardware design of the robotic AFO is introduced, including its mechanical structure, actuator design and configuration, and electronic system. The SEA is primarily composed of an electric motor, a planetary gearbox, a torsion spring, and a pair of bevel gears. The MR brake can modulate the viscosity of the robotic AFO and generate a large braking torque of 21.8 Nm with a low power of 8.8 W. Additionally, the modeling of the robotic AFO is presented, followed by an introduction to its control; several gait evaluation indices are proposed as well. Finally, a pilot study is conducted to verify the effectiveness of the developed robotic AFO. The experimental results demonstrate that the robotic AFO has the potential to provide dorsiflexion assistance, thus preventing foot slap and toe drag, in addition to plantarflexion assistance for the forward propulsion of the body. During a gait cycle, an average power of 0.23 W is harvested, and an 8% improvement in the system energy efficiency is achieved.

Design of Muscle Reflex Control for Upright Standing Push-Recovery Based on a Series Elastic Robot Ankle Joint.

In physical human–robot interaction environment, ankle joint muscle reflex control remains significant and promising in human bipedal stance. The reflex control mechanism contains rich information of human joint dynamic behavior, which is valuable in the application of real-time decoding motion intention. Thus, investigating the human muscle reflex mechanism is not only meaningful in human physiology study but also useful for the robotic system design in the field of human–robot physical interaction. In this paper, a specialized ankle joint muscle reflex control algorithm for human upright standing push-recovery is proposed. The proposed control algorithm is composed of a proportional-derivative (PD)-like controller and a positive force controller, which are employed to mimic the human muscle stretch reflex and muscle tendon force reflex, respectively. Reflex gains are regulated by muscle activation levels of contralateral ankle muscles. The proposed method was implemented on a self-designed series elastic robot ankle joint (SERAJ), where the series elastic actuator (SEA) has the potential to mimic human muscle–tendon unit (MTU). During the push-recovery experimental study, the surface electromyography (sEMG), ankle torque, body sway angle, and velocity of each subject were recorded in the case where the SERAJ was unilaterally kneed on each subject. The experimental results indicate that the proposed muscle reflex control method can easily realize upright standing push-recovery behavior, which is analogous to the original human behavior.

Haptic Adaptive Feedback to Promote Motor Learning With a Robotic Ankle Exoskeleton Integrated With a Video Game.

Background: Robotic devices have been used to rehabilitate walking function after stroke. Although results suggest that post-stroke patients benefit from this non-conventional therapy, there is no agreement on the optimal robot-assisted approaches to promote neurorecovery. Here we present a new robotic therapy protocol using a grounded exoskeleton perturbing the ankle joint based on tacit learning control.Method: Ten healthy individuals and a post-stroke patient participated in the study and were enrolled in a pilot intervention protocol that involved performance of ankle movements following different trajectories via video game visual feedback. The system autonomously modulated task difficulty according to the performance to increase the challenge. We hypothesized that motor learning throughout training sessions would lead to increased corticospinal excitability of dorsi-plantarflexor muscles. Transcranial Magnetic Stimulation was used to assess the effects on corticospinal excitability.Results: Improvements have been observed on task performance and motor outcomes in both healthy individuals and post-stroke patient case study. Tibialis Anterior corticospinal excitability increased significantly after the training; however no significant changes were observed on Soleus corticospinal excitability. Clinical scales showed functional improvements in the stroke patient.Discussion and Significance: Our findings both in neurophysiological and performance assessment suggest improved motor learning. Some limitations of the study include treatment duration and intensity, as well as the non-significant changes in corticospinal excitability obtained for Soleus. Nonetheless, results suggest that this robotic training framework is a potentially interesting approach that can be explored for gait rehabilitation in post-stroke patients.

Kinematics of underactuated robotics for product carbon footprint

Product low-carbon design has become one of the important means of sustainable manufacturing. An important design principle should be to minimize the weight of the robot while maximizing its motion efficiency. Therefore, how to develop and analyze low-carbon robots is the focus of this paper. The illustration used in the paper is a novel proposal for an underactuated robotic ankle exoskeleton for human workers. Conventional robots have enough actuators to perform independent movements. In contrast, an underactuated device emphasizes the use of natural dynamic control systems. Kinematics does not take into account the causal force of motion to study moving objects. This paper uses kinematic ankle joint as an example to analyze kinematics. The human worker is the causal force for an exoskeleton design. In order to make it easier for human to use, this paper proposes a joint exoskeleton based on underactuated spherical parallel mechanism. The underactuated mechanism has reduced a lot of unnecessary weight and added more degree of freedom compared with the traditional mechanism. Through the optimal design of the mechanism to reduce its carbon footprint through its life cycle. The carbon footprint analysis of the underactuated robotic ankle exoskeleton is then discussed in detail, which is given as an example to demonstrate this approach.

Artificial Human Balance Control by Calf Muscle Activation Modelling

The natural neuromuscular model has greatly inspired the development of control mechanisms in addressing the uncertainty challenges in robotic systems. Although the underpinning neural reaction of posture control remains unknown, recent studies suggest that muscle activation driven by the nervous system plays a key role in human postural responses to environmental disturbance. Given that the human calf is mainly formed by two muscles, this paper presents an integrated calf control model with the two comprising components representing the activations of the two calf muscles. The contributions of each component towards the artificial control of the calf are determined by their weights, which are carefully designed to simulate the natural biological calf. The proposed calf modelling has also been applied to robotic ankle exoskeleton control. The proposed work was validated and evaluated by both biological and engineering simulation approaches, and the experimental results revealed that the proposed model successfully performed over 92% of the muscle activation naturally made by human participants, and the actions led by the simulated ankle exoskeleton wearers were overall consistent with that by the natural biological response.