Assistance Force Research Articles

Role-theoretic discourse analysis of German security policy: a case of German parliamentary debate on the mission in Afghanistan.

This article combines linguistic discourse analysis with role theory to create a role-theoretic discourse analysis framework for German security policy. To illustrate this, we employ topos analysis on 30 plenary minutes of parliamentary debates regarding the International Security Assistance Force mission in Afghanistan, conducted by German Members of Parliament between 2001 and 2014. We interpret their perception of Germany's roles in light of key behavioral norms related to German security policy. The parliamentary discourse, shaped by topoi, sets the stage for decisions on German military operations abroad. The use of topoi is influenced by dominant thought patterns, particularly the perspective on Germany's role in security policy held by the political elite. Political decisions, in turn, reflect behavioral preferences guided by these viewpoints. Our research reveals how changes in German security policy are mirrored in the discourse. This discourse is structured around five categories of topoi for legitimizing or delegitimizing military operations abroad: necessity, obligation, self-interest, capability and preparedness, and solution. An evaluation of the use of topoi through the lens of role theory indicates that perceptions of Germany's role have evolved over time, encompassing roles such as a "civilian power," a "normal state," and an "agenda-setting role" in sync with its foreign military engagements.

Extracorporeal Closed-Loop Respiratory Regulation for Patients With Respiratory Difficulty Using a Soft Bionic Robot.

Respiratory regulation is critical for patients with respiratory dysfunction. Clinically used ventilators can lead to long-term dependence and injury. Extracorporeal assistance approaches such as iron-lung devices provide a noninvasive alternative, however, artificial actuator counterparts have not achieved marvelous biomimetic ventilation as human respiratory muscles. Here, we propose a bionic soft exoskeleton robot that can achieve extracorporeal closed-loop respiratory regulation by emulating natural human breath. For inspiration, a soft vacuum chamber is actuated to produce negative thoracic pressure and thus expand lung volume by pulling the rib cage up and outward through use of external negative pressure. For expiration, a soft origami array under positive pressure pushes the abdominal muscles inward and the diaphragm upward. To achieve in vitro measurement of respiratory profile, we describe a wireless respiratory monitoring device to measure respiratory profiles with high accuracy, validated by quantitative comparisons with spirometer as gold-standard reference. By constructing a human-robot coupled respiratory mechanical model, a model-based proportional controller is designed for continuous tracking of the target respiratory profile. In experiments with ten healthy participants and ten patients with respiratory difficulty, the robot can adjust its assistive forces in real time and drive human-robot coupling respiratory system to track the target profile. The biomimetic robot can achieve extracorporeal closed-loop respiratory regulation for a diverse population. The soft robot has important potential to assist respiration for people with respiratory difficulty, whether in a hospital or a home setting.

Evaluation and modeling of diaphragm displacement using ultrasound imaging for wearable respiratory assistive robot.

Assessing the influence of respiratory assistive devices on the diaphragm mobility is essential for advancing patient care and improving treatment outcomes. Existing respiratory assistive robots have not yet effectively assessed their impact on diaphragm mobility. In this study, we introduce for the first time a non-invasive, real-time clinically feasible ultrasound method to evaluate the impact of soft wearable robots on diaphragm displacement. We measured and compared diaphragm displacement and lung volume in eight participants during both spontaneous and robotic-assisted respiration. Building on these measurements, we proposed a human-robot coupled two-compartment respiratory mechanics model that elucidates the underlying mechanism by which our extracorporeal wearable robots augments respiration. Specifically, the soft robot applies external compression to the abdominal wall muscles, inducing their inward movement, which consequently pushes the diaphragm upward and enhances respiratory function. Finally, we investigated the level and shape of various robotic assistive forces on diaphragm motion. This robotic intervention leads to a significant increase in average diaphragm displacement by 1.95 times and in lung volume by 2.14 times compared to spontaneous respiration. Furthermore, the accuracy of the proposed respiratory mechanics model is confirmed by the experimental results, with less than 7% error in measurements of both diaphragm displacement and lung volume. Finally, the magnitude of robotic assistive forces positively correlates with diaphragm movement, while the shape of the forces shows no significant relationship with diaphragm activity. Our experimental findings validate the effective assistance mechanism of the proposed robot, which enhances diaphragm mobility and assists in ventilation through extracorporeal robotic intervention. This robotic system can assist with ventilation while increasing diaphragm mobility, potentially resolving the issue of diaphragm atrophy. Additionally, this work paves the way for improved robotic designs and personalized assistance, tailored to the dynamics of the diaphragm in respiratory rehabilitation.

Characterizing the Effects of Adding Virtual and Augmented Reality in Robot-Assisted Training.

Extended reality (XR) technology combines physical reality with computer synthetic virtuality to deliver immersive experience to users. Virtual reality (VR) and augmented reality (AR) are two subdomains within XR with different immersion levels. Both of these have the potential to be combined with robot-assisted training protocols to maximize postural control improvement. In this study, we conducted a randomized control experiment with sixty-three healthy subjects to compare the effectiveness of robot-assisted posture training combined with VR or AR against robotic training alone. A robotic Trunk Support Trainer (TruST) was employed to deliver assistive force at the trunk as subjects moved beyond the stability limits during training. Our results showed that both VR and AR significantly enhanced the training outcomes of the TruST intervention. However, the VR group experienced higher simulator sickness compared to the AR group, suggesting that AR is better suited for sitting posture training in conjunction with TruST intervention. Our findings highlight the added value of XR to robot-assisted training and provide novel insights into the differences between AR and VR when integrated into a robotic training protocol. In addition, we developed a custom XR application that suited well for TruST intervention requirements. Our approach can be extended to other studies to develop novel XR-enhanced robotic training platforms.

Training Postural Balance Control with Pelvic Force Field at the Boundary of Stability.

This study characterizes the effects of a postural training program on balance and muscle control strategies in a virtual reality (VR) environment. The Robotic Upright Stand Trainer (RobUST), which applies perturbative forces on the trunk and assistive forces on the pelvis, was used to deliver perturbation-based balance training (PBT) in a sample of 10 healthy participants. The VR task consisted of catching, aiming, and throwing a ball at a target. All participants received trunk perturbations during the VR task with forces tailored to the participant's maximum tolerance. A subgroup of these participants additionally received assistive forces at the pelvis during training. Postural kinematics were calculated before and after RobUST training, including (i) maximum perturbation force tolerated, (ii) center of pressure (COP) and pelvic excursions, (iii) postural muscle activations (EMG), and (iv) postural control strategies (the ankle and hip strategies). We observed an improvement in the maximum perturbation force and postural stability area in both groups and decreases in muscle activity. The behavior of the two groups differed for perturbations in the posterior direction where the unassisted group moved towards greater use of the hip strategy. In addition, the assisted group changed towards a lower margin of stability and higher pelvic excursion. We show that training with force assistance leads to a reactive balance strategy that permits pelvic excursion but that is efficient at restoring balance from displaced positions while training without assistance leads to reactive balance strategies that restrain pelvic excursion. Patient populations can benefit from a platform that encourages greater use of their range of motion.

Enable Fully Customized Assistance: A Novel IMU-Based Motor Intent Decoding Scheme

Assisting human locomotion is essentially related to the assistive force profile, which can be determined from four aspects: timing, magnitude, shape and duration. Most current methods of decoding human motor intent enable the customized determination of the assistive force profile by providing information of different subsets of the four aspects. Trustworthy human-exoskeleton interaction essentially relates to determining the assistive force profile. Current methods of decoding human motor intent enable the customized determination of the assistive force profile by providing limited information of human kinetics. In this paper, we propose and validate a novel motor intent decoding scheme that can enable a fully customized assistive force profile, where only inertial measurement units (IMUs) are used. First, we improve the robustness of the IMU-based kinematic estimation by sampling IMU measurements that well meet the hinge-joint assumption, and by online calibrating axes’ direction in order to avoid the post-hoc analysis of joint axes’ directions during the determination of the body-fixed coordinate frame. Second, using the calculated kinematics as input, we develop a computationally efficient dynamic model, through which kinetics of users can be calculated in real-time. Finally, we leverage a cable-driven ankle exoskeleton method to validate the assistive performance of our motor intent decoding scheme. We perform experiments on ten healthy subjects to evaluate the accuracy of our algorithm, and the change of metabolic rate and muscle efforts under the exoskeleton’s assistance. The results show the improvement from determining the assistive force profile by nominal curves and the feasibility of our algorithm.

Servo-controlled Semi-rigid Exoskeleton Designed for the Human Knee

Musculoskeletal injuries are occurring more and more frequently, with one of the main causes being the increasing number of new patients who sustain knee structure injuries. Currently, exoskeletons that assist the knee joint are either fully rigid or soft systems, which induce the risk of misalignments due to the complicated nature of the kinematics of the knee joint or require additional anchors or mechanical parts that may cause discomfort or force unnecessary weight upon the user. In this paper, a semi-rigid exoskeleton principle is introduced. This exoskeleton addresses the concerns of both rigid and soft exoskeletons while performing the same benefits by establishing a pre-determined route for the tendon. This exoskeleton can provide up to 37.26Nm assistive torque to the knee joint. The system’s effectiveness was validated through a series of experiments which included testing its range of motion, total tensile force, and accuracy and safety of the pose detection system. The prototype had successful results, and the overall system is efficient, flexible, and easy to use. Future work will focus more on a customizable system in which the users can determine the amount of assistive torque force they need to be applied to their knee joint depending on their current physical ability.

Development of Wearable Finger Prosthesis with Pneumatic Actuator for Patients with Partial Amputations

As the number of patients with amputations increases, research on assistive devices such as prosthetic limbs is actively being conducted. However, the development of assistive devices for patients with partial amputations is insufficient. In this study, we developed a finger prosthesis for patients with partial amputations. The design and mathematical modeling of the prosthesis are briefly presented. A pneumatic actuator, based on the McKibben muscle design, was employed to drive the finger prosthesis. We characterized the relationship between the actuator’s force and axial length changes with varying pressure. An empirical model derived from conventional mathematical modeling of force and axis length changes was proposed and compared with experimental data, and the error was measured to be between about 3% and 13%. In order to control the actuator using an electromyography (EMG) signal, an electrode was attached to the user’s finger flexors. The EMG signal was measured in relation to the actual gripping force and was provided with visual feedback, and the magnitude of the signal was evaluated using root mean square (RMS). Depending on the evaluated EMG signal magnitude, the pressure of the actuator was continuously adjusted. The pneumatic pressure was adjusted between 100 kPa and 250 kPa, and the gripping force of the finger prosthesis ranged from about 0.7 N to 6.5 N. The stiffness of the prosthesis can be varied using the SMA spring. The SMA spring is switched to a fully austenite state at 50 °C through PID control, and when the finger prosthesis is bent to a 90° angle, it can provide approximately 1.2 N of assistance force. Finally, the functional evaluation of the finger prosthesis was performed through a pinch grip test of eight movements.

Assistance control strategy for upper-limb rehabilitation robot based on motion trend

Abstract. Robot-assisted rehabilitation has proven to improve a subject's upper-extremity motor function. However, it is still challenging to control the robot to provide minimal assistance based on the subject's performance. This paper proposes a motion-trend-based assistance control strategy to solve this problem. The control strategy provides the corresponding normal and tangential forces by constructing an adaptive virtual assistance force field around a predetermined training trajectory. In the normal direction, a performance function based on the position-tracking error and normal motion trend is established to adjust the normal assistance force field strength in real time; in the tangential direction, a performance function based on the tangential interaction force and tangential motion trend is established to adjust the tangential assistance force field strength in real time. Additionally, good motion trends can quickly reduce the assistance force field. The normal motion trend represents the state of the subject moving toward the target trajectory, and the tangential motion trend represents the state of increasing tangential interaction force. Finally, the performance of this control strategy was evaluated by training experiments with eight healthy subjects. Preliminary experiments showed that the normal assist force in the active movement phase was 92.48 % smaller than that in the poor phase, and the tangential assist force was 90.73 % smaller than that in the slack phase. And the normal assist force and tangential assist force will become zero within 0.2 s when the subject has a good tendency to move. This shows that the control strategy proposed in this paper can quickly adjust the assistance according to the subject's motor performance. In addition, the assistance can be quickly reduced when the subject has a good movement trend. Future work will incorporate OpenSim (muscle and bone simulation software) to develop a pathway suitable for the subject's arm rehabilitation.

Design control and actuator selection of a lower body assistive exoskeleton with 3-D passive compliant supports

Physical human–robotic interaction is a crucial area of concern for robotic exoskeletons. Lower weight requirement for the worn exoskeletons limits the number and size of joint actuators, resulting in a low active degree of freedom for the exoskeletons with joint actuators having limited power and bandwidth. This limitation invariably results in reduced physical human–robotic interaction performance for the exoskeleton. Recently several techniques have been proposed for the low active degree of freedom exoskeletons with improved physical human–robotic interaction performance using better load torque compensators and improved active compliance. However, effective practical implementation of these techniques requires special hardware and software design considerations. A detailed design of a new lower body exoskeleton is proposed in this paper that can apply these recently developed techniques to practically improve the physical human–robotic interaction performance of the worn exoskeletons. The design presented includes the exoskeleton's structural design, new joint assemblies and the design of novel 3-D passive, compliant supports. A methodology of selecting and verifying the joint actuators and estimating the desired assistive forces at the contact supports based on human user joint torque requirements and the degree of assistance is also thoroughly presented. A new CAN-based master–slave control architecture that supports the implementation of recent techniques for improved physical human–robotic interaction is also fully presented. A new control strategy capable of imparting simultaneous impedance-based force tracking control of the exoskeleton in task space using DOB-based-DLTC at joint space is also thoroughly presented. Simulation verification of the proposed strategy based on the actual gait data of elderly is presented lastly.

Design and Implementation of Upper-Body Exoskeleton for Assistance of Individuals With Manual Handling Tasks

AbstractThis paper illustrates the design and testing of an upper-body exoskeleton for the assistance of individuals with load-lifting and load-carrying tasks, and the provided assistive force can well match with the force required by the human. First, the biomechanics of the human lumbar during the squat lifting of an object is described. Next, the modeling of the exoskeleton is introduced. Additionally, the hardware design of the exoskeleton is presented. The exoskeleton is mainly composed of a back-assist mechanism and an upper extremity labor-saving mechanism, which can assist the wearer’s lumbar during the squat lifting of an object and assist the wearer’s arms to carry an object during walking, respectively. Finally, experiments are conducted to evaluate the performance of the developed upper-body exoskeleton. The experimental results demonstrate that the exoskeleton has the potential to provide assistance for individuals with manual handling tasks. An average assistive force of 44.8 N can be provided for the wearer to lift a 10-kg object. During the squat lifting of the 10-kg object, reductions of 31.86% and 28.30% of the average muscle activities of the wearer’s lumbar erector spinae and thoracic erector spinae are observed, respectively. In addition, a reduction of 23.78% of the average muscle activity of the wearer’s biceps brachii is observed during walking while carrying the 10-kg object.

The Establishment of a Humanitarian Assistance Force in the Community of Portuguese-Speaking Countries (CPLP)

The study seeks to identify advances in Defense Cooperation in the Community of Portuguese-speaking countries (CPLP, in Portuguese) by creating a Humanitarian Assistance Force (HAF). The research problem analyzes the opportunities and challenges of creating a HAF in the Community. The hypothesis indicates that the CPLP’s cooperation in Defense, since 1998, has had an extraordinary development since it is consolidated as a dynamic and committed Defense Architecture among all Member States, whose expertise in human resources and equipment are the main potential opportunities. However, the challenge lies in materializing this involvement into concrete resultsthat can respond, first, to the needs of each country and the CPLP and, second, to provide further vitality and operationality to the Defense cooperation under the guidelines for strategic collaboration in the organization and aligned with the CPLP’s New Strategic Vision. Therefore, it is understood that the CPLP, by proposing an HAF, seeks to become an organization with more capacity to react purposefully and positively to disasters in the Member States. Furthermore, risk management is essential to assess and analyze risks and plan and execute specific actions to prevent and reduce destruction. Based on hypothetical and deductive methods, the study applies the qualitative researchprotocol. Regarding the objectives, the study is characterized as descriptive explanatory and uses bibliographic and documentary surveys (which mainly originated in the CPLP).

Lessons learned from the ROLE 3rd International Hospital in Afghanistan. The necessity of training in expanded surgical skills

Introduction: Acquiring and maintaining a wide range of surgical skills is challenging both for military surgeons and all physicians providing surgical treatment in a wartime conflict. In the article we analyze the activities of the surgeons of the field surgical team of the Army of the Czech Republic operating in the multinational hospital ROLE 3 in Kabul, Afghanistan, in the International Security and Assistance Force (ISAF) operation. Methods: All patients undergoing surgery between 21st June and 26th September 2012 were evaluated. ISAF soldiers, Afghan Army soldiers, Afghan National Police officers, Afghan civilians and non-Afghan civilians of various nationalities were operated on including children. Combat and noncombat injuries and illnesses requiring acute surgical treatment or elective surgery were monitored. Results: In a period of three months, a total of 442 procedures were performed on 263 patients, 23% of whom were pediatric patients with the mean age of 10 years. Thirty seven percent were operated on due to a combat injury, 29% were operated on due to a non-combat injury, and 34% of the patients were operated on due to a chronic or acute illness. In combat injuries, 57% were combined injuries requiring a solution based on the principle of damage control surgery, and 26% required life-saving procedures for injuries to the chest and large vessels. Conclusion: A military surgeon, as well as a surgeon treating wounds in a war conflict, must have extensive professional knowledge and must master a wide variety of surgical skills to quickly and effectively deal with especially life-threatening conditions, including thoracic and vascular trauma. In contrast to the direction of current surgery towards specializations and sub-specializations, it seems necessary to develop and implement in the Czech Republic a comprehensive surgical training program focusing on war injuries.

Dynamic optimization of anchor points positions in a cable driven exosuit: a computer simulation approach

The purpose of this study is to simulate the different walking adaptation strategies and their impact on muscle activities while changing the anchor point position of an exosuit in hip extension assistance motion. In particular, muscle activation and metabolic power consumption are assessed at varying levels of assistive force actuation that alters the position of anchor points. OpenSim software was used to perform simulations of 10 elderly subjects at comfortable gait speed while varying the anchor point positions of the thigh. Compared to unassisted gait, the extension assistance at placements below 40% (proximal) requires an increase in metabolic cost to maintain gait characteristics. At 40%, energy consumption corresponds to unassisted gait. From 50% proximal to distal positions, a reduction in metabolic cost is observed, with a minimum at 80%. The variation of the metabolic cost at different positions of the anchor point is reflected in the muscular activities, with an increase when the cable is placed below 40% of the total length of the thigh and a decrease from this position onwards. The activation level and metabolic cost exerted by the hip flexors and extensors muscles may be optimized during the exosuit actuation. The dynamics of the muscles spanning joints not actuated by the exosuit are not influenced by the actuation. The results and analysis provide information to optimize actuation profiles in the design of exosuits to assist gait for older adults and, thus, promote active aging and improving rehabilitation routines.

Motor Characteristics of Human Adaptations to External Assistive Forces

Technology advancement has enabled the development of robotic exoskeletons that are portable, powerful, and sufficiently smart to be of practical use in the real world. These devices provide partial assistive forces that increase their user’s physical strength to better meet the demands of everyday life and have potential applications in various settings. Examples include helping older adults maintain their independence and preventing musculoskeletal injuries among factory workers. Although great strides have been made to improve the performance and usability of these devices, human characteristics and the way humans adapt to the external assistive forces from these devices are rarely explicitly considered in their development. A common assumption is that if the provided assistive forces are aligned with the intent of users, users can easily “switch off” their muscles and effectively utilize this assistive force. In this review, we demonstrate that human adaptations to external assistive forces can lead to inefficiencies or conflicts that decrease the effectiveness of robotic exoskeletons. We then discuss the motor characteristics of human adaptations to external assistive forces.

Empowering Hand Rehabilitation with AI-Powered Gesture Recognition: A Study of an sEMG-Based System.

Stroke is one of the most prevalent health issues that people face today, causing long-term complications such as paresis, hemiparesis, and aphasia. These conditions significantly impact a patient's physical abilities and cause financial and social hardships. In order to address these challenges, this paper presents a groundbreaking solution-a wearable rehabilitation glove. This motorized glove is designed to provide comfortable and effective rehabilitation for patients with paresis. Its unique soft materials and compact size make it easy to use in clinical settings and at home. The glove can train each finger individually and all fingers together, using assistive force generated by advanced linear integrated actuators controlled by sEMG signals. The glove is also durable and long-lasting, with 4-5 h of battery life. The wearable motorized glove is worn on the affected hand to provide assistive force during rehabilitation training. The key to this glove's effectiveness is its ability to perform the classified hand gestures acquired from the non-affected hand by integrating four sEMG sensors and a deep learning algorithm (the 1D-CNN algorithm and the InceptionTime algorithm). The InceptionTime algorithm classified ten hand gestures' sEMG signals with an accuracy of 91.60% and 90.09% in the training and verification sets, respectively. The overall accuracy was 90.89%. It showed potential as a tool for developing effective hand gesture recognition systems. The classified hand gestures can be used as a control command for the motorized wearable glove placed on the affected hand, allowing it to mimic the movements of the non-affected hand. This innovative technology performs rehabilitation exercises based on the theory of mirror therapy and task-oriented therapy. Overall, this wearable rehabilitation glove represents a significant step forward in stroke rehabilitation, offering a practical and effective solution to help patients recover from stroke's physical, financial, and social impact.

Fuzzy Adaptive Passive Control Strategy Design for Upper-Limb End-Effector Rehabilitation Robot.

Robot-assisted rehabilitation therapy has been proven to effectively improve upper-limb motor function in stroke patients. However, most current rehabilitation robotic controllers will provide too much assistance force and focus only on the patient's position tracking performance while ignoring the patient's interactive force situation, resulting in the inability to accurately assess the patient's true motor intention and difficulty stimulating the patient's initiative, thus negatively affecting the patient's rehabilitation outcome. Therefore, this paper proposes a fuzzy adaptive passive (FAP) control strategy based on subjects' task performance and impulse. To ensure the safety of subjects, a passive controller based on the potential field is designed to guide and assist patients in their movements, and the stability of the controller is demonstrated in a passive formalism. Then, using the subject's task performance and impulse as evaluation indicators, fuzzy logic rules were designed and used as an evaluation algorithm to quantitively assess the subject's motor ability and to adaptively modify the stiffness coefficient of the potential field and thus change the magnitude of the assistance force to stimulate the subject's initiative. Through experiments, this control strategy has been shown to not only improve the subject's initiative during the training process and ensure their safety during training but also enhance the subject's motor learning ability.

Development of a hierarchical control strategy for a soft knee exoskeleton based on wearable multi-sensor system

Soft exoskeleton is a newly emerging approach for providing assistive forces to the movement of disabled individuals, which has aroused the interest of many researchers due to its promising prospects in rehabilitation training and motion assistance. In this article, a wearable wireless multi-sensor system and a hierarchical control architecture are developed for a soft knee exoskeleton. First, the major components of the soft knee exoskeleton are introduced, including the flexible Bowden-cable actuators, the soft wearable components, and the sensing modules and the control system. The wearable wireless multi-sensor system consists of an inertial measurement unit–based knee flexion–extension angle sensing module, a surface electromyogram–based joint torque estimation module, a miniature pulling force sensing module, and a central communication unit. And then, a three-level hierarchical control strategy—which fuses a high-level motion recognition and torque estimation algorithm, a mid-level knee trajectory generation strategy, and a low-level fuzzy impedance controller—is proposed to realize human motion assistance. Finally, experiments are carried out to verify the effectiveness of the proposed control strategy. The experimental setup is established with the soft knee exoskeleton, a treadmill, a wearable robotic rotary joint with an encoder, and an inelastic rope. The experimental result indicates that the root mean square errors of the joint angle estimation strategy and joint torque estimation strategy are less than 4.3° and 4.8 Nm, while the surface electromyogram–based assistance efficiency and torque-based assistance efficiency under different loading conditions are higher than 10.2% and 18.2%, respectively.

Stiffness optimization based on muscle fatigue and muscle synergy for passive waist assistive exoskeleton

PurposeThis paper aims to optimize the stiffness coefficient of the elastic element for a passive waist assistive exoskeleton (WAE). There is a tradeoff between stiffness coefficient of elastic element of the exoskeleton and work efficiency of the wearer, because elastic element affects original bending motion of the wearer and the force requirement of erector spinae is compensated by the other muscles. However, there is no accepted conclusion on how to determine the proper stiffness coefficient, especially with respected to the effort of groups of muscles, not only erector spinae.Design/methodology/approachIn this study, a consumption indicator based on muscle fatigue of seven muscles is proposed and a Bayesian-based human-in-the-loop optimization approach is adopted to optimize the stiffness coefficient. Pneumatic artificial muscles are used to replace the mechanical elastic part to adjust the assistive force automatically. The proposed optimization method is verified by the way of load-lifting experiments with three different conditions: without exoskeleton, with fixed air pressure and with optimized air pressure. Six subjects participated in the experiment and each experiment is performed in different day.FindingsCompared with No-Exo condition and static assistance condition, the parameter-optimized waist exoskeleton averagely reduces muscle fatigue of the six subjects by 45.30 ± 29.14% and 30.94 ± 30.29%, respectively. The experimental results indicate that the proposed method is effective to reduce muscle fatigue during stoop lifting task.Originality/valueThis paper provides a novel cost function construction method based on muscle fatigue and muscle synergy for passive WAE stiffness optimization.

Age-Related Reliability of B-Mode Analysis for Tailored Exosuit Assistance.

In the field of wearable robotics, assistance needs to be individualized for the user to maximize benefit. Information from muscle fascicles automatically recorded from brightness mode (B-mode) ultrasound has been used to design assistance profiles that are proportional to the estimated muscle force of young individuals. There is also a desire to develop similar strategies for older adults who may have age-altered physiology. This study introduces and validates a ResNet + 2x-LSTM model for extracting fascicle lengths in young and older adults. The labeling was generated in a semimanual manner for young (40,696 frames) and older adults (34,262 frames) depicting B-mode imaging of the medial gastrocnemius. First, the model was trained on young and tested on both young (R2 = 0.85, RMSE = 2.36 ± 1.51 mm, MAPE = 3.6%, aaDF = 0.48 ± 1.1 mm) and older adults (R2 = 0.53, RMSE = 4.7 ± 2.51 mm, MAPE = 5.19%, aaDF = 1.9 ± 1.39 mm). Then, the performances were trained across all ages (R2 = 0.79, RMSE = 3.95 ± 2.51 mm, MAPE = 4.5%, aaDF = 0.67 ± 1.8 mm). Although age-related muscle loss affects the error of the tracking methodology compared to the young population, the absolute percentage error for individual fascicles leads to a small variation of 3-5%, suggesting that the error may be acceptable in the generation of assistive force profiles.