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The Dutch police are considering using autonomous robotic dogs in drug lab raids to protect officers from dangerous situations. The robots, powered by artificial intelligence, would be able to inspect the labs, identify dangerous chemicals, and create a map of the location. This would allow human officers to plan a safe way to dismantle the lab. While there are safety and political concerns with using autonomous robots, experts believe that the benefits, such as increased speed and human safety, outweigh the risks. [Extracted from the article]

This paper proposes an active torque-based gait adjustment multi-level control strategy for lower limb patient–exoskeleton coupling system (LLPECS) in rehabilitation training. The proposed controller has three levels of high, middle, and low sub-controllers: gait adjustment layer (high-level), interaction torque design layer (middle-level), and trajectory tracking layer (low-level). The high-level sub-controller uses an adaptive central pattern generator (ACPG) to adjust the desired gait for rehabilitation training according to the patient's active torque. In the middle-level sub-controller, the desired interaction torque is designed with neural networks and the estimated muscle torque by utilizing nonlinear disturbance observer (NDO). In the low-level sub-controller, a time delay estimation-based prescribed performance model free control is designed for the accurate tracking performance of the exoskeleton, so as to make the actual interaction torque track the desired value. An exoskeleton virtual prototype, which is developed in SolidWorks, has been imported to MATLAB/Simulink to conduct co-simulations in the SimMechanics environment. The results of co-simulations demonstrate the effectiveness of the proposed control strategy when the patient's muscle torque is at different recovery degrees. [ABSTRACT FROM AUTHOR]

• Moisture-responsive actuators are developed from seafood dried bonito flakes. • Such actuator has a gradient structure along the vertical direction. • Such actuator exhibits excellent actuation performance and biodegradability. • Soft biomimetic robots and smart wearable clothing are successfully constructed. Exploring high-performance soft actuators from biomass resources is significant for developing eco-friendly smart devices. Dried bonito (DB) flake is a common food as well as a biomass material, and it can produce irregular motion in changed moisture, just like dancing. Inspired by this intriguing phenomenon, a cost-effective, biocompatible, and biodegradable moisture-responsive DB film actuator with a gradient structure is developed. The DB film actuator exhibits rapid and reversible bending deformation triggered by a humidity gradient with a high bending speed (40° s–1) and a maximum bending angle (180°). Moreover, the DB film actuator shows large bending deformation (–71° to +51°) with a high actuation force (214.7 Pa) in response to changes in relative humidity. Furthermore, the actuation performance can be also tuned by adjusting the thickness of the film. Potential applications of this actuator, including smart grippers, crawling robots, and biomimetic flowers for visible humidity sensing, are demonstrated. More importantly, smart sweat-responsive wearables that automatically deform to promote sweat evaporation and convection during exercise are constructed based on the actuator, making it promising for adaptive personal thermal management. This work offers an easily processable, cost-effective, and environmentally benign strategy to construct moisture-responsive actuators for future eco-friendly smart devices. [Display omitted] [ABSTRACT FROM AUTHOR]

The aim of our study was to evaluate the long-term effects of back-support exoskeletons (BSEs) in occupational settings. Valuable insights were gained through repeated in-depth interviews with occupational safety professionals over a one-year period regarding the use and impact of BSEs over a one-year period. The results highlight a significant lack of user acceptance, primarily due to movement restrictions and discomfort. Passive BSEs (PassEXOs) were reported to be sometimes uncomfortable, restricting mobility and causing pressure point discomfort, while quasipassive soft BSEs (SoftEXO) received more positive feedback. In addition, factors such as proper fit, adjustability, hygiene maintenance, and the ease of donning and doffing were identified as key determinants of employee acceptance of BSEs. By gaining a deeper understanding of these factors, organisations can facilitate a successful and sustainable integration of BSE technology into the workplace. [ABSTRACT FROM AUTHOR]

This article provides an update on new codes and fees that will be effective from April 1, 2024. The article explains the process for submitting code applications and how the Healthcare Common Procedure Coding System (HCPCS) works. It also discusses the creation of new codes and the establishment of fees for certain orthoses and prostheses. The article advises readers to update their systems and billing sheets to reflect the new codes and fees. [Extracted from the article]

These gems are identical to natural gems - and alas, nearly as expensive. Spinning Gold If you can make gems out of powdered rock, could you ever spin gold out of straw, like Rumpelstiltskin? To grow gems, scientists melt the mineral ingredients of the gemstone in a hot furnace, or with lasers. Features Hundreds of years ago, the idea of seeing pictures move, talking to someone far away, or flying to another city through the air would have sounded like pure fantasy. [Extracted from the article]

An interview with Doctor Kristin Chrouser of University of Michigan and Doctor Amy Park of Cleveland Clinic is presented. They talk about the challenges and issues in surgery-related musculoskeletal injuries. They discuss how surgical ergonomics could help alleviate or prevent the work-related musculoskeletal disorders that could affect vascular surgeons, microsurgeons, and urologists. They explain the need for surgeons to be mentally and physically conditioned in their job.

Chengdu, a city in China's Sichuan province, has transformed into an innovation hub and global talent magnet. The city combines its rich history with cutting-edge technology, making it a place where traditional life and technological advancement coexist. Chengdu's focus on technological innovation has led to impressive growth in its tech landscape, with numerous higher education institutions, research centers, and hi-tech enterprises. The city also prioritizes the well-being of its residents, with initiatives to improve healthcare, education, and cultural experiences. Chengdu's success in balancing technological advancement with quality of life has earned it the title of China's happiest city for 15 consecutive years. The city's commitment to nurturing talent has attracted professionals from around the world, contributing to its status as an innovative hub. [Extracted from the article]

• A balance control framework for lower limb exoskeleton is proposed in this study. It combines a neuromuscular controller with a feedback controller, and constructs an observer through oscillators as a bridge between the two kinds of controller. • According to the motion characteristics of lower limb exoskeleton, an improved repetitive learning control method is proposed, which has better tracking effect for walking. • The balance control system is applied to the control of a real lower limb exoskeleton. Simulation and experimental results show that the integrated control system has a better control effect than the simple biological control method. In recent years, several biological frameworks have been proposed to imitate human motion and control lower limb exoskeletons. Compared with position or impedance tracking of defined joint trajectories, this kind of strategy can reproduce human walking dynamics, and tolerate external disturbance. The output of this kind of strategy is anticipatory feedforward torque, which means that the controller needs to have sufficient prior knowledge on neurology. Moreover, lower limb exoskeletons are fundamentally different from humans, which weakens the ability of the controller to resist external internal interference. Thus, pure feedforward control hardly achieves a flexible movement like that of a human. In this study, we propose a feedback control framework based on repetitive learning control (RLC) to enhance the anti-interference capability of a neuromuscular controller. The controller consists of two parts: (1) A data-driven morphed nonlinear phase oscillator is used as a state observer to learn the changing law of an exoskeleton's posture and center of mass and to construct a stable limit cycle in the state space. (2) A posture and centroid tracker based on RLC is utilized to track the output of oscillators and achieve a natural balance recovery process. Simulation and experimental results show that the integrated control system has a better control effect than the simple biological control method. [ABSTRACT FROM AUTHOR]

An exoskeleton suit that boosts leg motion helps people sprint faster, according to a small study. Non-elite runners sprinted a 200-metre race 0.97 seconds faster while wearing the exosuit, which weighs 4.4 kilograms, than they did when they ran as normal (Science Robotics, doi.org/gssv6g). Why nuts dance in fizzy drinks When an object like a raisin or nut is dropped into a carbonated liquid, bubbles gather on its exterior and push it upwards. [Extracted from the article]

Copyright of Zeitschrift für Arbeitswissenschaft is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Zeitschrift für Arbeitswissenschaft is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

A recent study conducted by a researcher from Universitat Jaume I focused on designing a custom-made six-bar exoskeleton for pulp pinch grasp rehabilitation in stroke patients. The exoskeleton, based on the pulp pinch movement, was customized from 3D scans of the patient's hand and optimized using a two-stage genetic process. This innovative device delivers a stable force to the fingertip, enabling repetitive movements to improve rehabilitation consistency and facilitate home-based therapy. The research aims to address neuromotor disabilities caused by stroke, particularly impacting index finger function in daily activities. [Extracted from the article]

A recent study from the University of New South Wales (UNSW) explores the use of deep learning in robotics for personalized gait rehabilitation. The research focuses on designing robotic exoskeletons for lower limb rehabilitation, emphasizing the need for individualized adjustments based on leg anatomy. By integrating a genetic algorithm with deep learning, the study aims to optimize the functionality of robotic systems for post-stroke patients. The findings suggest that this novel approach can accurately generate customized gait trajectories, showcasing the potential of computational intelligence in enhancing rehabilitation robotics. [Extracted from the article]

Researchers at the University of Sussex have developed a new active control framework for robot-aided bilateral treatment in hemiplegic rehabilitation. The framework uses optimal trajectory deformation to ensure safety in the leader-follower paradigm of bilateral treatment. By employing physically interactive trajectory deformation, abnormal motion patterns can be rectified, leading to enhanced human-robot interaction. This research has been peer-reviewed and published in the IEEE/ASME Transactions on Mechatronics. [Extracted from the article]

A study conducted by Zhejiang University in Hangzhou, China, focused on the efficacy and safety of using a unilateral lower limb exoskeleton combined with conventional treatment in post-stroke rehabilitation for patients with hemiplegia. The research involved a multicenter randomized controlled trial with 92 participants, showing that the group using the exoskeleton device had significantly improved balance function compared to the control group. The study concluded that the combination of the exoskeleton device and conventional treatment was effective and safe for balance function training in post-stroke hemiplegic patients. [Extracted from the article]

A recent study conducted by the Bulgarian Academy of Sciences has developed a novel exoskeleton robot for home rehabilitation of stroke-affected patients. The exoskeleton is designed as a one-degree-of-freedom four-bar mechanism that guides the human index finger in performing a finger curl exercise motion. The device is the first lateral, stand-alone mechanism capable of carrying the weight of the human hand, eliminating the need for the user to wear it. The proposed design has been proven effective for index finger rehabilitation and can be modified for use with the middle finger as well. [Extracted from the article]

A patent application has been submitted for an upper-body robotic exoskeleton by inventors Ashish Warren Deshpande and Bongsu Kim. The exoskeleton is designed to be worn by a person and aims to provide mechanical power to assist with tasks such as telemanipulation, man-amplification, and rehabilitation. The invention specifically focuses on improving upper-body robotic exoskeletons, which have potential applications in stroke treatment and recovery. The patent application includes detailed descriptions of the robotic shoulder joint, robotic exoskeleton, and robotic forearm joint. [Extracted from the article]

Ossur Iceland Ehf has been issued a patent for an interface system in an exoskeleton. The patent aims to address technical issues with existing exoskeleton devices, such as discomfort, weight, and alignment with the human body. The interface system is designed to support assistive devices in the exoskeleton, increase comfort, reduce injuries, and improve productivity. It can be adjusted to accommodate different user sizes and maintain an ergonomically favorable body position. The patent includes claims for a posterior strut and an interface system. [Extracted from the article]

A recent study conducted at Texas A&M University investigated the use of shoulder exoskeletons in a visuomotor upper extremity wiring task over three days. The study found that participants in the exoskeleton group reported lower perceived workload and higher task accuracy compared to the control group, suggesting that the exoskeletons provided physical and cognitive benefits. Neuroergonomics analysis also revealed differences in neural signatures between the two groups, indicating that the exoskeleton group exhibited increased activation in motor function-related brain regions. These findings suggest that shoulder exoskeletons can improve performance in tasks that require complex cognitive processing. [Extracted from the article]

Researchers at Huazhong University of Science and Technology in Wuhan, China have developed deep learning-driven multimodal information fusion frameworks for lower limb motion recognition. By leveraging the power of deep learning, the researchers constructed several end-to-end frameworks, achieving high accuracy in recognizing different types of lower limb motions in healthy subjects and patients with stroke. The proposed frameworks show promise in supporting the development of human-robot collaborative lower limb exoskeletons or rehabilitation robots. The research has been peer-reviewed and published in Biomedical Signal Processing and Control. [Extracted from the article]

A study conducted by the University of Ulsan in Seoul, South Korea, explored the effects of exoskeleton-assisted gait training on stroke patients. The study involved 30 chronic stroke patients who were randomly assigned to either a group that received training with a wearable powered exoskeleton or a control group that underwent treadmill training. The primary outcome measured was changes in oxyhemoglobin levels, which represent cortical activity in the motor cortices. The study found that the group receiving exoskeleton-assisted training showed significantly higher cortical activity and improvements in walking ability and voluntary strength compared to the control group. The researchers concluded that exoskeleton-assisted gait training can induce cortical modulation effects and improve motor function in stroke patients. [Extracted from the article]

A study conducted by researchers at Shenzhen Technology University in China explores the use of lower limb exoskeleton robots for gait rehabilitation in stroke patients. The researchers developed an Individualized Gait Trajectory Generation (IGTG) method based on Fast Fourier Transform (FFT) to approximate and regress pre-stroke gaits. The algorithm was trained using data from healthy subjects and then applied to generate personalized trajectories for stroke patients. Clinical trial results showed that rehabilitation training using these individualized gait trajectories resulted in significant reductions in blood oxygen saturation and heart rate compared to training with fixed trajectories. [Extracted from the article]

A recent study conducted by researchers at the University of Michigan has focused on back injuries and the fatigue experienced by the quadriceps during repetitive lifting, lowering, and carrying tasks. The researchers developed a task-adaptive knee exoskeleton controller that can assist with various movements such as squatting, walking on different terrains, and ascending or descending ramps and stairs. The controller effectively reduced quadriceps effort and improved performance and posture during repetitive lifting and lowering tasks. The findings suggest that this versatile control framework can mitigate quadriceps fatigue and its negative effects across multiple tasks. [Extracted from the article]

A patent has been issued for an exoskeleton finger rehabilitation training device developed by inventors from Southeast University in China. The device aims to improve the rehabilitation of finger function in patients with paralysis or dyskinesia caused by cerebral stroke. The device features an independent rehabilitation training mechanism for each finger, allowing for more finger actions during exercise and better rehabilitation outcomes. The device is designed to be placed on the back of the palm, providing a complete range of motion for the fingers without restricting the patient's ability to clench their hand. [Extracted from the article]

A recent report from the University of Shanghai for Science and Technology discusses the potential of wearable trunk exoskeletons in fields such as healthcare and industry. The report focuses on the importance of intention recognition control in users' daily use of exoskeletons. The researchers reviewed 50 articles published between 2013 and 2023 and identified several promising research directions for the development of trunk exoskeleton technology. This research has been peer-reviewed and provides valuable insights for further advancements in the field of neurorehabilitation. [Extracted from the article]

A recent report discusses the issue of work-related musculoskeletal disorders (WMSDs) in healthcare workers and the potential use of exoskeletons to aid in manual handling tasks. The report highlights the limitations of traditional measurement methods and introduces a flexible sensor-based approach using a wireless technology called BioStamp nPoint. The objective of the study was to explore the effects of a back exoskeleton on joint kinematics during patient handling. The research provides new insights into human factors and ergonomics and offers potential solutions to address the challenges faced in this field. [Extracted from the article]

A researcher from Tianjin University of Technology and Education in China has published a study on the design and analysis of a rehabilitation evaluation system for a finger rehabilitation robot. The current methods for evaluating hand dysfunction in patients face challenges such as inconsistent standards and incomplete quantification processes. To address these issues, the researcher developed a system that integrates various rehabilitation training modes and utilizes an exoskeleton finger rehabilitation robot. The system was tested on stroke patients and healthy subjects, and the results showed that the robotic rehabilitation evaluation was consistent with clinical evaluations. This research provides valuable insights into the field of robotics and its potential applications in rehabilitation. [Extracted from the article]

A recent study conducted by researchers from Texas A&M University explored the use of soft passive low back exoskeletons (LBEs) in a dynamic work environment, specifically focusing on tasks performed by Emergency Medical Technicians (EMTs). The study found that the use of LBEs resulted in lower muscular demands and improved kinematics, although these benefits were task-specific. Interestingly, EMTs were not able to recognize the benefits during the tasks, indicating a mismatch between subjective perception and objective outcomes. This research provides valuable insights into the potential of LBEs in reducing the risk of work-related low back injuries for EMTs. [Extracted from the article]

A recent study conducted by researchers at the University of North Carolina Chapel Hill explores the use of soft pneumatic actuators in wearable robotic systems, specifically hand exoskeletons. These actuators are lightweight, integrated with clothing, and can accommodate uncontrolled degrees of freedom. The researchers designed an actuator consisting of a hollow chamber that can conform to the shape of the fingers and assist with finger extension. They tested different chamber designs and dimensions, and created a prototype hand exoskeleton with the best-performing parameters. The study concludes that these soft actuators are feasible for promoting finger extension and offer a more comfortable and safer alternative to pulling for digit extension. [Extracted from the article]

A recent study conducted by researchers at Texas Tech University has found that the use of exoskeletons during lifting tasks may impair physical and cognitive performance among novice users. The study involved 32 participants with no prior experience using exoskeletons, who performed lifting tasks with and without the support of back- and leg-support exoskeletons. The results showed that exoskeleton use led to slower lifting task performance and increased target detection errors, suggesting that novice users may experience physical interference, discomfort, and increased mental workload while wearing an exoskeleton. This research provides valuable insights into the potential limitations of exoskeleton technology for certain users. [Extracted from the article]

Researchers at Northeast Forestry University in Harbin, China have developed a wearable soft hand rehabilitation device (HRD) for individuals with hand injuries. The device is actuated by shape memory alloy (SMA) wires and has been redesigned to be 36.7% shorter than previous models. The researchers also designed a supporting structure for the SMA wires to ensure optimal actuation. Experimental results showed that the device is safe to use and can assist in hand function rehabilitation. The study was published in the Journal of Mechanics in Medicine and Biology. [Extracted from the article]

A recent study conducted at Virginia Polytechnic Institute and State University (Virginia Tech) has developed a predictive model to estimate external hand forces during overhead tasks while wearing arm-support exoskeletons (ASEs). The researchers used EMG signals to map force time series, taking into account participant characteristics and task parameters. The study found that the predicted values for external hand forces using EMG signals were similar to the values obtained through direct measurement with load cells, suggesting the potential of using EMG signals to estimate these forces. This research provides valuable insights into the effectiveness of ASEs in reducing muscle activation during overhead work. [Extracted from the article]

Researchers at Virginia Polytechnic Institute and State University (Virginia Tech) have developed a vision-based human-machine interface (HMI) for a robotic exoskeleton glove designed to assist patients with brachial plexus injuries. The HMI incorporates computer vision techniques to identify and estimate the size and material of target objects, allowing for precise application of force. The study found that the vision-based method had a grasp success rate of 87.5%, surpassing the baseline slip-grasp method's rate of 71.9%. This research has been peer-reviewed and was supported by the Eunice Kennedy Shriver National Institute of Child Health & Human Development. [Extracted from the article]

A recent report from State University discusses the need for precise real-time feedback in rehabilitation programs and introduces a new automated therapy approach. The approach utilizes robotic technologies and exoskeletons with Assist-as-Needed (AAN) controllers to improve recovery rates for individuals with stroke and neuromuscular disorders. The system integrates sensors and algorithms for continuous monitoring and uses minimal data to create personalized models. Initial trials with an exoskeleton focusing on elbow movements showed promising results in adjusting support in real time and designing customized rehabilitation programs. For more information, readers can refer to the Journal of Engineering and Science in Medical Diagnostics and Therapy. [Extracted from the article]

A recent study conducted at San Jose State University explored the application of upper limb exoskeletons in pediatric rehabilitation. The researchers found that these devices have the potential to improve upper limb movement in children with neuromotor impairments. The study reviewed 10 articles that evaluated the effectiveness of upper limb exoskeletons in children's rehabilitation, focusing on task performance and subjective perspectives. The results showed that these devices were effective in facilitating coordination, precision, smoothness, and quality of movement. However, the study also identified limitations, such as the lack of control groups and the need to consider long-term efficacy and adaptability for individual physical differences. [Extracted from the article]

A study conducted by Texas Tech University investigated the impact of exoskeletons on the self-efficacy and perceived work ability of manual labor workers aged 55 or older. The study found that although the results were not statistically significant, there was a trend indicating that older workers anticipated increased self-efficacy if exoskeletons were introduced to their workplaces. This suggests that exoskeletons have the potential to not only reduce injury risks and improve productivity for older workers, but also enhance their confidence at work, potentially extending their time in the workforce and improving their overall quality of life. [Extracted from the article]

Researchers at Lanzhou Jiaotong University in Gansu, China have conducted a study on the trajectory tracking control of wearable upper limb rehabilitation robots. The study utilizes model predictive control to address the challenges faced by traditional control methods in tracking the trajectory of the robot. The researchers have developed a model predictive controller based on the Laguerre model, which ensures system performance while reducing computational complexity. Simulation results demonstrate that the controller can achieve simultaneous tracking of joint trajectory and velocity while meeting various constraints. The study provides new research ideas and methods for the field of rehabilitation therapy. [Extracted from the article]

Researchers from Manipal University in Rajasthan, India have developed a novel robotic exoskeleton device for the rehabilitation of the index finger. The device utilizes a Stephenson III six-bar mechanism and nature-inspired algorithms to address post-stroke rehabilitation. The researchers found that the device successfully covered the prescribed range of motion and concluded that it is a viable solution for post-stroke index-finger rehabilitation. This research has been peer-reviewed and published in Applied Intelligence. [Extracted from the article]

• A trajectory tracking control problem of upper limb rehabilitation robots in the presence of the model uncertainty and external disturbances is investigated. • A compound control method combining with adaptive neural network and nonsingular terminal sliding mode control is proposed to achieve practical predefined time stability. The convergence time of tracking errors only depends on two parameters, and it can be determined by the designer. • An estimation-and-compensation strategy is adopted for disturbance-rejection, and an adaptive RBFNN is utilized to approximate the lumped disturbance and then compensated in the controller. This approach can reduce the switching gain of the sliding mode controller significantly, thereby alleviate the chattering phenomenon dramatically. This article investigates the predefined time trajectory tracking control problem of upper limb rehabilitation robots in the presence of the model uncertainty and external disturbances. An adaptive neural network-based practical predefined-time fast nonsingular terminal sliding-mode control (PPT-FNTSMC) strategy is proposed, in which a novel sliding mode surface is constructed to achieve predefined-time convergence and avoid the singularity problem as well. Additionally, a neural network is employed to approximate the lumped disturbances, and the estimated values are utilized in the controller for compensation, thereby reducing the required switching gain and mitigating chattering phenomenon. A rigorous theoretical analysis is provided to illustrate that the tracking errors can converge to a vicinity of the origin in a predefined time. Finally, simulations on a two-joint single-arm robot and a 5-DOF upper-limb exoskeleton are conducted and compared with an existing control method to demonstrate the effectiveness and superiority of the proposed control strategy. [ABSTRACT FROM AUTHOR]

I climb into an upper-body exoskeleton that's covered in sensors, motors, gears, and bearings, and then lean forward, tilting my head up to press my face against the eyepieces of a vision system hanging from the ceiling. In front of me, I see a large wooden board, painted black and punctuated by a grid of metal holes. The board is real. So is the peg in my hand that I'm trying to move from one hole to another, as fast as I can. When I begin to move the peg, a virtual cone appears over the target hole, along with a virtual surface easing toward it. I can feel the surface as I slide the peg along it toward the cone and into the hole. [ABSTRACT FROM AUTHOR]

The article offers information on the Gaussian process (GP) models which are popular in several applications, such as in machine learning, computer experiments and spatial statistics. It discusses that to allow greater flexibility in solving this broad class of data integration problems, the authors develop deep Gaussian process models that can handle nonstationary relationships between the two data sources.

Copyright of VDT Magazin is the property of Fortes Medien GmbH and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The article looks at the design, development, and application of wearable mobile machines, or exoskeletons. It discusses how such technology can be used in private industrial settings, such as for factory works at Ford automakers, and for military purposes.

A recent study conducted at Holland Bloorview Kids Rehabilitation Hospital in Toronto, Canada, explored the feasibility of using physiotherapy-assisted overground exoskeletons to help children with severe mobility challenges walk. The study involved children aged 3-6 years with cerebral palsy or related disorders. The researchers aimed to assess the safety, acceptability, and clinical feasibility of the intervention, as well as its impact on motor/functional outcomes, brain structure, muscle activity, heart rate, and user experience. This study is the first of its kind to investigate the use of exoskeletons in a school and outpatient context for children with mobility impairments. [Extracted from the article]

A new study conducted by researchers at South China University of Technology explores the potential of exoskeletons as ergonomic interventions for injured workers with limited trunk mobility. The study involved six adult males who performed simulated bending tasks with and without the use of a passive trunk exoskeleton. The results showed significant reductions in compressive loads and subject moments at the lumbosacral joint when the exoskeleton was used, particularly during full bending. The findings suggest that exoskeletons have the potential to facilitate the return to work for individuals with limited trunk mobility, but further empirical validation in real-world settings is needed. [Extracted from the article]

A recent study conducted by researchers at Boeing Company in Seattle, Washington, examined the impact of a passive shoulder exoskeleton on a drilling-fastening task. The study aimed to determine how exoskeletons affect work performance and processes that require accuracy and precision. The results showed that the exoskeleton did not affect the quality of the drilling task, perceived fatigue, or perceived workload. However, there were mixed results regarding perceived discomfort, with participants experiencing varying levels of discomfort depending on the body location. This study provides valuable insights for industries considering the use of passive shoulder-support exoskeletons to mitigate work-related musculoskeletal disorders. [Extracted from the article]

A new report from the Rochester Institute of Technology discusses the use of Back Support Industrial Exoskeletons (BSIEs) to reduce the risk of low-back injury during repetitive trunk flexion tasks. The researchers conducted a study with 14 participants who performed trunk bending tasks with and without fatigue, while their muscle activity and whole-body stability were measured. Machine learning algorithms were used to predict perceived back fatigue based on sensor data. The study found that the XGBoost algorithm performed the best in predicting back fatigue, and the findings can be useful in developing fatigue detection products for industrial scenarios. [Extracted from the article]

The article details a study by Rice University researchers on the use of cervical transcutaneous spinal stimulation (TSS) with an upper limb robotic exoskeleton to assess motor function. Topics include the assessment of muscle response using surface electromyography, the evaluation of joint torque changes during TSS, and the integration of robotic assessment into hybrid neuromodulation-robotic systems.