Articles tagged with Robotic Exoskeletons
A University of Michigan research team is exploring the development of knee exoskeletons to reduce joint contact forces and relieve osteoarthritis pain. Preliminary testing suggests that these orthotic brace-based exos and drone-style motors could provide significant relief.
A robotic hand developed at USC can hear a melody once and play it back after just two minutes of self-taught practice on a keyboard. The system, called the Musician Hand, mimics the way the brain and body coordinate fine motor skills through trial and error, offering a new model for machines — and medicine — to approach complex moveme...
Researchers at NC State University developed a morpho-interlocking protective module (MIPM) that responds to external threats and curls into a protective ball. The structure, inspired by armadillos' natural defense mechanisms, consists of multiple layers and can be tuned to respond to various levels of strain.
Researchers at USC, Caltech, and UC Irvine have developed a two-way brain interface that allows patients to control wearable robotic legs using their thoughts. The system accurately detected brain signals indicating the intent to walk about 92% of the time and restored walking sensations with about 93% accuracy in an early proof-of-con...
Utah engineers have created a wearable, portable hip exoskeleton that reduces the energy needed to walk by nearly 20% in individuals with hemiparesis after a stroke. The device helps compensate for reduced ankle propulsion and provides real-time motor assistance, improving mobility and quality of life.
Robotic exoskeletons enhance cancer patients' mobility, muscle strength, and gait training while providing personalized support and real-time feedback. This innovation integrates traditional therapies, nutritional support, and cognitive behavioral therapy to improve therapeutic outcomes.
A University of Delaware study uses robotic testing to gauge perception-based movement in stroke survivors, revealing hidden sensory losses. The researchers hope their findings will encourage clinicians to integrate precision testing into assessments, leading to a personalized medicine approach to treatment.
The robotic exoskeleton TWIN has been awarded the Compasso d’Oro International Award for its innovative design and ability to adapt to different user needs. Developed by Rehab Technologies IIT – INAIL and ddpstudio, TWIN provides energy assistance to individuals with limited mobility, enabling them to stand, walk, and sit down.
A wearable robot has been upgraded to provide personalized assistance to ALS and stroke patients. The device uses machine learning and a physics-based model to adapt to an individual user's movements, offering more nuanced help with daily tasks.
The AI for Good Global Summit 2025 will showcase AI innovations delivering better healthcare and education, reducing disaster risks, ensuring water and food security, and bolstering economic resilience. The event, organized by the International Telecommunication Union (ITU), features talks from AI leaders and 100+ demos.
A consortium of researchers and hospitals in Madrid has created a children's exoskeleton for domestic use, enabling children with gait impairments to walk at home or outdoors. The prototype features four motors that mimic natural muscle function and adapts to the child's growth.
Researchers from King's College London have created a new kind of compact circuit that enables robots to receive complex instructions without electricity. This breakthrough could enable the creation of robots with more complex AI-powered software and improve their social awareness and dexterity.
A new knee exoskeleton has been developed to support the quadriceps muscles during lifting tasks, helping workers maintain better posture even when fatigued. The device, which uses a complex algorithm to predict assistance needs, enabled participants to lift faster and with improved posture.
The Human AugmentatioN via Dexterity (HAND) center aims to develop robots capable of enhancing human labor through engineered systems of dexterous robotic hands, AI-powered fine motor skills, and human interface. The center's goal is to make robotic assistance accessible and applicable to a wide range of physical actions.
Researchers at North Carolina State University have developed a lightweight fluidic engine that can power muscle-mimicking soft robots for use in assistive devices. The new engine generates significant force and is untethered to an external power source, making it particularly attractive for improving people's ability to move their upp...
Researchers at North Carolina State University have developed an AI-powered method to train robotic exoskeletons to autonomously assist users in various movements, reducing energy consumption by up to 24.3% for able-bodied individuals and 15.4% for those with mobility impairments.
An interdisciplinary team of scientists and engineers compared various aspects of running robots with their equivalents in animals, finding that biological components performed poorly compared to fabricated parts. However, animals excel in integrating and controlling these components.
Researchers at Georgia Tech have developed a universal approach to controlling robotic exoskeletons that requires no training, calibration, or adjustments. The system uses deep learning to autonomously adjust assistance levels for walking, standing, and climbing stairs, reducing user effort and metabolic expenditure.
Researchers have developed a wearable patch that can detect and respond to human muscle signals, allowing people to control robotic exoskeletons more efficiently. The patch, called SNAP, uses microneedles to pick up tiny signals from muscles and sends them to outside equipment for processing.
A new technology enables the printing of complex robots with soft, elastic, and rigid materials in one go. This allows for the creation of delicate structures and parts with cavities as desired.
A team of New Jersey researchers reviewed the evidence on robotic exoskeleton devices for individuals with acquired brain injury, laying out a systematic framework for future research. The review highlights the need for comprehensive approaches to evaluate these devices and their role in improving mobility in individuals with acquired ...
Researchers developed a new method for controlling lower limb exoskeletons using deep reinforcement learning, enabling more robust and natural walking control. The system has the potential to benefit users with spinal cord injuries, multiple sclerosis, stroke, and other neurological conditions.
Robotic exoskeletons have been shown to provide intensive high-quality rehabilitation and potentially improve functional outcomes in individuals with MS. However, experts agree that wide acceptance depends on further clinical studies aimed at determining optimal selection criteria and long-term outcomes.
Researchers found that an elephant's folded skin plays a crucial role in its flexible and strong trunk, enabling it to grasp fragile vegetation and rip apart tree trunks. The study suggests that wrapping soft robotics with a skin-like structure could give machines protection and strength while maintaining flexibility.
Researchers developed a lightweight exoskeleton that uses machine learning to predict user intentions and provide assistance. The system successfully helped participants stand up, demonstrating potential for supporting individuals with mobility impairments.
Researchers developed a bioinspired system using ultrasound measurements to create customized assistance profiles for users. The exosuit significantly reduced metabolic energy of walking across various speeds and inclines.
A new algorithm provides accurate solutions that mimic natural human movement, reducing the risk of injury. The Pro-ISADE approach improves calculation speed while ensuring calculated joint angles are feasible for robotic use in daily activities like drinking water and brushing teeth.
Researchers found that high-dose gait training using a robotic exoskeleton can restore functional ambulation in individuals with moderate to severe hemiplegia caused by stroke. The study showed improvements in walking distance, speed, balance, and endurance, with no complications or falls reported.
Zach Lerner, a mechanical engineer at Northern Arizona University, has received an NSF CAREER award to develop wearable robotic exoskeletons for long-term gait rehabilitation. The project aims to understand the interplay between disease severity and wearable assistance, with potential to transform treatment of walking disabilities.
Researchers are developing AI-controlled exoskeletons and prosthetic legs that can think and make control decisions on their own. The system combines computer vision and deep-learning AI to mimic human walking by adjusting to surroundings.
Researchers found that high-dose gait training with robotic exoskeletons during acute inpatient rehabilitation can improve motor function and functional independence in stroke patients. The study demonstrated the potential of overground walking in an exoskeleton to increase therapy dose without extending rehabilitation duration.
Researchers have found that gait training using robotic exoskeletons significantly improved motor function in adolescents and young adults with acquired brain injury, including increased loading, longer step length, and faster walking speed. However, further studies are needed to confirm the training effect and optimal dosing protocol.
A soft robotic exosuit can assist both walking and running by detecting the wearer's gait and providing appropriate assistance, reducing metabolic costs of walking and running by 9.3% and 4.0%, respectively. The device weighs only 11 pounds and enables a near-seamless transition between gaits.
A joint team from Kessler Foundation and NJIT is developing new applications for wearable robotic exoskeleton devices to improve mobility and enable safer, more independent functioning for people with spinal cord injuries, Duchenne Muscular Dystrophy, and stroke. Researchers are also evaluating the efficacy of existing robots for resto...
A new study improves brain-machine interface control by adding a robotic arm providing kinesthetic information, enhancing the design of 'wearable robots' for paralyzed patients. This approach may help spinal cord injury patients operate computers and robots using only their thoughts.