For anyone who's spent the week crammed into subway cars or hustling up stairs to catch a train, the idea of a weekend hike can feel...aspirational. I grew up in cities like Seattle and Minneapolis, so swapping views of the city for mountains isn't foreign to me. But living in New York City now, just getting through the subway stations on the way to work feels like microdosing a sprint on the stair master. By the weekend, my joints are pleading for mercy despite craving trees, dirt, trail markers -- anything that doesn't smell like construction dust or hot trash. That's why when I first saw a clip of the Hypershell X at CES, I was intrigued. It looked like something out of a sci-fi -- sleek, robotic, and futuristic AF.

New prosthetic arms combine artificial intelligence, machine learning and advanced sensor systems. If you've ever wondered what's next for prosthetic technology, you're not alone. For many people living with limb loss, finding a prosthetic that feels natural and works seamlessly with their body has always been a challenge. Now, a California startup called Atom Bodies is making headlines for its groundbreaking approach to prosthetic technology. By combining artificial intelligence, machine learning and advanced sensor systems, Atom Bodies is developing mind-controlled robotic arms that could soon make highly advanced prosthetics accessible to thousands of amputees.

Not so long ago, generative AI could only communicate with human users via text. Now it's increasingly being given the power of speech -- and this ability is improving by the day. On Thursday, AI voice platform ElevenLabs introduced v3, described on the company's website as "the most expressive text-to-speech model ever." The new model can exhibit a wide range of emotions and subtle communicative quirks -- like sighs, laughter, and whispering -- making its speech more humanlike than the company's previous models. Also: Could WWDC be Apple's AI turning point?

Wandercraft's Personal Exoskeleton is about helping people stand tall, connect with others and live life on their own terms. For Caroline Laubach, being a Wandercraft test pilot is about more than just trying out new technology. It's about reclaiming a sense of freedom and connection that many wheelchair users miss. Laubach, a spinal stroke survivor and full-time wheelchair user, has played a key role in demonstrating the personal AI-powered prototype exoskeleton's development, and her experience highlights just how life-changing this device can be. "When I'm in the exoskeleton, I feel more free than I do in my daily life," said Laubach.

Every weekend warrior knows the drill -- you sit in front of a computer all week, and when the weekend hits, you bike, hike, and run yourself ragged. Your body feels destroyed on Monday. If this sounds like you -- or even if you're a casual exerciser who wants to walk and bike longer distances without getting tired -- the future has arrived. The world's first-ever outdoor exoskeleton, Hypershell X, can help max out your physical abilities with minimal effort. Hypershell X is causing a buzz among both outdoorsy types and robotics enthusiasts, and it won the Best of Innovation in Robotics award at CES 2025.

Thousands of people in Gaza require artificial limbs after being maimed in Israeli attacks. Technicians are making prosthetic arms and legs from recycled materials as medical supplies are blocked by Israel's siege.

Gait asymmetry is a significant clinical characteristic of hemiplegic gait that most stroke survivors suffer, leading to limited mobility and long-term negative impacts on their quality of life. Although a variety of exoskeleton controls have been developed for robot-assisted gait rehabilitation, little attention has been paid to correcting the gait asymmetry of stroke patients following the assist-as-need (AAN) principle, and it is still challenging to properly share control between the exoskeleton and stroke patients with partial motor control. In view of this, this article proposes an AAN hip exoskeleton control with human-in-the-loop optimization to correct gait asymmetry in stroke patients. To realize the AAN concept, an objective function was designed for real-time evaluation of the subject's gait performance and active participation, which considers the variability of natural human movement and guides the online tuning of control parameters on a subject-specific basis. In this way, patients were stimulated to contribute as much as possible to movement, thus maximizing the efficiency and outcomes of post-stroke gait rehabilitation. Finally, an experimental study was conducted to verify the feasibility and effectiveness of the proposed AAN control on healthy subjects with artificial gait impairment. For the first time, the common hypothesis that AAN controls can improve human active participation was validated from the biomechanics viewpoint.

Hand exoskeletons have significant potential in labor-intensive fields by mitigating hand grip fatigue, enhancing hand strength, and preventing injuries.However, most traditional hand exoskeletons are driven by motors whose output force is limited under constrained installation conditions. In addition, they also come with the disadvantages of high power consumption, complex and bulky assistive systems, and high instability.In this work, we develop a novel hand exoskeleton integrated with magnetorheological (MR) clutches that offers a high force-to-power ratio to improve grip endurance. The clutch features an enhanced structure design, a micro roller enhancing structure, which can significantly boost output forces. The experimental data demonstrate that the clutch can deliver a peak holding force of 380 N with a consumption of 1.48 W, yielding a force-to-power ratio of 256.75N/W, which is 2.35 times higher than the best reported actuator used for hand exoskeletons. The designed MR hand exoskeleton is highly integrated and comprises an exoskeleton frame, MR clutches, a control unit, and a battery. Evaluations through static grip endurance tests and dynamic carrying and lifting tests confirm that the MR hand exoskeleton can effectively reduce muscle fatigue, extend grip endurance, and minimize injuries. These findings highlight its strong potential for practical applications in repetitive tasks such as carrying and lifting in industrial settings.

Details of the Model Architecture The detailed encoder architecture is depicted in Figure 7. Some implementation details that we use in the decoder, and the decoder architecture are depicted in Figure 8. We design the grouped 1x1 convolutions to be able to mix channels. For each group, the same number of channels are extracted from one half of the feature map separated by coupling layers and the other half, respectively. Figure 8c shows an example.