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Scientists Discover Way to Send Information into Black Holes Without Using Energy

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This AI-Powered Soft Robotic Glove Helps People With Paralysed Hands Move Again

Imagine losing the ability to move your hand for years. Even simple tasks like holding a spoon, buttoning a shirt, or picking up a cup become impossible without help. For millions of people living with paralysis, stroke, or diseases such as ALS, this is a daily reality.

Now, researchers have developed an exciting new technology that could change lives. A team from the Technical University of Munich and the Center for Rehabilitation Passauer Wolf has created a lightweight, soft robotic glove that helps people with severe hand paralysis move their fingers and grasp objects again.

Unlike traditional robotic devices, this innovative exoskeleton uses soft fabric, artificial intelligence (AI), and muscle-sensing technology to understand what the user wants to do. The findings, published in Nature Machine Intelligence, show that the device could restore independence to people who have lost almost all hand function.

Why Hand Movement Matters

Our hands are involved in nearly everything we do. Eating, writing, cooking, dressing, using a phone, and shaking someone's hand all depend on fine hand movements.

Unfortunately, millions of people worldwide struggle with hand movement because of neurological conditions. Some suffer from amyotrophic lateral sclerosis (ALS), a progressive disease that gradually destroys the nerve cells controlling muscles. Others lose hand function after a stroke or injuries to the brain, spinal cord, or nerves.

While rehabilitation therapies can help some patients, many people with severe paralysis never fully regain movement.

This inspired researchers to search for a better solution.

A New Kind of Robotic Exoskeleton

The research team developed a soft robotic hand exoskeleton that works like a wearable glove.

Unlike bulky metal robotic devices, the glove is made from lightweight fabric and can even be stitched together using a standard sewing machine. Instead of using heavy motors, it is powered by air pressure, making it comfortable, flexible, and safe to wear.

Because the glove is soft, it naturally fits the shape of the hand, making movements feel more comfortable and reducing the risk of injury.

The biggest breakthrough, however, is not just the glove itself—it's the intelligent system that controls it.

AI That Understands Your Intentions

Many people with severe paralysis cannot visibly move their fingers, but their muscles still produce tiny electrical signals when they try.

The researchers placed sensors on the user's hand to detect these weak muscle signals.

These signals are then analyzed by an AI-powered machine learning system that predicts the person's intention. If the user is trying to grasp an object, the AI recognizes this intention and instructs the robotic glove to perform the movement.

Instead of forcing movements automatically, the glove responds to what the user is trying to do.

This creates a more natural interaction between the human body and the robotic device.

A Patient Regained the Ability to Feed Himself

One of the most remarkable demonstrations involved a patient living with ALS.

The man had almost completely lost the ability to move his right hand and had been unable to use it for about four years.

Using the AI-powered glove, he was able to intentionally pick up a fork and feed himself a piece of cake.

This may sound like a simple task, but for someone who has lived with paralysis for years, it represents a huge step toward independence and dignity.

Lead researcher Gordon Cheng explained that restoring hand function is one of the most important goals in rehabilitation because our hands are essential for nearly every aspect of daily life.

Testing the Robotic Glove

The researchers evaluated the exoskeleton with one ALS patient and six stroke survivors who had lost movement in one hand.

Participants completed two well-known clinical assessments:

  • Box and Block Test, which measures how well someone can pick up and move small blocks.

  • Action Research Arm Test (ARAT), which evaluates a person's ability to perform everyday arm and hand movements.

The results showed something interesting.

People with the most severe hand impairments experienced the greatest improvements while wearing the glove.

Those who still had some hand movement did not always perform better because they already retained partial control of their hands.

This suggests the technology could be especially valuable for individuals who currently have very few treatment options.

Patients Helped Design the Technology

One of the most valuable parts of the project was the close collaboration between researchers and patients.

Instead of simply testing the finished device, the ALS patient actively helped improve both the glove and its control system.

Researchers discovered that he did not want the glove to move automatically.

Instead, he wanted the device to wait until he intentionally tried to move his hand.

This feedback became an important part of developing the AI intention prediction system.

By allowing users to remain in control, the exoskeleton feels more natural and respects the person's own decisions.

This patient-centered approach could become an important model for designing future rehabilitation technologies.

Why Soft Robotics Are the Future

Traditional robotic exoskeletons often use rigid metal structures that can feel heavy, uncomfortable, and difficult to wear for long periods.

Soft robotics offers several advantages:

  • Lightweight and comfortable design

  • Better flexibility during movement

  • Safer interaction with the human body

  • Easier to wear for extended periods

  • Lower manufacturing costs using fabric materials

Because the glove behaves more like clothing than a machine, patients may be more willing to use it regularly during rehabilitation or daily activities.

More Than Just Rehabilitation

The potential applications of this technology go far beyond hospitals.

In the future, similar AI-powered gloves could help people perform everyday activities independently at home, including:

  • Eating meals

  • Holding utensils

  • Grasping household objects

  • Opening doors

  • Using electronic devices

  • Completing personal care tasks

Regaining the ability to perform even a few of these activities without assistance can greatly improve confidence, independence, and overall quality of life.

The Next Step: Helping People Walk Again

The researchers are already looking ahead.

Their next goal is to develop a soft lower-body exoskeleton that could help people with walking difficulties caused by neurological disorders or injuries.

Lead researcher Gordon Cheng hopes these technologies will eventually benefit as many people as possible before the end of his career.

As artificial intelligence, wearable robotics, and medical engineering continue to advance together, devices like these could become increasingly common in rehabilitation centers and even in patients' homes.

A New Era of Assistive Technology

This soft robotic glove represents much more than an engineering achievement. It demonstrates how artificial intelligence and wearable robotics can restore abilities that many people believed were permanently lost.

By detecting tiny muscle signals and understanding a person's intention to move, the glove gives users control over their own hands again—even after years of paralysis.

While more clinical testing is still needed before the technology becomes widely available, the early results are extremely encouraging.

For millions of people living with severe hand paralysis due to ALS, stroke, or neurological injuries, this AI-powered soft exoskeleton offers something incredibly valuable: the possibility of greater independence, improved quality of life, and renewed hope for the future.

Reference: Nassour, J., Berberich, N., Utpadel-Fischler, D. et al. A dexterous soft hand exoskeleton restores intentional grasping in individuals with severe hand impairment. Nat Mach Intell (2026). https://doi.org/10.1038/s42256-026-01263-3

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