Artificial Intelligence (AI) Helps Stroke Patients To Walk Again

Navin Bondade 4 Comments Artificial Intelligence, Data Science, Deep Learning, Machine Learning

Spinal cord injury is an extremely serious type of physical trauma. A person’s sensory, motor and reflex messages are heavily getting damage and it often causes permanent changes in strength, sensation and other functions of the body.

Research studies are ongoing around the world, but the complete repair of spinal cord injuries is not possible yet. The major reason behind this is the slow repair rate of damage nerve cells and these cells also stop repairing very soon.

Now a robotic harness combined with artificial intelligence (AI) software has its a solution. No, it will not repair the damage, but it could help spinal injury and stroke patients walk again.

The research comes from the Center for Neuroprosthetics and Brain Mind Institute, School of Life Sciences, Swiss Federal Institute of Technology Lausanne (EPFL), Lausanne, Switzerland.

In this new study, researchers sought to develop an AI system that better mimicked the conditions that people might experience during everyday life, where they would have to move in more than one direction and vary their gaits.

“The idea is to provide the most appropriate environment for patients to be active during training,” says study co-author Grégoire Courtine, a neuroscientist at the Swiss Federal Institute of Technology Lausanne. “The goal of this rehabilitation is to have patients repeat natural activities for an extended amount of time.”

Recovery plans for spinal cord injuries and strokes typically require usually many hours of supported walking, using devices like treadmills, with the walking aid pre-programmed by a medic to provide a steady pace. This one-size-fits-all approach does not account for each patient moving around in different directions and having different gaits, both varying according to the individual.

What this new technology improves on is the use of AI and robotics to help simulate the forces people will encounter in various real-world situations.

Dr. Jean-Baptiste Mignardot used digital technology to developed a robotic harness that controls the amount of upward and forward force that patients feel while also permitting them to walk forward, backward, and side to side.

The robotic harness is controlled by the AI system that personalized the multi-directional forces that each patient experienced depending on their specific problems.

To customize patient experiences, this system relied on an artificial neural network, where components known as artificial neurons are supplied data and work together to solve a problem.

This neural net can then alter the pattern of links among those neurons to change the way they interact, and the network tries solving the problem again. Over time, the neural net learns which patterns are best at computing solutions, an AI strategy that imitates the human brain.

The machine is able to assess 120 different variables relating to body movement, such as how fast they could walk, and then computed what kind of support they should need.

“The amount of support that patients receive is calculated precisely for each patient,” Courtine says. “If patients need only as much gravity as they would experience walking on the moon, the harness creates a moon-like feeling of gravity, and if the patients are stronger, it creates, says, a Mars-like feeling of gravity.”

As part of a clinical trial of this “neurorobotic platform,” the researchers experimented with 26 volunteers recovering from spinal cord injuries or strokes, whose disability ranged from being able to walk without assistance to be able to neither stand nor walk independently.

The participants were tested on four tasks—standing on two separate plates, walking on a straight path, walking on a wavy path, or walking on a ladder with irregularly positioned rungs. Each patient who took part in the first trial was able to walk with motor abilities comparable to healthy individuals.

After the volunteers walked roughly 20 meters using the neurorobotic platform to familiarize themselves with the apparatus, three patients with spinal cord injuries who previously could not stand independently could, immediately after such practice, walk with or without assistance.

Four of 10 patients with spinal cord injuries who previously could only move with crutches or a walker could, immediately after such practice, do so without assistance. Similar or even superior findings were seen with stroke patients, the researchers say.

Furthermore, after a one-hour training session with the neurorobotic platform, four out of five patients with chronic spinal cord injuries who previously could only walk with the assistance of a device experienced significant improvements, such as the increase in speed, the researchers say.

In contrast, the same amount of time on just a treadmill actually impaired the ability to walk without robotic assistance in one patient.

“It’s striking how a system that applies force in directions other than just vertical can make a world of difference,” Courtine says.

The scientists are also exploring how spinal cord stimulation can improve patient mobility. They are combining that approach with their neurorobotic platform, Courtine says.

The new development has been described in the journal Science Translational Medicine, with the research paper headed “A multidirectional gravity-assist algorithm that enhances locomotor control in patients with stroke or spinal cord injury.”

Going forward, the plan is for the technology to be commercialized for use in rehabilitation centers as part of the clinical routine.

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