Fighting hand tremors with AI and robots

Researchers from NYU Tandon and Canada develop a machine learning model that allows robots to safely treat symptoms of Parkinson's disease and other neurological movement disorders.

Photo
Researchers have tapped AI techniques to build an algorithmic model that will make the robots more accurate, faster, and safer when battling hand tremors.

Robots hold promise for a large number of people with neurological movement disorders severely affecting the quality of their lives. Now researchers have tapped artificial intelligence techniques to build an algorithmic model that will make the robots more accurate, faster, and safer when battling hand tremors.

The international team reports the most robust techniques to date to characterize pathological hand tremors symptomatic of the common and debilitating motor problems affecting a large number of aging adults. One million people throughout the world have been diagnosed with Parkinson's disease, just one of the neurodegenerative diseases that can cause hand tremors.

While technology such as sophisticated wearable exoskeleton suits and neurorehabilitative robots could help people offset some involuntary movements, these robotic assistants need to precisely predict involuntary movements in real-time - a lag of merely 10 or 20 milliseconds can thwart effective compensation by the machine and in some cases may even jeopardize safety.

Enter the big dataset collected at the London (Ontario) Movement Disorders Centre and the team's pioneering machine learning model, which they named PHTNet, for "Pathological Hand Tremors using Recurrent Neural Networks". Using small sensors, they analyzed the hand motions of 81 patients in their 60s and 70s, then applied a novel data-driven deep neural network modeling technique to extract predictive information applicable to all patients. "Our model is already at the ready-to-use stage, available to neurologists, researchers, and assistive technology developers," said co-author S. Farokh Atashzar, who is now an NYU Tandon assistant professor and who began exploring the use of robots coupled with artificial intelligence while conducting doctoral and post-doctoral research in Canada. "It requires substantial computational power, so we plan to develop a low-power, cloud-computing approach that will allow wearable robots and exoskeletons to operate in patients' homes. We also hope to develop models that require less computational power and add other biological factors to the inputs."

Subscribe to our newsletter

Related articles

Neural network helps doctors explain relapses of heart failure

Neural network helps doctors explain relapses of heart failure

Researchers have developed an algorithm that not only predicts hospital readmissions of heart failure patients, but also tells you why these occur.

Neural networks helps grow artificial organs

Neural networks helps grow artificial organs

Researchers have developed a neural network capable of recognizing retinal tissues during the process of their differentiation in a dish.

AI challenge aims to improve mammography accuracy

AI challenge aims to improve mammography accuracy

AI techniques, used in combination with the evaluation of expert radiologists, improve the accuracy in detecting cancer using mammograms.

Neural networks support endovascular stroke therapy

Neural networks support endovascular stroke therapy

Researchers have been investigating whether artificial intelligence might be used to steer a catheter automatically and reliably to a blocked blood vessel.

Making new materials using AI

Making new materials using AI

Researchers have revelead the mechanism behind making materials used in new memory devices by using artificial intelligence.

AI-enabled rapid diagnostic test for COVID-19

AI-enabled rapid diagnostic test for COVID-19

Scientists have developed an extremely rapid diagnostic test that detects and identifies viruses in less than five minutes.

Neural networks could help predict future self-harm

Neural networks could help predict future self-harm

Researchers have created artificial intelligence algorithm that can automatically identify patients at high risk of intentional self-harm, based on the information in the clinical notes in the electronic health record.

Algorithm could unleash the power of quantum computers

Algorithm could unleash the power of quantum computers

A new algorithm that fast forwards simulations could bring greater use ability to current and near-term quantum computers.

5 ways AI is used against COVID-19

5 ways AI is used against COVID-19

Find out more about how scientists and physician are using AI to make contributions in the fight against the coronavirus.

Popular articles