AI Can Detect Parkinson’s Disease Even When Patient is Asleep


The researchers from MIT have developed an Artificial Intelligence (AI) model that can detect Parkinson’s disease from the breathing patterns of the patients. This phenomenal breakthrough comprising of an AI module that can easily detect Parkinson’s disease by monitoring the breathing patterns of the patient.

The AI system with access to a Wi-Fi router uses a neural network to recognize the presence and severity of one of the fastest-growing neurological diseases in the world.

Currently the fastest-growing neurological illness globally, Parkinson’s also happens to be the second-most common neurological ailment. Their study was influenced by 200-year-old observations from James Parkinson, the first doctor to clinically classified the signs of degenerative neurological disease.

The progression of Parkinson’s disease which causes tremors and many other serious movement challenges can be detected and tracked by the AI module by analysing the changes in nighttime breathing patterns.

When the AI module was tested on an independent dataset, it seamlessly diagnosed Parkinson’s patients with an impressive 86% accuracy through just one night’s research. It accurately flagged Parkinson’s using one night’s breathing data compiled from the belt patient wore in his abdomen.

Read More News: Click Here