New AI Device Detects Parkinson’s Via Breathing Pattern

Among the numerous diseases plaguing the globe, Parkinson’s disease has been a major blow to human health. Parkinson’s disease is difficult to detect since it depends mostly on the emergence of symptoms such as stiffness, tremors, and slowness. 

However, some professionals in the MT’S Department of EECS (Electrical Engineering and Computer Science) have developed an AI tool that can quickly detect the disease using an individual’s breathing pattern.

The AI tool is a neural network consisting of intertwined algorithms which simulate the working mechanisms of the human brain. It can ascertain an individual’s breathing patterns while sleeping.

New AI Tool Can Diagnose And Monitor The Parkinson’s Disease 

Yuan Yuan, a postdoc, and Yuzhe Yang, an MIT PhD student, developed the neural network. The network can determine how severe an individual’s Parkinson’s disease is and monitor the condition over time.

Researchers have looked into the possibility of diagnosing Parkinson’s using neuroimaging and cerebrospinal fluid. Unfortunately, both techniques are expensive and need access to specialist medical facilities.

This renders them unfit for routine testing that might permit quick diagnosis or assessment of the condition. However, these MIT researchers revealed that a Parkinson’s evaluation using AI is possible.

Moreover, one can carry out the diagnosis while the individual is asleep without touching them. To do this, these researchers developed a device resembling a house’s Wi-Fi router.

Instead of the device providing internet service, it releases radio signals and evaluates how its reflection in the surroundings. Afterwards, without physical touch, it collects the individual’s breathing patterns.

Benefits Of The AI Tool

In 1817, James Parkinson’s research revealed a relationship between breathing and Parkinson’s. One of the MIT researchers, Kabi, said this motivated them to consider using this to detect the disease. 

Parkinson’s disease, the second most prevalent neurological ailment after Alzheimer’s disease, is the neurological condition with the greatest growth rate globally. It affects over 1 million persons in America alone, putting a yearly strain of over $51.9 billion on its economy.

Katabi notes that the study is relevant for medication research and clinical treatment for Parkinson’s disease. In developing drugs, the findings would permit clinical trials that take less time and fewer patients, hence quickening the development of new treatments.

Also, this tool can help patients in disadvantaged communities. Those who stay in the rural regions and can’t learn their homes will benefit from the latest innovation.