Computer science and technology

A new tool for diagnosing Parkinson’s disease developed by MIT researchers uses an AI system to monitor a person’s breathing patterns during sleep, reports Hiawatha Bray for The Boston Globe. “The system is capable of detecting the chest movements of a sleeping person, even if they’re under a blanket or lying on their side,” writes Bray. “It uses software to filter out all other extraneous information, until only the breathing data remains. Using it for just one night provides enough data for a diagnosis.”

Boston Globe reporter Hiawatha Bray speaks with Radio Boston host Tiziana Dearing about how MIT researchers developed an artificial intelligence model that uses a person’s breathing patterns to detect Parkinson’s Disease. The researchers “hope to continue doing this for other diseases like Alzheimer’s and potentially other neurological diseases,” says Bray.

Researchers at MIT have developed an artificial intelligence sensor that can track the progression of Parkinson’s disease in patients based on their breathing while they sleep, reports Conor Hale for Fierce Biotech. “The device emits radio waves and captures their reflection to read small changes in its immediate environment,” writes Hale. “It works like a radar, but in this case, the device senses the rise and fall of a person’s chest.”

MIT researchers have developed a new artificial intelligence system that uses a person’s breathing pattern to help detect Parkinson’s sisease, reports Susannah Sudborough for Boston.com. “The device emits radio signals, analyzes reflections off the surrounding environment, and monitors the person’s breathing patterns without any bodily contact,” writes Sudborough.

Researchers at MIT and other institutions have developed an artificial intelligence tool that can analyze changes in nighttime breathing to detect and track the progression of Parkinson’s disease, reports Casey Ross for STAT. “The AI was able to accurately flag Parkinson’s using one night of breathing data collected from a belt worn around the abdomen or from a passive monitoring system that tracks breathing using a low-power radio signal,” writes Ross.

Computer science lecturer Iddo Drori and his team have developed an artificial intelligence algorithm that can solve college-level math problems at a human level, reports Susan D’Agostino for Inside Higher Ed. “The model can also explain the solutions and generate new problems that students found indistinguishable from human-generated problems,” reports D’Agostino.

Fast Company reporter Elissaveta Brandon writes that a team of scientists from MIT and elsewhere have developed an amphibious artificial vision system inspired by the fiddler crab’s compound eye, which has an almost 360-degree field of view and can see on both land and water. “When translated into a machine,” writes Brandon, “this could mean more versatile cameras for self-driving cars and drones, both of which can become untrustworthy in the rain.”

Mark Lee MS ’94 spoke with Forbes reporter Karen Walker about the success of Splashtop, a company he co-founded that is developing cloud-based software that allows secure and remote access and support.

The MIT mini cheetah broke a speed record after learning to adapt to difficult terrain and upping its speed, reports Rienk De Beer for Popular Mechanics.

Postdoctoral researcher Murat Onen  and his colleagues have created “a nanoscale resistor that transmits protons from one terminal to another,” reports Alex Wilkins for New Scientist. “The resistor uses powerful electric fields to transport protons at very high speeds without damaging or breaking the resistor itself, a problem previous solid-state proton resistors had suffered from,” explains Wilkins.

Researchers from CSAIL and elsewhere have found that Irish judges are using Wikipedia articles as a source in their rulings, reports Shane Phelan for Independent. “This work shows that Wikipedia reaches even farther than that, into high-stakes, formalized processes like legal judgments,” says research scientist Neil Thompson. “The worst outcome would be for a judge’s reliance on Wikipedia to lead them to decide a case differently than they would have if they had read either an expert secondary source or the cited precedent itself.”

Researchers from CSAIL, Cornell University, and Maynooth University have released a study concluding that judges in Ireland are utilizing Wikipedia articles to help inform their decisions, reports Colleen Hagerty for Popular Science. Based on their findings, the researchers suggest “the legal community increases its efforts to monitor and fact-check legal information posted on Wikipedia.” 

MIT researchers have developed a new system that enabled the mini robotic cheetah to learn to run, reports John Koetsier for Forbes. ““Traditionally, the process that people have been using [to train robots] requires you to study the actual system and manually design models,” explains Prof. Pulkit Agrawal. “This process is good, it’s well established, but it’s not very scalable. “But we are removing the human from designing the specific behaviors.”

Wall Street Journal reporter Daniela Hernandez spotlights the work of Media Lab Research Scientist Andreas Mershin in developing sensors that can detect and analyze odors. Mershin “is focusing on medical applications of olfaction technology. Inspired by dogs that have demonstrated an ability to sniff out malignancies in humans, he’s working on an artificial-intelligence odor-detection system to detect prostate cancer.”

Researchers at MIT have created a knit textile containing pressure sensors called 3DKnITS which can be used to predict a person’s movements, reports Charlotte Hu for Popular Science. “Smart textiles that can sense how users are moving could be useful in healthcare, for example, for monitoring gait or movement after an injury,” writes Hu.