Forbes contributor Jennifer Kite-Powell spotlights how MIT researchers created a new AI system that analyzes radio waves bouncing off a person while they sleep to monitor breathing patterns and help identify Parkinson’s disease. “The device can also measure how bad the disease has become and could be used to track Parkinson's progression over time,” writes Kite-Powell.
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.
Loh Down on Science host Sandra Tsing Loh spotlights Prof. Cathy Wu and graduate student Vindula Jayawardana and their work developing a new method for self-driving vehicles that would help minimize idling at red lights. “In their method, self-driving can be taught to minimize stops at red lights. To make this work, traffic lights and self-driving cars would have sensors. This would let them check in with each other on their surroundings,” says Loh.
Alumni Carter Huffman ’14 and Mike Pappas ’14 co-founded Modulate, an artificial intelligence technology that helps differentiate between friendly banter and inappropriate outbursts in video game voice chats, reports Scott Kirsner for The Boston Globe. “Modulate highlights for a game’s human moderators the most severe violations of the game’s guidelines and allows them to decide on the consequences after they examine the situation,” writes Kirsner. “They may send the player a warning, mute them temporarily, or ban them from the game.”
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.
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.
A new study from researchers at MIT and Dartmouth suggests that the speed of automation should be halved, reports Adi Gaskell for Forbes. Their paper showed that “while investments in automation usually result in higher productivity in firms, and therefore often more employment, it can be harmful to those who are displaced, especially if they have few alternative options,” writes Gaskell.
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.
Butlr, spinout founded by researchers from the MIT Media Lab, is developing sensors that utilize body heat to estimate office occupancy, reports Kyle Wiggers for TechCrunch. The new technology “uses thermal sensing AI to provide data on space occupancy and historical activity,” writes Wiggers.
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.”