DEEP TECH HEALTH + NEUROTECH
MeMed BV is a blood test which uses the body’s immune response to distinguish between bacterial and viral infections. It does not detect the cause of an infection — instead it analyzes the “host response,” measuring levels of three proteins that appear differently, depending on whether the immune system is fighting a virus or bacteria. […]
Yi Lu and Benito Marinas at the University of Illinois and University of Texas have developed a sensor that detects both the presence of a virus and whether or not it is infectious, integrating purpose designed DNA fragments and nanopore sensing. They have already studied its potential with the adenovirus and COVID 19. Current PCR […]
The Apple/UCLA project “Seabreeze” and Apple/Biogen project “Pi” represent a further move into iPhone health monitoring. According to the Wall Street Journal, Apple is attempting to develop an algorithm to identify depression and cognitive decline from sleep patterns, mobility, and how one uses the phone — for example, how often they look at its clock. […]
ApplySci’s 14th Wearable Tech + Digital Health + Neurotech conference returns to MIT on September 30, 2022. ApplySci’s 14th Deep Tech Health + Neurotech conference returns to MIT on September 30, 2022, focused on healthy longevity – understanding, detecting, treating and preventing disease through technology. Topics include: Slowing and reversing aging The new preventive care paradigm Next generation […]
UCSD’s Joe Wang has developed a totally noninvasive sensor and algorithm to detect glucose levels from sweat on the fingertip. The painless, rapid, and accurate system could revolutionize diabetes management. The systemcombines a simple touch-based fingertip sweat electrochemical sensor with a new algorithm that addresses for personal variations toward the accurate estimate of blood glucose […]
Arto Nurmikko and Brown colleagues have developed BCI system which employs a coordinated network of independent, wireless microscale neural sensors, to record and stimulate brain activity. “Neurograins” independently record electrical pulses made by firing neurons and send the signals wirelessly to a central hub, which coordinates and processes the signals. In a recent Nature paper, […]
UCSD’s Joe Wang continues to define the future of vital sign monitoring with a combination of advanced chemistry and unobtrusive wearables. Together with Professor Sheng Xu, he has developed a skin patch that continuously tracks blood pressure and heart rate while measuring glucose levels, lactate, and alcohol or caffeine. It is the first wearable device […]
DeepCOVID-XR is a Northwestern University developed algorithm that automatically detects the signs of COVID-19 on a basic X-ray of the lungs. The system is able to detect COVID-19 in X-rays 10 times faster than thoracic radiologists and 1% to 6% more accurately. The developers said the AI could be used to rapidly screen patients at […]
The US Army and USC Prof Maryam Shanechi have developed an algorithm that can determine which specific behaviors—like walking and breathing—belong to specific brain signals. Segmenting brain signals has been notoriously difficult, as all signals associated with tasks mix together. Shanechi and her team used the algorithm to separate behaviorally relevant brain signals from behaviorally […]
Stanford’s Fei Fei Li, Arnold Milstein and albert Haque have developed AI and sensor based “ambient intelligence” protocols to prevent medical errors and improve outcomes. Applications include alerting clinicians and visitors when they fail to sanitize their hands before entering a hospital room; monitoring the elderly for behavioral clues of impending health crises; prompting caregivers, […]