DEEP TECH HEALTH + NEUROTECH
University of Missouri’s Marjorie Skubic has used sensors to measure gait speed and stride length, to predict falls. The goals is to use wearables and smart home technology to preserve independence and allow seniors to age in place. Data was collected at an independent-living style retirement residence. Images and nurse alert emails were generated when […]
SenseCare (Sensor Enabled Affective Computing for Enhancing Medical Care) is a Cork Institute of Technology led project meant to teach computers how to recognize and respond to human emotions. The goal is to use applied psychology to monitor and improve the care of dementia patients. The affective computing based system will manage data from voice and face […]
Ludwig is a University of Toronto – built robot meant to assist seniors with cognitive issues. “He” stands in front of a person, displays a picture on a screen, and asks the viewer to describe what he or she sees. Ludwig then interprets a user’s condition, including engagement, happiness or anxiety, and behavior changes over time. […]
iBeat is a wearable emergency response system that continuously monitors the heart. Meant for seniors, it detects cardiac arrest in real time, provides alerts, and sends regular updates to caregivers. If cardiac arrest is detected, the wearer receives a call within 10 seconds. If he/she cannot be reached, an emergency contact and emergency medical services […]
Hitachi’s EMIEW3 robot, designed to provide customer service in commercial environments, could be an ideal companion for the elderly or disabled. Its “remote brain” allows it to identify voices, images and language in its surroundings (which it can process with background street noise). AI enables it to respond to human dialogue and avoid collisions. It is light enough to […]
SINTEF‘s Anders Liverud and Tellu AS colleagues have developed a fall detector able to detect more types of incidents, including “sinking falls” often missed by current sensors. These slow motion falls are difficult to monitor as they occur slowly, and the g-forces are not significant. Examples include when a senior slides down a wall, or […]
Dina Katabi and MIT colleagues are using radio signal based software to recognize human silhouettes through walls, and track movements. The technology is intended to help monitor children and the elderly, and could be used by the military and the police. The signal is displayed on a screen, where movements are tracked in real time. The person is […]
HomeHero is a senior caregiver site that uses an algorithm to match families with carers, and provides video interviews, daily, mobile access to care reports and security camera feeds. While it is not the only caregiver matching site, it is perhaps the slickest, and has one standout feature — the ability to crowdfund care via […]
Notre Dame’s Nitesh Chawla has created eSeniorCare, a personalized, social app to help seniors age in place. Several existing apps track data. eSeniorCare is meant to engage and stimulate seniors, and be interactive. Users can connect with carers by sending questions and concerns through text or voice recordings. Health goals are tracked and sent to supporters who […]
Roozbeh Jafari and Texas A&M colleagues are developing a gait monitoring wearable to prevent senior falls. The system will analyze multiple sway and gait parameters while one walks or stands on one leg. Users will receive auditory and vibration feedback to reduce an unsafe sway and prevent falls. The wearable will be worn on the […]