When I was six years old, I remember walking with my father to the doctor's office, which was in a clinic two towns from where we lived. When we reached the Afari clinic, the only nurse on duty recorded my vital symptoms, including my temperature, pulse, and blood pressure, and told us to wait for our turn. I was the 30th person in line to meet the only doctor available at the clinic. We waited for hours before it was finally my turn. The doctor went over my vital symptoms which were: Pressure: Normal; Temperature: High; Pulse: Normal.
During the current coronavirus pandemic, one of the riskiest parts of a health care worker's job is assessing people who have symptoms of Covid-19. Researchers from MIT, Boston Dynamics, and Brigham and Women's Hospital hope to reduce that risk by using robots to remotely measure patients' vital signs. The robots, which are controlled by a handheld device, can also carry a tablet that allows doctors to ask patients about their symptoms without being in the same room. "In robotics, one of our goals is to use automation and robotic technology to remove people from dangerous jobs," says Henwei Huang, an MIT postdoc. "We thought it should be possible for us to use a robot to remove the health care worker from the risk of directly exposing themselves to the patient."
Testing a patient for Covid-19 can be an unnerving experience for health care workers, but researchers from the Massachusetts Institute of Technology and Brigham and Women's Hospital in Boston are hoping to use robots to change that. Operating robots with a handheld device, medical workers may soon be able to talk with patients about their symptoms while measuring vitals -- all from another room. Researchers modified Boston Dynamics' dog-like robot spot to measure patients' vital signs. The researchers have been using a robot on healthy volunteers and are making plans to use it to test people who show Covid-19 symptoms in a hospital setting, the university said in a news release. "In robotics, one of our goals is to use automation and robotic technology to remove people from dangerous jobs," MIT postdoc Henwei Huang said, according to the release.
Look into your camera for thirty seconds. You've just given your phone enough information to check your heart rate, oxygen saturation, breathing rate, heart rate variability, blood pressure, stress level, and ten other health indicators at medical grade levels of reliability. Now imagine doing that 50 times a day without even thinking about it. And having the results funneled to your personal medical AI engine to monitor you for any signs of poor health, ready to notify your physician if anything looks out of the ordinary. Like higher temperature, which might indicate a fever, flu ... or Covid-19. That's part of the vision of Binah.ai, an Israeli health startup that uses high-end artificial intelligence and low-end cameras built into all our phones and laptops to continuously monitor health.
Farmers have gradually embraced IoT in their bid to lower cost and increase productivity IoT-enabled wearable devices can help in monitoring the cattle's diet Wearable devices can be used to check the heart rate, respiratory rate, blood pressure, digestion and other vital signs Technological advancements have ushered in digitalisation across sectors and geographies. Internet of things (IoT), artificial intelligence (AI), machine learning (ML) and predictive analytics are transforming industries.
A new study shows that an artificial intelligence (AI) method that fuses medically relevant information enables critical circulatory failure to be predicted in the intensive care unit (ICU) several hours before it occurs. Developed at the Swiss Federal Institute of Technology (ETH; Zurich, Switzerland) and Bern University Hospital (Inselspital; Switzerland), the early-warning platform integrates measurements from multiple systems using a high-resolution database that holds 240 patient-years of data. For the study, the researchers used anonymized data from 36,000 admissions to ICUs, and were able to show that just 20 of these variables, including blood pressure, pulse, various blood values, the patient's age, and medications administered were sufficient to make accurate predictions. In a trial run of the algorithms developed, they were able to predict 90% of circulatory-failure events, with 82% of them identified more than two hours in advance. On average, the system raised 0.05 alarms per patient and hour.
In several crucial applications, domain knowledge is encoded by a system of ordinary differential equations (ODE). A motivating example is intensive care unit patients: The dynamics of some vital physiological variables such as heart rate, blood pressure and arterial compliance can be approximately described by a known system of ODEs. Typically, some of the ODE variables are directly observed while some are unobserved, and in addition many other variables are observed but not modeled by the ODE, for example body temperature. Importantly, the unobserved ODE variables are ``known-unknowns'': We know they exist and their functional dynamics, but cannot measure them directly, nor do we know the function tying them to all observed measurements. Estimating these known-unknowns is often highly valuable to physicians. Under this scenario we wish to: (i) learn the static parameters of the ODE generating each observed time-series (ii) infer the dynamic sequence of all ODE variables including the known-unknowns, and (iii) extrapolate the future of the ODE variables and the observations of the time-series. We address this task with a variational autoencoder incorporating the known ODE function, called GOKU-net for Generative ODE modeling with Known Unknowns. We test our method on videos of pendulums with unknown length, and a model of the cardiovascular system.
Able to monitor multiple patients in separate rooms simultaneously; staying on top of their blood pressure, pulse and vital signs; and spotting signs of deterioration even before the patients feel it themselves. This medical superhero is not human, but rather a product of artificial intelligence, advanced software algorithms, sensors and cameras. And it's being assembled right now at Tel Aviv Sourasky Medical Center. The creation of an AI-powered "super nurse" is the result of a decade of steady work by Ahuva Weiss-Meilik and her team in the hospital's I-Medata center. "Our doctors and nurses can't be everywhere," Weiss-Meilik tells ISRAEL21c.
This accessibility tech promises to make it safer than ever to live independently (Photo: Reviewed.com) Purchases you make through our links may earn us a commission. Technology may be entertaining, but at its essence, its primary function is to make our lives easier. When we want to find answers to our questions, communicate with friends, secure our homes, or hundreds of other scenarios, we turn to technology. At CES 2020, technology took on another role: helping us care for ourselves and loved ones.
Technology may be entertaining, but at its essence, its primary function is to make our lives easier. When we want to find answers to our questions, communicate with friends, secure our homes, or hundreds of other scenarios, we turn to technology. At CES 2020, technology took on another role: helping us care for ourselves and loved ones. In an effort to make living with disabilities and aging in place as safe and independent as possible, companies are promising smart technology that allows you to better assess you or a loved one's health and environment. Linksys Wellness Pods use WiFi to track motion and respiratory changes.