AI-controlled sensors could save lives in smart hospitals and homes
Reporter: Irina Robu, PhD
Arnold Milstein, professor of medicine and director of Stanford’s Clinical Excellence Research Center along with Fei-Fei Li, computer science professor and graduate student Albert Haque believe that having the ability to build technologies into the physical spaces where health care is delivered minimize the rate of fatal errors that occur lately due to sheer volumes of patients and complexity of their care. Even though, the technology is a very promising, it also raises legal and regulatory issues as well as privacy concerns.
They believe that the AI can alert clinicians and patient visitors when they fail to sanitize their hands before entering hospital room for example. Also, AI tools can be built into smart homes where the technology can monitor the frail elderly for behavioral clues of a health crises and can let in-home caregivers, remotely located clinicians and patients to make life saving interventions.
Li and Milstein co-direct the 8-year-old Stanford Partnership in AI-Assisted Care (PAC), one of a growing number of centers, including those at Johns Hopkins University and the University of Toronto, where technologists and clinicians have teamed up to develop ambient intelligence technologies to help health care providers manage patient volumes, roughly 24 million Americans required an overnight hospital stay in 2018.
Haque, who compiled the 170 scientific papers cited in the Nature article, the availability of infrared sensors that are inexpensive enough to build into high-risk care-giving environments, and the rise of machine learning systems as a way to use sensor input to train specialized AI applications in health care.
The infrared technologies are of two types. The first is active infrared, such as the invisible light beams used by TV remote controls. Nonetheless as an alternative of simply beaming invisible light in one direction, like a TV remote, new active infrared systems use AI to compute the time it takes the invisible rays to bounce back to the source, like a light-based form of radar that maps the 3D outlines of a person or object.
These alert systems are being confirmed to see if they can reduce the number of ICU patients who get nosocomial infections due to failure of other people in the hospital to fully observe to infection prevention protocols.
The second type of infrared technology are passive detectors, that allow night vision goggles to generate thermal images from the infrared rays generated by body heat. In a hospital setting, a thermal sensor above an ICU bed would allow the governing AI to sense twitching beneath the sheets, and alert clinical team members to forthcoming health crises without continuously going from room to room.
Constant monitoring by ambient intelligence systems in a home environment could also be used to detect clues of serious illness or potential accidents, and alert caregivers to make timely interventions. . Researchers are still developing activity recognition algorithms that can examine through infrared sensing data to detect variations in habitual behaviors, and benefit caregivers get a more holistic view of patient health.
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