Digital health company PeerWell just announced the launch of Trip and Fall Hazard Detector, an augmented reality (AR) extension providing real-time analysis from video stream from a smartphone’s camera that identifies and helps correct trip and fall hazards at home, one of the major setbacks for postoperative recovery, especially for those undergoing joint replacement and spine surgery.
This AI-powered app extension allows patients and caregivers to scan their home using smartphone cameras, receive alerts on any hazards patients could potentially trip over at home and tips on how to fix them. Proper home setup is often times overlooked and neglected in ensuring patient safety for optimal recovery from surgery. But as a matter of fact, 29 million older adults fall every year and many of those are among the millions of Americans going through joint replacement and spinal surgery.
Currently, patients can either receive general information on home setup from confusing brochures at doctor’s office or spend a big sum having a homecare expert over to help properly set up their homes. This newly launched interactive Trip and Fall Hazard Detector in a sense extends physicians’ reach to ensure patient safety in recovery.
PeerWell’s AI will assign patients’ homes a risk score, which can be used by health systems to allocate in-home occupational therapy visits and inform discharge planning. In home patient safety is a key focus area for the healthcare industry, driven by the aging of western populations, continued pressure to reduce hospital length of stay, and the rapid growth of same-day surgery.
“Until now, augmented reality has mostly been used in gaming,” said Manish Shah, CEO of PeerWell. “We’ve combined it with real-time image recognition powered by our AI to bring this life-saving tool to patients. This technology continues to put us years ahead of the industry. Most image recognition systems are trained using publicly available data sets. Here, there is no data set like this, so even the foundational data is proprietary.”
PeerWell will offer this as a new component of its existing platform, which includes smartphone based range of motion assessment, autonomous care path creation, and the tracking of over 40 data streams per episode of care. PeerWell has collected over 1 million mHealth records to date, enabling its artificial intelligence based system.