We frequently write about technology components in health and medicine, including enabling technologies that support other devices or platforms. Biometrics sensors used with artificial intelligence machine learning crop up increasingly in studies that demonstrate AI’s value in a supportive role in medicine and healthcare. To cite just one recent example, we wrote about AEYE Health’s retinal image analysis to monitor signs of retinal disease. Work with compressible 3D-printed batteries by a team led by engineers at Singapore University o Technology and Design (SUTD) is an example of enabling technology, in this case, to provide power for implant devices.
Israel-based Binah.ai‘s mobile device video-based vital sign monitoring promises “previously impossible levels of accuracy, stability, and performance” by mixing AI with signal processing, according to the company. The Binah.ai process uses video from any mobile device in a 6-step system. The steps include video capture, face detection, face tracking, motion compensation, illumination normalization, and skin region selection.
According to the company website, Binah.ai’s back-end algorithms analyze video taken of a person’s upper cheek region. Binah.ai then extracts the photoplethysmogram (PPG) signal to calculate heart rate, heart rate variability, oxygen saturation, respiration rate, and mental stress. The platform plans to add blood pressure readings soon.
Binah states its technology scored between 95 and 98% accuracy during clinical testing in tandem with standard vital sign monitoring systems used in hospitals. During the tests, a smartphone on a tripod in front of the subject’s face captured video at the same time the subject’s arm was strapped to a standard medical monitoring device. We reached out to Binah.ai for links to studies that substantiate the accuracy claims and will report back when we hear from them.
There are significant advantages of video vital sign monitoring, especially during a pandemic in order to minimize person-to-person contacts to protect both patients and healthcare workers. Additional potential self-video monitoring benefits include saving clinical staff time, automatic biometric inputs for patients’ electronic health records, and early-stage diagnosis and treatment. Binah.ai’s technology potentially figures in prevention, diagnosis, treatment, and after-care monitoring.
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