Artificial intelligence is everywhere. And in the medical & life sciences industry, it has had a significant impact on the way in which treatment and care are delivered. Embedded cameras have also played a key role in this transformation by enabling medical devices to capture images required for AI algorithms to analyze test samples and patient conditions.

Of all the applications in the medical space where AI and camera technology come together, remote patient monitoring or RPM has seen a wide adoption given the possible benefits. So, let us learn how artificial intelligence and embedded vision can change the game for patients and caregivers in remote patient monitoring.

Remote patient monitoring is dependent on one or more digital imaging solutions that are integrated into hospital networks. It allows health workers to monitor multiple patients, and clinical teams to assess patient conditions without being physically present in the same room.

By leveraging artificial intelligence, remote patient monitoring is moving from mere video monitoring to doing behavioral analyses like fall detection, tracking patient movements, and many such. The patient’s behavior is then classified and analyzed using AI frameworks like PeopleNet to prevent falls from happening.

For example, imagine a patient on a highly sedative medication trying to wake up from a hospital bed. An AI model trained to identify patients who are moving from a minimally conscious state can send an alert to a caretaker or nurse for immediate attention. This is made possible by continuously capturing the video of the patient using the camera in the RPM device, thereby feeding the required image and video data to the AI model.

This is already happening, and e-con Systems is currently working with multiple customers in this space by helping them smoothly integrate our camera solutions into their RPM devices.

So that’s it about how artificial intelligence and camera technology are changing remote patient monitoring.