Customers often tell us about their problems finding IV pumps and other critical mobile patient care equipment, and the resultant frustration among nurses, clinical engineering, and many others. The net effect is increased expense and wasted time, which takes away from the goal of providing timely, high quality patient care.
The NavvTrack® Care Traffic Control platform has deployed a Bluetooth Low Energy (BLE) sensor network at several Boston area hospitals, designed to monitor the supply and location of IV Pumps throughout the building. Part of this solution uses a network of sensors, some of which contain a thermal camera that identifies the location of equipment, but can also be used to detect heat signatures in a room. This technology is used to determine things like occupancy of the room, or if a patient is in their bed or not.
The interest in working on this began recently when my father was in the hospital. He had a fall in a room where there was already a standard video camera monitoring him. Unfortunately, he was on the floor for 10 minutes before my sister arrived and found him. The system in place to monitor wasn’t smart enough to detect the fall, and failed to recognize he was not where he was supposed to be.
Solving these kinds of problems is in our DNA at Navv Systems. It was clear we had the right tools and a solid understanding of the nature and scope of the problem. We always aim to focus our R&D efforts on technology that has the potential to transform healthcare in multiple ways. One of the tools we have recently been experimenting with is thermal imaging. This involves the use of infrared (heat-sensing) cameras to detect what we refer to as “presence” - that is the status of a person (patient, employee, etc.) in a particular place. This can be relevant for a number of healthcare-specific applications, and though we knew thermal cameras could be used to detect a person, we also wanted to know if the patient was in the correct location. This seems like a simple extension, but in order to accurately detect a change in conditions (like an elderly patient falling out of bed) we needed to tap into some of the specialized expertise developed at Navv Systems over the past few years - namely, the ability to merge contextual data from multiple input systems together, and assemble a complete picture of what is actually happening in a real-world 3-dimensional space, indoors, in real-time.
More to come on how thermal imaging, artificial intelligence, and a very large dog came together to solve this problem in part II.
