IoT in Medicine: Applying real time rules processing and actuation in Radiation Dosimetry

Abstract Winner: Digital Medicine & Wearable Technology

Author: Raghu Bala

Background Modern medicine has utilized sensors for decades - thermometers, blood pressure monitors, urine analysis strips are all sensors in various forms. These sensors, when subjected to input, provide a reading that translates to a data point for a physician in his/her diagnosis of a patient. The Internet of Things, or IoT, refers to the internetworking of smart connected devices for the purpose of collecting and exchanging data. The focal point of our research is to explore the benefits of applying smart IoT-enabled sensors in the field of medicine for real-time collection and aggregation of radiation data and how it impacts the healthcare facility outcomes. Method With IoT, sensors in Medicine can now operate as part of a larger ecosystem of connected technologies. The sensory data is captured and transmitted through a network (e.g. BLE, Ultrawideband, Wifi, 4G, LTE) to cloud based services. For our research, we have developed a proprietary, smart radiation dosimeter (SRD) device for collecting radiation exposure data, at healthcare facilities. Unlike common radiation dosimeters that capture data on a film, over a 30 to 60 day window, ours is solid-state electronic dosimeter. It collects and disseminates radiation readings (x-rays, gamma and beta radiation), precise location and timestamp in real time via cloud connectivity. We utilize the NetObjex IoT platform and its Rules engine to inspect incoming data packets from an SRD in two ways. First, we capture the radiation exposure in real-time instead of waiting for a 30 or 60-day window and share this information with the SRD holder. We also check to see if the reading is beyond a safe threshold so we can immediately inform the SRD holder about the unsafe environment. Edge computing algorithms enable localized decision making without cloud connectivity in this case. These algorithms can be modified and adjusted with Over-The-Air (OTA) updates. Secondly, we analyze the cumulative exposure of an individual over a rolling 30-day window by precise location and timestamp. This will significantly increase the safety of the SRD holder and reduce the liability of the healthcare facility. In both cases, correspondence with the stakeholders, the healthcare facility, and the SRD holder is made through a free mobile application. Additionally, when the exposure reaches unsafe levels, the response is handled by a notification e.g. SMS, email, or mobile notification. Custom integration for actuation e.g. the invocation of a remote command from the cloud to shutoff an x-ray device, or turning on a siren, is possible as well. Conclusion Our initial results have been extremely promising in that IoT enables much faster reaction to cases of radiation overexposure unlike the current dosimetry devices. The benefits of this approach are groundbreaking as the core tenets of real time data capture and analysis can be applied to many other facets of medicine and improve outcomes from a health, and medical liability point of view.

Co Author/Co-Investigator Names/Professional Title: Srini Pagidyala, Advisory Board Member, Hoang Thanh Tung and Dr Divakar Krishnareddy