Facial Recognition – Not just the surface
- When a patient is admitted, a front-facing photo is taken.
- The photo is stored either locally or in Azure Blob Storage.
- The URI for the image is inserted into an HL7 Version 2.x OBX-5 message.
- Once the Processor Service receives the message it is added to the HL7 FHIR Patient Resource.
- When the patient is brought into the Operating Room, a facial scan is performed.
- It is verified using the Azure Cogitative Face API Service.
Solving the problem
I have been developing an extension device which can be attached to a Cell Phone or Pad.
I have several 3-D Cameras and am also working with the Azure Kinect SDK.
I am currently training the device software to detect not just the face, but the complete muscle and bone structure. The following video shows what I am targeting.
Patient Identification Device
- The device will have it own camera or can be used with the phone or pad own camera.
- It will use the phone or pads WiFI to connect to a IoT Edge Server
- The server could connect to Azure to synchronize the Patient images.
- The server would also store the patients image .
- Since the server has only one purpose, a Raspberry PI 4 or a Nano Jetson with the Extension Board for a 1-TB SSD would be all that is needed.
- The Server would run Linux and be configured as an HL7 FHIR Server and API.
- It would only contain the FHIR Resources for Medical Devices and Patient data.
- All data would be encrypted in flight and at REST.
I am not in the business of selling products. I normally open-source everything.
I plan on providing a complete tutorial for those that want to build the recognition software. I don’t want to see it ending up being sold by a device manufacturer.