Inspiration

Teaching patients new skills before discharge when working on the floor clinically in the ER, ICU, Med/Surg areas. https://www.americannursetoday.com/wound-care-post-acute-care/ https://intermountainhealthcare.org/services/wound-care/patient-education/ https://intermountainhealthcare.org/ext/Dcmnt?ncid=520684503

What it does

Provides a base library of common skills for hospital patients being discharged from a healthcare facility.

How I built it

(This is a pitch for ATT&T Magic Leap Hackathon, with actual project code being worked on at event.) Base Rails 6 app was created using the Edge branch of Rails, XR integration via aframe is the content delivery mechanism via the web to the Magic Leap Helio browser. Please see attached youtube link for an example of one of our Rails apps on Magic Leap thru Helio.

Challenges I ran into

Learning new technologies to solve existing problems requires diverse knowledge sets and collaboration.

Accomplishments that I'm excited about

Directly impacting patient quality of care delivery and consumption is rewarding by seeing positive outcomes in the community, this is what excites and drives new ideas and innovative solutions in the projects that i collaborate on.

What I learned

New paradigms like Mixed Reality require new ways of applying existing content and creating new to mesh into a cohesive UX. Mulituser experiences are paramount, desiging this Healthcare ADL Training application for the provider to be able to remotely via tele-presence interact with the patient if needed, is the optimal outcome for the interactive Mixed Reality app.

What's next for Healthcare ADL(activities of daily living) training.

Building out a database for common healthcare education topics with Mixed Reality technologies. Then next phase is to integrate depth cam scans of actual wounds as a means to assist in documentation and health maintenance(different therapies are ordered as the wound progresses or does not progress thru stages of healing). The TrueDepth cam on iPhone X model line is a guide for the kind of camera and meshing capabilities needed to start to gather clinical level significant data via these devices. Orbbec cams provide a similar level of detail space mapping needed for this kind of use case. We've implemented a similar feature in one of our iOS apps utilizing coreML to help stage wounds. Ref link: https://itunes.apple.com/us/app/skin-assess/id1378011734?mt=8 Integrating this data collection and utilization would occur thru our Rails based evermed(research) EMR with data portablity and interoperability via Redox Engine(a health integration engine or HIE) https://www.redoxengine.com

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