By attending the Health Panel held at TreeHacks, we had the opportunity to listen and better understand the needs of the health industry. Afterwards, we consulted with a surgeon, who mentioned that while scrubbed in and sterile in the operating room, it is very important to reference the scans containing important details relating to the surgical operation to avoid any mishaps.

What it does

Ammalia is a Leap Motion assisted app that allows medical professionals to easily view and manipulate scans while scrubbed in, sterile and ready to perform a surgery.

The Leap Motion controller tracks the professionals hands using infrared cameras, motions such as swipe, grab and pinch were some of the movements integrated in our application. Authentication and database storage are made possible by using the Dropbox API

Primary use cases

The areas we believe Ammalia could be the most useful is with radiology image manipulation / scrolling while scrubbed in & sterile in the OR.

How we built it

[Leap Motion API](

  • With Leap Motion, you can interact with digital content in virtual and augmented reality, Mac and PC using your hands just as you would in the real world.
  • The unique combination of software and hardware tracks the movement of hands and fingers with very low latency, converting in into 3D input.
  • We used the Leap Motion API to program the gestures in order to manipulate the medical imaages just using our hands and the external Leap Motion hardware

[Dropbox API](

  • Dropbox is a personal cloud storage service that is frequently used for file sharing and collaboration
  • Use Dropbox API for uploading/storing images of patient’s
  • Use Dropbox API for user authentication as patient security is an issue in the current health care system

[Flask] (

  • Flask is a "microframework" primarily aimed at small applications with simpler requirements

Challenges we ran into

  • Working with the Leap Motion API was difficult since a limited number of our team members has experience with JS and front-end development in general.
  • The gestures are very mathematically dependent so programming and calibrating the sensor was difficult to perfect.
  • We had to utilize the help of the mentors available to us to get the Dropbox API to work correctly but we were able to get it working eventually.

Accomplishments that we're proud of

  • We were very excited when we successfully got the Leap Motion API to work with the actual hardware as we didn't think we'd be able to finish the hack in time.
  • Getting the Dropbox to link up correctly with the medical images that had to be manipulated was challenging.

What we learned

  • Effie learned how to edit a webpage.
  • Frances and Diana learned the basics of the Leap Motion API.
  • Stephanie learned how to create a web app using Flask and linking it to the Dropbox API.

What's next for Ammalia

Ammalia has endless possibilities as it can be applied to various industries including medical, engineering, mining, etc..

  • We can see Ammalia potentially pivoting to include 3D manipulation of MRI and CT scans mid-procedure, which is important when, for example, determining the extent of a tumor in real-time.
  • Another area we could look into is radiology and cardiology intervention which would actually involve catheter manipulation.
  • Also, depending on the patient chosen, Ammalia could also showcase different health record data points that pertain to the patient being showcased (i.e. name, age, background, etc).
Share this project: