Out-of-hospital cardiac arrest (OHCA) is a major cause of mortality throughout many regions of the world. Calling an emergency number should be the first thing the bystander does. Today almost everybody have a smart phone, permitting the incorporation other functions in addition to speech by using an emergency app. In case of emergency, the app is activated and takes control over the phone. A dispatcher receives the phone call, and in addition to talking to the bystander, the app provides the dispatcher with GPS coordinates.
At UiS we are working on including chest compression measurement using the video camera of the smart phone placed beside the patient during bystander CPR. Image processing is performed on the smart phone, and the dispatcher will be provided with the detected compression rate, if any.
An example of the information to the dispatcher can be seen here.
The app is now available at google play and Appstore under the name TCPR link . See also TCPR Link Demo .
Some different publicity about the app (mostly in Norwegian):
http://www.uis.no/om-uis/nyheter-og-presserom/lanserte-livreddende-app-i-usa-article122350-8108.html
https://www.nrk.no/rogaland/ny-mobilapp-kan-hjelpe-deg-med-a-redde-liv-1.13936712
https://tv.nrk.no/serie/distriktsnyheter-rogaland/DKRO99022718/27-02-2018#t=35s
http://www.uis.no/om-uis/nyheter-og-presserom/lanserte-livreddende-app-i-usa-article122350-8108.html
The following open access publication show the results of our first realt-time app-implementation:
1. K.Engan, T.Hinna, T.Ryen, T.S.Birkenes, H.Myklebust, "Chest compression rate measurement from smartphone video", BioMedical Engineering OnLine, volum 15, no 1, pp 1-19, 2016, DOI: 10.1186/s12938-016-0218-6
The long-hair problem is fixed, and is explain in this paper that recieved «best paper award» at ISPA 2017:
Ø. Meinich-Bache, K.Engan, T.S. Birkenes, H.Myklebust “Robust real-time chest compression rate detection from smartphone video”, In Proc. 10th int. symposium on Image and Signal Processing and Analysis (ISPA), IEEE, pp. 7-12. Ljubljana, Slovenia, sept 2017.
We are currently looking onto estimating compression depth in different ways. A first step was presented at SCIA 2017:
Ø. Meinich-Bache, K. Engan, T. Eftestøl, I. Austvoll “Detecting Chest Compression Depth Using a Smartphone Camera and Motion Segmentation”. In: Sharma P., Bianchi F. (eds) Image Analysis. SCIA 2017. Lecture Notes in Computer Science, vol 10270. Springer, Cham, 2017. https://doi.org/10.1007/978-3-319-59129-2_5