Lately, there have been announcements that could make large-scale, healthcare focused sensor network much more of a reality. A healthcare monitoring network could drive substantial improvements in care and reductions in cost. Today, if you are in a hospital, you are plugged into the sensor network that is relatively stationary and highly controlled (for obvious reasons). But there are many more healthcare, consumer-level networks that could be created. Here’s a mention of the world’s smallest blood monitoring implant and other heart rate monitoring capabilities based on visual monitoring techniques:
- http://www.extremetech.com/computing/151134-worlds-smallest-blood-monitoring-implant-talks-to-a-smartphone-but-whose
- http://appfinder.lisisoft.com/app/heart-rate-monitor.html
- https://github.com/shelhamer/visual-pulse-monitor
- http://www.geek.com/apps/measure-your-heart-rate-using-a-webcam-and-your-forehead-1552180/
Putting together a big data solution here means a solution that can scale out. Batch technologies are not the answer here so frameworks like hadoop directly are not the primary component. Other analytical frameworks like Storm, Dempsy, Apache S4, Esper, OpenMDAO, Stormkeeper or the eclipse m2m framework are needed.
In this case, BigData is about scaling out solutions for sensor networks and piecing together analytical processing nodes to create a workflow that accomplishes the analysis.
But healthcare sensor networks are not without their challenges. Here’s some links that describe the issues in more detail and the research going on in this area