Future Now
The IFTF Blog
Anticipating Emergencies
I'm surprised that BabyBeat an algorithmic- and sensor-driven system for detecting and preventing sudden infant death hasn't gained more attention. The prototype system, developed by Tomer Apel and Anava Finesilver of Ben Gurion University, aims to detect subtle shifts in a baby's biometrics and sleeping position that hint at the potential for sudden death.
According to Fast Company, the system works like this:
The system detects bodily changes known to precede SIDS and sets off an alarm to jolt a sleeping baby into a less susceptible awakened state. As part of their final research project, Tomer Apel and Anava Finesilver developed a novel algorithm to read skin temperature and heart rate from video footage.
"This is such a minor change that it's not visible to the human eye, but it's still there. We have developed algorithms to interpret the discoloration recorded by the camera and translate them into pulses. It's widely assumed that baby's pulses slow down before SIDS, and this system could help prevent this," said Apel.
If the prototype system works as initial research suggests it could, it's a pretty amazing innovation. It's an example of something broader we're seeing in health: That real-time data analytics are opening up opportunities to prevent emergencies just before they happen. Take, for example, a system being developed by Siemens that also uses real-time data analysis and increasingly cheap technology to give people with asthma an early warning that at some point within the next few hours, they're likely to have an asthma attack, and should go to a doctor, carry an inhaler, or otherwise prepare.
I think it's worth noting that what these efforts have in common is, in effect, turning real-time analysis of imperceptible (or off-the-radar) changes into meaningful and actionable knowledge. In the next few years, making sense of previously invisible changes will be increasingly central preventing emergencies.