Breathing is a fundamental activity for sustaining life. Beyond that, how and how often we breathe can provide insight into our health, how hard we are physically working, how calm we are, and generally how we feel. So much of our emotions are also tied to how we breathe; we say “we can’t breathe” when we’re anxious or nervous or claustrophobic, love or excitement or amazement can “take our breath away”. Understanding how we breathe through objective recording, signal processing, statistical analysis and pattern recognition, and correlative associations can provide a unique vantage point to how we are doing.
With Respa, we’re not just recording breathing sounds. We’re trying to understand patterns of breathing by looking at breath rate variability (how regular or irregular is our breathing) and breathing intensity (how deep or shallow is our breathing), and relating it to situational awareness of what we are doing at the time (also objectively recorded). We can achieve this through modern signal processing methods using both time- and frequency-domain methods and peak-finding algorithms that allow us to accurately identify each breath both in timing and intensity, which then allows us to look at how we breathe. Alongside this, we use data science to identify correlative patterns between breathing patterns and different activities. The activities could range from athletics and yoga to meditation, rehabilitation, and preparing for a big event; it could even help quantify if you’re recovering from an illness. Real-time breathing pattern analysis can guide you in whatever activity you are doing to enhance, optimize and maximize performance, whether you are a high school athlete, a yoga enthusiast, a weekend warrior, a public speaker or in a high-pressure occupation.
World's first breathing sensor Respa by Zansors is now available to order here
Abhijit Dasgupta, PhD, is Co-Founder and Chief Data Science Officer of Zansors. You can follow him on Twitter @webbedfeet