Show HN: Live breath detection and biofeedback from a phone microphone

A Swiss family doctor has developed shii • haa, a breathing app that uses a phone's microphone to provide live biofeedback on rhythm, depth, and regularity without uploading any speech or raw audio. The app processes all signals on-device using signal processing, a breathing state machine, and machine learning, aiming to promote self-awareness rather than gamifying breathing into a score or competition.

Hi everyone, I am Felix, a famliy doctor from ZH, Switzerland. A couple of month ago I started this little project called shii • haa, a breathing app that uses the phone s microphone for live biofeedback My prior work in emergency medicine and intensive care was closesly linked to breathing, mostly in critical situations... and let me to reevaluate my own way of breathing. over time one question popped into my mind: can medical knowledge and biofeedback make an app actually promote self-awareness instead of attaching your goals to the award system of the app. it combines signal processing, a breathing state machine and ML. The state machine follows inhale, exhale and transitions in the mic signal. A quality layer rejects noisy or ambiguous windows before signals are used for feedback. All processing is done on-device, no speech or raw audio is uploaded. What I'm trying to avoid is turning breathing into another score or game. The app gives feedback on rhythm, depth and regularity, but the point is more "notice what you are doing" than "perform well". I'd be interested in feedback, especially from people who have worked on signal processing, health UX, or Android/iOS audio issues. Comments URL: https://news.ycombinator.com/item?id=48372036 https://news.ycombinator.com/item?id=48372036 Points: 9 Comments: 1