How accurate is SomniSense — really?

The 98% problem

"98% accurate" sounds great until you ask which 98%, on what population, against what ground truth. Accurate at detecting that there was a sound? Distinguishing snores from background noise? Counting the right number of breathing pauses in a night? These are different questions with different answers. Collapsing them into one number is the thing you do when you don't want people to look too closely.

SomniSense breaks accuracy into four numbers, each tied to a specific question. They tell different stories. Together they tell the whole one.

Two indices, one app — and why the validation numbers split that way

SomniSense produces two independent indices each night, and they're validated separately:

• BRI (Breathing Irregularity Index) — apnea + hypopnea events per hour. Same shape as the clinical AHI; that's the index that says is your breathing OK at night. 80% sensitivity / 91% precision against PSG.
• SRI (Snoring Rate Index) — snore events per hour. The first per-hour rate for snoring; the index that says how the room actually sounded. 91% sensitivity / 98.5% precision against PSG.

The reason there are two numbers per index isn't marketing — it's that they answer different questions. BRI is medically interpretable (because AHI exists). SRI is product-defined (we made it up — carefully, but still). The validation numbers are what tell you each of them is honest.

The four numbers we actually have

These come from n=70+ paired nights — meaning we ran SomniSense on a phone next to the same person, on the same night, in a sleep lab where they were also being recorded with a real polysomnography setup. The audio was scored by AASM-trained sleep technicians who didn't know what SomniSense had said.

That last part — "didn't know what we said" — is what "blinded scoring" means. We don't get to pre-train our scorers on our own answers. Otherwise the test would be circular.

How we tested it (the methodology, plain)

Detection performance was measured against gold-standard in-lab polysomnography (PSG) recordings, audio-annotated by certified sleep technicians. Every audio segment they scored was blinded to what SomniSense said about it. That's the only honest way to do it.

Specifically:

• Sample: 70+ paired nights (smartphone + PSG simultaneously) — internal validation, adults with and without diagnosed sleep breathing concerns. Demographics documented in §6 of the whitepaper, including who's underrepresented (mostly: under-18, severe BMI extremes, certain ethnic groups). I want to be specific about who's not in the cohort because "n=70+" without context can be misleading.
• Recording medium: bedside smartphone (varied iPhone & Android models from 2018 onward), 50–90 cm from participant's head.
• Ground truth: PSG with synchronized audio channel; manual scoring by AASM-trained sleep technicians, blinded to SomniSense output.
• Comparison: per-event sensitivity, per-event precision, per-night BRI vs PSG AHI agreement (Bland–Altman analysis).

The breathing-event detection algorithm builds on years of sleep apnea research by our founder. The version powering SomniSense was retrained from scratch and rebuilt for SomniAI LLC to handle smartphone audio specifically — different microphone, different distance, different acoustic context than clinical hardware. SomniAI LLC's first peer-reviewed publication of the upgraded algorithm and the US patent application are in active preparation.

Honest limitations

Here's what we don't know yet, and what I'd want to know if I were the user:

• The cohort skews adults with sleep breathing concerns. If you're a healthy 24-year-old with no symptoms, the numbers above are likely conservative for your case (you're probably underrepresented in the sample).
• Acoustic environment matters. If your bedroom has unusual acoustic properties — hard surfaces, partner snoring louder than you, a fan blowing directly at the phone — the model may catch fewer of your events. The methodology paper documents the conditions we tested under.
• Borderline events. The 20% of breathing irregularities we miss are mostly the borderline ones near the 10-second / 30%-amplitude threshold. We miss them on purpose, by tuning for precision over sensitivity. If your real BRI is 12, we might say BRI 10. If we say BRI 18, you can trust it's at least 18.
• Not validated for under-18. The cohort was adults only.
• Internal study, not peer-reviewed yet. This is the caveat I keep saying because it matters. The peer-reviewed publication is in active preparation; this page updates when it lands.

What this isn't

• Not a diagnostic claim. Even at these numbers, SomniSense is not a medical device, doesn't diagnose sleep apnea, and isn't validated for users under 18.
• Not a personal guarantee. Your specific results may differ from population averages. Read the methodology paper to know whether your scenario is in or out of distribution.
• Not a replacement for a sleep study. If your BRI runs above 15 consistently, that's a clinic conversation. We give you the data to bring. The clinic gives you the diagnosis.