Post by Akhila Labs, LLC

Continuous Sleep-Quality & Apnea Screening Band Sleep monitoring breaks down outside the lab. Movement noise, inconsistent signals, and delayed analysis make real-world data unreliable. Where engineering gets complex: • Extracting respiratory patterns from PPG • Handling motion artifacts during sleep • Separating sleep stages with limited signals • Detecting apnea risk in real-time • Maintaining privacy for clinical data How we support: • Multi-modal sensing (PPG + respiratory effort modeling) • Artifact-robust TinyML models for sleep stage classification • On-device apnea risk scoring algorithms • Secure data pipelines for home-to-clinic sync What this enables: • Continuous home monitoring (no lab dependency) • Real-time insights instead of delayed reports • Clinically relevant data with lower noise • Privacy-compliant remote diagnostics If you're building sleep tech or remote patient monitoring devices, this is where most of the system complexity sits. #MedicalDevices #Wearables #SleepTech #RemotePatientMonitoring #TinyML #EmbeddedSystems #AkhilaLabs