Ultra-Low Power Sensor

Clairways' ultra-low power wearable acoustic sensor allows for long-term, continuous monitoring of the lungs and airways.

Analytics & Reporting

Summary and trends of various metrics are collated and reported for each patient in an easily digestible format that highlights relevant insights and patterns.

AI Symptom Detection

The core of Clairways technology is on-device machine learning that detects and characterizes respiratory  metrics:​

coughing, wheezing, lung sounds, respiratory patterns, heart rate variability, inhaler use

coughing

wheezing

lung sounds

respiratory patterns

heart rate variability

inhaler use

Capture Reliable Metrics

Reduce your reliance on effort dependent monitoring and participant journals, which hurt both adherence and data quality.

Reduce Your Trial Duration

Enroll participants faster and determine dosing protocol faster, thereby reducing trial duration.

Enable Your Virtual Trial

Recruit for rare disease studies without geographic restriction and eliminate the high costs of participant trial site visits.

Improve Your Commercialization

Demonstrate your treatment’s impact for payors and prescribers with long-term, continuous, objective participant metrics.

Participants go about their normal lives, while the sensor continuously captures metrics​

Easily digestible analytics and summary metrics are transmitted back to the trial

Jeff Bemowski

Co-Founder, CEO

Jeff is experienced in product management, market research, and customer discovery for novel biomedical devices. He previously worked in product management for Endotronix, a Series C funded medical device company. MBA, Tuck School of Business at Dartmouth.

Justice Amoh

Co-Founder, CTO

Justice is a pioneer in embedded systems for stochastic modelling of physiological signals. His focus is on deep neural network models for detecting the onset of symptoms in respiratory diseases. PhD, Thayer School of Engineering at Dartmouth.

Ricardo Serrano Smith
Embedded Systems Engineering Manager