Address

Onescope SA
Chemin de la Mairie, 4ter
1223 Cologny
Switzerland

Connected to life.

A revolutionary pocket-sized medical device, powered by AI, decentralizing the assessment, monitoring, and management of respiratory diseases.

Unique and
innovative solution

Lung sounds, oxygen blood saturation, heart rate, and temperature are simultaneously transmitted to an intuitive mobile app for real-time analysis and recognition of respiratory acoustic signatures by AI algorithms. The app guides the exam, structures the findings, and is designed to provide, once certified, an AI-based score supporting severity assessment and the choice of care pathway.

Our AI-based approach is built to empower healthcare professionals and, in time, patients themselves, to perform rapid pulmonary checks and better manage respiratory conditions. Onescope offers a decentralized solution that lowers healthcare costs and improves patient outcomes.

A disruptive 3-in-1 medical device

Our patented technology integrates 3 sensors allowing simultaneous measurement of sound, oximetry and patient temperature. The combination of these biosignals is unique and strengthens the performance of our AI algorithms.

Thermometer

Record body temperature

Digital stethoscope

Record lungs sounds and respiratory frequency

Oxymeter

Record blood oxygen saturation and heart rate

2 Patent Families

Device granted EU · allowed US 2026 · AI filed

>3'000 Patients

across 5 countries

250'000 Respiratory

cycles recorded

DeepBreath

A revolutionary AI model for the detection of respiratory disease signatures

AI and Machine Learning (ML) are techniques for designing and training algorithms from a database. The main objectives of this technology in the field of health care to improve decision-making, enhance the quality and safety of health care and advance clinical research.
In order to demonstrate the feasibility of predicting lung disease using AI algorithms, a number of clinical studies have been conducted to build a database of chest sounds and develop AI algorithms. The results of these studies have demonstrated the strong performance of our DeepBreath AI model in identifying adults and children who are breathing normally and those with lung disease. These results are published in npj Digital Medicine (Nature Portfolio).

Publications:

  1. Heitmann et al., Nature Digital Medicine, 2023
  2. Siebert et al., BMC Pulmonary Medicine, 2023
  3. Glangetas et al., BMC Pulmonary Medicine, 2021
  4. Solà et al., IEEE Engineering in Medicine and Biology Society, 2016

Onescope turns body sounds into actionable clinical insight.