The startup has developed a low-cost electronic stethoscope that utilizes auscultation to monitor lung sounds, automatically detecting crackles and wheezes. This technology enables healthcare professionals to differentiate between severe lung conditions and less critical issues, facilitating timely and accurate diagnoses for patients with chronic respiratory diseases.
Funding
$3.6M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Traditional stethoscopes can be limited in their ability to detect subtle lung sounds, potentially leading to missed or delayed diagnoses of respiratory conditions. Variability in clinician experience and subjective interpretation of lung sounds can also contribute to inconsistencies in patient assessment.
Solution
ChestPal Pro is a smart stethoscope that combines a Bluetooth-enabled stethoscope with a mobile app to automatically detect and classify lung sounds. The device employs digital signal processing and AI algorithms trained on a dataset labeled by respiratory specialists to identify normal breathing, wheezes, crackles, artifacts, and heartbeats. ChestPal Pro displays results visually through spectrograms and provides automated analysis, aiding healthcare professionals in the diagnosis and management of respiratory conditions. The system is designed to facilitate early detection of acute respiratory events at the point of care and enable the tracking and sharing of patient recordings.
Target Audience
ChestPal Pro is intended for use by healthcare professionals in various settings, including hospitals, clinics, and primary care, to aid in the diagnosis and management of patients with respiratory conditions, including adults, adolescents, and children over 3 years old.
Features
- Bluetooth-enabled stethoscope for wireless connectivity to mobile devices
- Mobile app for recording, storing, and sharing lung exam data
- AI-powered algorithm for automated detection and classification of lung sounds, including normal breathing, wheezes, crackles, artifacts, and heartbeats
- Visual representation of lung sounds through spectrograms
- Option for spot or complete lung exams to capture sounds from select areas or all lung fields
- Ability to filter and visualize patient history to identify trends over time
- HIPAA compliance for secure handling of patient data
- High sensitivity (94%) and specificity (97%) validated against lower respiratory tract infections in COVID-19 patients
- 87% classification accuracy across main lung sound types