Cardiosense

Cardiosense

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Private Company

Total funding raised: $48.8M

Overview

Cardiosense is a Chicago-based, private digital health company founded in 2017, focusing on the early detection and management of cardiovascular disease. Its integrated platform centers on the CardioTag™, a medical-grade wearable sensor that captures seismocardiogram (SCG), photoplethysmogram (PPG), and electrocardiogram (ECG) signals. Proprietary deep learning algorithms analyze these signals to generate predictive digital biomarkers for conditions like heart failure. The company aims to shift cardiac care from reactive to proactive by identifying measurable changes in cardiovascular function before symptoms appear.

Cardiovascular

Technology Platform

Multimodal wearable sensor (SCG, PPG, ECG) combined with deep learning AI algorithms to generate predictive digital biomarkers for cardiac dysfunction.

Funding History

4
Total raised:$48.8M
Series A$16M
Series A$25M
Seed$2.8M
Seed$5M

Opportunities

The massive and growing burden of heart failure and cardiovascular disease creates a urgent need for better remote monitoring tools.
Supportive reimbursement trends for remote patient monitoring (RPM) and the shift towards value-based care provide a strong tailwind for adoption of solutions that can reduce hospitalizations and improve outcomes.

Risk Factors

Key risks include the challenge of proving clinical utility and securing reimbursement for AI-driven insights, intense competition in the digital cardiac monitoring space, and the execution risk of integrating a new technology into complex clinical workflows.

Competitive Landscape

Cardiosense competes in a crowded field including large medtech companies (e.g., Medtronic, Abbott) with implantable monitors and ECG patches, and numerous startups focused on wearable ECG and PPG-based analytics. Its differentiation lies in its multimodal approach, particularly the incorporation of seismocardiography (SCG) to assess cardiac mechanics, which may provide earlier and more specific signals of dysfunction than rhythm-based monitoring alone.