The startup develops a wristwatch-type wearable device that monitors heart failure patients by detecting cardiac murmurs, reduced activity, and peripheral coldness. This remote medical treatment system enables early symptom detection, allowing patients to receive timely intervention from home.
Funding
Funding not disclosed
Founders
Product
Problem
Chronic heart failure patients face a high rate of readmission, with approximately 40% returning to the hospital within a year due to worsening conditions. Early detection of deterioration is critical to improving patient outcomes and reducing healthcare costs, but current at-home monitoring methods are limited. Traditional methods for assessing heart failure status require in-person visits for blood tests and imaging.
Solution
A-wave is developing a digital therapeutic (DTx) solution for remote monitoring of chronic heart failure patients. The system uses a wearable device with integrated AI and a mobile application to monitor key indicators of heart failure exacerbation, including heart-specific murmurs, activity levels indicative of pulmonary congestion, and peripheral coldness related to sympathetic nerve overstimulation. By continuously tracking these parameters, the A-wave system aims to provide early warnings of worsening heart failure, enabling timely intervention and reducing the need for hospital readmissions. The device is currently undergoing clinical research at Osaka University Hospital, with preparations underway for clinical trials.
Target Audience
The primary target audience includes chronic heart failure patients at risk of readmission, as well as cardiologists and healthcare providers seeking to improve remote patient monitoring and reduce hospital readmission rates.
Features
- Wearable sensor continuously monitors heart sounds for heart-failure-specific murmurs.
- Activity tracking to detect reduced activity levels associated with pulmonary congestion.
- Peripheral temperature sensing to identify coldness indicative of sympathetic nerve overstimulation.
- AI-powered analysis of sensor data to identify patterns and predict heart failure exacerbation.
- Mobile application for patients to view their data and receive alerts.
- Remote monitoring dashboard for clinicians to track patient status and intervene as needed.