Mhealth AI for remote & rural chronic disease detection and management

The National Heart, Lung, and Blood Institute awarded Tele-Stethoscope Inc. $406,367 on September 1, 2026, under the Cardiovascular Diseases Research program (CFDA 93.837) to develop Phase I algorithms and demonstrate technical feasibility for a mobile phone–based diagnostic tool that uses acoustic data to predict clinically significant spirometry and echocardiogram findings.

The recipient will develop algorithms for predicting FEV1 percent predicted findings using mobile phone–captured auscultation data, recruiting 237 patients previously referred to pulmonary function testing within a health system serving a large rural population. The award also supports developing algorithms for predicting low ejection fraction and abnormal diastolic relations and filling pressures using previously enrolled patient data and existing recordings. Additionally, the recipient will conduct qualitative research with key stakeholders to inform commercial planning, product optimization, and FDA intended use statement development. The technology is a Class 2 mobile phone auscultation software as a medical device employing a novel chaos-based biofluid dynamics approach to acoustic data modeling; it is designed to aid providers in situations where gold standards like echocardiography and spirometry are unavailable, including telehealth exams and pre-office screening.

Tele-Stethoscope Inc. is a self-certified small disadvantaged business. The period of performance runs through August 31, 2027, with work performed in Brownsboro Village, Kentucky.

Abstract

The lack of remote detection of chronic heart and lung diseases in frontline medicine remains a barrier to improving patient outcomes and health disparities. Our long-term vision is to enable any mobile phone to predict key spirometry and echocardiogram findings. This will improve patient access to quality care, drive early diagnosis and enable remote patient monitoring. The goal of this study is to 1) demonstrate technical feasibility of classifying patients in terms of clinically significant echo and spirometry values using a mobile phone and 2) engage in qualitative research techniques with key stakeholders. The specific aims of the study are to use mobile phone captured auscultation data to: 1) determine phase I technical feasibility of and produce phase II ready algorithms for predicting FEV1 % predicted (FEV1%P) related findings. Clinically, the study will recruit 237 patients previously referred to a PFT lab within a health system serving a large rural population. 2) to determine phase I technical feasibility of and produce phase II ready algorithms for predicting low ejection fraction and abnormal diastolic relation (EA) & filling pressure (E/E') findings. No clinical enrollment is necessary for this aim since previously enrolled patient data will be analyzed. Analytical work builds on our previously funded studies and large database of recordings. 3) to gain key stakeholder insights necessary for commercial planning, product optimization and FDA intended use statement development. The technology is class 2 mobile phone auscultation software as a medical device. IT employs a novel chaos-based biofluid dynamics approach to modeling acoustic data. Our device is being developed to aid providers in situations where gold standards like echocardiograph and spirometry testing are not possible, such as impromptu tele-health exam, pre-office visit screening and in less developed countries. The device is simple enough for patient self-recording and can be operationalized on 7 billion phones globally simply by downloading our software. However, the results are intended to be interpreted only by qualified providers. The device would significantly improve clinical practice by enabling quantitative assessments of key heart and lung findings in places and applications that are not now possible. This is especially impactful to reduce health disparities in populations with access barriers to clinical facilities. And scientific knowledge would be advanced by demonstrating the feasibility of a chaos based, "locked" device to estimating echocardiogram and spirometry values.