Xilicom Research

Research: “Consumerizing” Healthcare Industry

Acoustic Cardiography — AKG Normal and Abnormal Sound Analysis

Heart failure affects 5.5 million Americans and 22 million people worldwide every year. Its victims span the spectrum: half are healthy young athletes, half are aging baby boomers.

Yet there are only approximately 10,000 heart specialists in the United States serving a patient population of 80.7 million. The gap between supply and demand in cardiovascular care is profound and growing.

In 2009, the United States spent $2.5 trillion on medical expenses. That figure is projected to reach $4.5 trillion by 2019. According to the Commonwealth Foundation, one-third of U.S. households spent more than 10% of their income on medical care, and among low-income households, 53% spent an average of 44% of their income on healthcare.

For centuries, physicians have used the acoustic stethoscope and phonocardiograph to diagnose conditions of the heart, lungs, and intestines. These instruments remain among the most valuable diagnostic tools available — non-invasive, immediate, and informative.

We propose extending this proven diagnostic approach using non-invasive acoustic cardiography: a consumer-grade device combining surround-sound signal processing, artificial intelligence, and an internet-connected socio-medical network. This system would allow continuous, at-home monitoring of cardiac health, provide early warning of anomalies, and share anonymized data through a community health network comparable to a medical WebMD.

Please join us if you want to see the cost and performance of medical devices taking the route of consumer electronic devices.

Jason Kim

Present: Acoustic Medical Diagnosis

Physicians today use stethoscopes and phonocardiographs to diagnose heart, lung, and intestinal conditions through sound. These tools are effective but require trained specialists and clinic visits.

Our research focuses on democratizing this capability through consumer-grade acoustic sensors and AI-driven analysis.

Future: Acoustic Spatial 3D Analysis

Next-generation acoustic cardiography will use spatial microphone arrays and 3D signal processing to localize and characterize sound sources within the body — providing richer diagnostic data than a single-point stethoscope can capture.

Solution: Preventive Healthcare Technology

By moving cardiac monitoring out of the clinic and into everyday life, we can detect problems earlier, reduce emergency hospitalizations, and lower the overall cost of care.

Continuous at-home monitoring
AI-powered anomaly detection
Socio-medical network for community health data
Early intervention before acute events occur

Problem 1: Leading cause of death

Heart Disease:

5.5M Americans,

22M worldwide,

annually

Cardiovascular disease remains the leading cause of death in the United States and worldwide. Despite decades of medical progress, the disease strikes both the young and the old, athletes and the sedentary alike. Access to timely, high-quality diagnostic care remains the single most important factor in survival outcomes.

Problem 2: Enormous cost of hospitalization

US Healthcare:

$2.5T in 2009,

$4.5T projected,

by 2019

Hospitalization for cardiac events is extraordinarily expensive. A single emergency cardiovascular procedure can cost tens of thousands of dollars, and post-event recovery and ongoing management add substantially to that figure. Preventive monitoring and early detection represent the most cost-effective path to reducing these expenses.

Problem 3: We will not be able to afford care

Affordability:

1/3 households,

>10% income,

on healthcare

As healthcare costs continue to rise faster than household income, an increasing share of the population will find quality cardiac care financially out of reach. The solution is not simply to spend more — it is to dramatically reduce the unit cost of diagnostic capability by leveraging consumer electronics technology and mass-market economies of scale.

Solution: Consumerize Healthcare Industry

Research:

Acoustic,

AI Analysis,

Social Network,

We are researching a non-invasive acoustic cardiography system that combines consumer-grade microphone arrays, real-time signal processing algorithms, and machine learning models trained on large phonocardiographic datasets.

Connected to a socio-medical network, the device will allow individuals to monitor their own cardiac health at home, share data with physicians, and benefit from community-level health trend analysis — bringing the diagnostic power of a hospital to the living room at consumer electronics cost.