UNSW researchers have developed AusculPatch, a micro-wearable sensor designed to replicate clinical cardiovascular and respiratory assessments for home use. Weighing 3.2 grams, the device addresses limitations in current remote monitoring by capturing detailed mechanical vibrations of the heart, lungs, and blood vessels. Published in Nature Communications, the proof-of-concept aims to enable early disease detection and reduce hospital burden. Developed by a team led by Scientia Associate Professor Hoang-Phuong Phan, the flexible patch adheres to the chest or peripheral arteries. It utilizes an ultra-thin silicon sensing element to detect low-frequency acoustic pressure waves generated by physiological processes. Unlike standard microphones, the sensor is directionally shielded to isolate body-borne vibrations, minimizing interference from ambient noise. The device captures respiration patterns, pulse waves, heart sounds, and blood flow data across extended periods, including during physical activity. Testing against clinical standards, including electrocardiograms, ultrasound, and digital stethoscopes, demonstrated strong signal agreement. The patch maintained data integrity in noisy environments and during movement. Researchers highlighted the device's ability to detect subtle anomalies, such as heart valve irregularities, which are often missed during brief clinical examinations. The continuous data stream supports integration with machine learning algorithms to identify patterns indicative of worsening conditions. Co-author Dr. Chi Cong Nguyen noted the potential for automated alerts to patients and clinicians before symptoms escalate. Beyond cardiorespiratory health, early experiments showed the sensor can detect vocal cord vibrations, enabling speech recognition and device control, potentially aiding individuals with speech or physical disabilities. The team, including clinicians and biomedical engineers from UNSW, plans to expand trials to approximately 200 patients with heart valve disease or implanted assist devices this year. Subsequent studies aim to enroll 1,000 participants to refine AI diagnostic tools. While medical-grade regulatory approval is estimated in four to five years, researchers anticipate consumer-focused wellness variants may reach the market sooner.