VivaLNK, a Campbell, CA-based connected healthcare solutions provider, teamed up with Emory University to provide its medical wearable ECG sensors for a study to evaluate autonomic function in predicting coronary artery disease (CAD) and its relationship to depression and long-term outcomes. The study builds upon previous work by Emory researchers titled Circadian Autonomic Inflexibility: A Marker of Ischemic Heart Disease, which associates lower heart rate variability (HRV) with subclinical myocardial ischemia.
The VivaLNK ECG patch contains a sensor and accelerometer to capture and generate multiple physiological data including ECG trace, heart rate, RR-interval, and 3-axis motion. About the size of a small bandage, the reusable and rechargeable patch weighs a mere 7.5 grams, and can be worn continuously for 72 hours at-a-time to capture and transmit data in real time, the company said in a press release.
“VivaLNK’s ECG patch is very small and comfortable to wear, which are important factors for clinical use and long-term ECG monitoring,” said Amit Shah, MD, Assistant Professor of Epidemiology at the Rollins School of Public Health at Emory University. “In addition, the software development kit makes it easy to use the patch for research and product development purposes.”
The researchers will use the device to remotely monitor patients who are undergoing coronary angiography, in order to measure autonomic function. Participants will be monitored using the ECG patch for continuous 72-hour periods in a clinical and ambulatory environment, which offers a more complete picture in a natural setting.
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The goal is to better understand the role of the autonomic nervous system in depression and coronary artery disease, and to develop better tools for clinical assessment.
VivaLNK provides connected healthcare solutions for wellness, patient care, and telemedicine. The company’s portfolio includes wearable medical grade devices and data analytics applications that continuously monitor the health and well-being of individuals.
