Healthcare Industry News:  arrhythmia 

Devices Monitoring Cardiology FDA

 News Release - July 23, 2018

MEDICALgorithmics, Medi-Lynx Receive FDA 510(K) Clearance for PocketECG CRS Mobile Cardiac Rehabilitation System

New Device offers Data Critical to Effective Rehab Training

PLANO, Texas, July 23, 2018 -- (Healthcare Sales & Marketing Network) -- MEDICALgorithmics, S.A. (WSE: MDG) and U.S. subsidiary Medi-Lynx Cardiac Monitoring L.L.C., today announced that the U.S. Food and Drug Administration (FDA) has granted 510(k) clearance for the PocketECG Cardiac Rehabilitation System (CRS), a new mobile cardiac rehabilitation system designed to provide high-quality ECG monitoring and automated arrhythmia detection during rehabilitation training. The device is currently approved and marketed in the European Union and patented in the US (US Patent No. 9,846,764) for use in low and high-risk cardiac patients.

"We are thrilled to now introduce PocketECG CRS to patients and clinicians in the U.S., providing a valuable monitoring tool with the potential to improve the effectiveness of cardiac rehabilitation training," said Marek Dziubinski, PhD, CEO of MEDICALgorithmics. "PocketECG CRS was built on our PocketECG arrhythmia monitoring solution platform, and includes new software and enhancements specifically designed for use during all phases of the cardiac rehabilitation process – from early mobilization during hospitalization to post-discharge and ongoing maintenance."

PocketECG CRS is a smartphone-sized device that monitors a patient's heart rhythm and heart rate during rehabilitation exercises to safely guide the intensity and duration of workouts in real-time. The system transmits the full disclosure ECG signal classifying every heartbeat to automatically detect abnormalities and arrhythmia. A built-in accelerometer allows clinicians to analyze the impact of physical activity on heart rate. All data are streamed via mobile telephony network to a secure online clinician portal and to a cardiac monitoring center for constant monitoring, evaluation, and urgent notifications.

CR or medically supervised exercise training is highly recommended by the American Heart Association and shown to improve the health and recovery of patients with acute myocardial infarction or heart attack, chronic stable angina, coronary artery bypass grafting (CABG), percutaneous coronary intervention (PCI), cardiac valve surgery, stable, chronic heart failure, and cardiac transplantation. The American Association of Cardiovascular and Pulmonary Rehabilitation estimates that at least 3.8 million patients are eligible to receive CR.

About MEDICALgorithmics

MEDICALgorithmics S.A. (WSE: MDG) is a leader in cardiac monitoring and diagnostic solutions. Its PocketECG system enables remote monitoring of cardiac disorders, accurate arrhythmia diagnosis, and heart-rate monitoring around the world. Its PocketECG Cardiac Rehabilitation System (CRS) is cleared to monitor low and high-risk patients enrolled in a cardiac rehabilitation training program.

MEDICALgorithmics is developing several other products, including software to optimize repetitive tasks in hospitals, and algorithms for remote interpretation of multi-lead electrocardiography (ECG) signals. The Company also provides services in the field of information technology, biotechnology and scientific research. Based in Poland, MEDICALgorithmics operates in the United States through MEDICALGORITHMICS US HOLDING CORPORATION and its US subsidiary and service provider Medi-Lynx. For more information, visit www.medicalgorithmics.com.

About Medi-Lynx

Medi-Lynx Cardiac Monitoring LLC, is the US service provider and subsidiary of MEDICALgorithmics S.A., delivering best-in-class cardiac diagnostic solutions and service to enable the best possible care for patients. The Company's team of highly-trained technicians and customer care specialists work seamlessly to provide round-the-clock monitoring, reporting, training and support for cardiology practices and their patients. To learn more, visit www.medi-lynx.com.


Source: MEDICALgorithmics

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