News | ECG Monitoring Services | May 16, 2019

Preventice Solutions Presents Real-World Performance Data on BodyGuardian Remote Monitoring System With AI

Wearable ECG monitoring technology uses deep learning algorithms to detect atrial fibrillation

Preventice Solutions Presents Real-World Performance Data on BodyGuardian Remote Monitoring System With AI

May 16, 2019 — Preventice Solutions presented clinical data validating its BodyGuardian Remote Monitoring System with the BeatLogic deep learning platform at Heart Rhythm 2019, the Heart Rhythm Society’s (HRS) 40th Annual Scientific Sessions, May 8-11 in San Francisco. This technology leverages machine learning and artificial intelligence (AI) for detection of atrial fibrillation (AF) and was validated using clinician adjudicated data.

The BodyGuardian Remote Monitoring System is designed to create a constant connection to monitor cardiovascular data in patients outside the clinic while they go about their daily activities. The data was presented by Hamid Ghanbari, M.D., MPH, FACC from University of Michigan in Ann Arbor, and Ben Teplitzky, Ph.D., and Mike McRoberts, from the Preventice data science team.

"One of the exciting advances in the diagnosis of AF is the use of machine learning techniques and deep learning technology because it can allow physicians to manage the massive amount of data that is collected," said Ghanbari, a cardiovascular electrophysiologist at the University of Michigan, where he treats patients who have arrhythmias. "Sensor technologies are creating so much data it's not feasible for physicians to be able to manage and review all of it. With accurate artificial intelligence to identify AF episodes, physicians can focus more on how their patients are feeling and the treatment approach they should take in each case. Artificial intelligence is freeing up the human potential with remote monitoring technologies."

Results from the study demonstrate how the BeatLogic deep learning platform is used to accurately detect the beginning and end of arrhythmias, ensuring accurate burden calculations and maximizing clinical value. The platform leverages multiple deep neural networks to detect AF episodes at rates that meet or exceed the best reported values within the literature. Perfect detection performance was achieved for AF episodes lasting more than one minute.

The study evaluated the AF detection performance of the Preventice BeatLogic platform using real-world clinician adjudicated data. The BeatLogic platform consists of multiple deep neural networks, which were trained using data from 10,946 BodyGuardian Heart patients. Performance was measured using real-world BodyGuardian Heart data from 512 patients that was annotated and then adjudicated by three board certified electrophysiologists. Specific results showed:

  • AF duration sensitivity (Se) and a positive predictive value (PPV) were 95.9 percent and 99.2 percent, respectively;
  • Episode detection Se and PPV were 96.7 percent; and
  • Episode detection Se and PPV increased to 100 percent for AF episodes with duration >1 minute.

Wearable patch electrocardiogram (ECG) monitoring quantifies AF burden using a combination of algorithms and trained technicians. New deep learning algorithms have improved the performance with respect to accurately detecting the presence of AF using algorithms. By leveraging multiple deep learning networks, the Preventice system is capable of accurately capturing the beginning and end of AF episodes, providing physicians with important clinical context for determining the appropriate treatment approach.

For more information: www.preventicesolutions.com

Related Content

An example of Viz.AI's pulmonary embolism AI application and mobile alert to the physician on-call. Viz.AI and Avicenna.AI Partner to Launch Artificial Intelligence Care Coordination for Pulmonary Embolism and Aortic Disease

An example of Viz.AI's pulmonary embolism AI application and mobile alert to the physician on-call.

News | Artificial Intelligence | July 21, 2021
July 21, 2021 — Artificial int...
Circle Cardiovascular Imaging Partners With DiA Imaging Analysis to Deliver AI-Based Cardiovascular Imaging Solutions
News | Artificial Intelligence | June 28, 2021
June 28, 2021 — Circle Cardiovascular Imaging Inc. and DiA Imaging Analysis Ltd.
Point of care ultrasound, POCUS, combined with artificial intelligence, can help improve echo image quality by inexperienced sonographers.

Getty Images

News | Artificial Intelligence | June 25, 2021
June 25, 2021 – COVID-19 changed everything in healthcare, and a benefit from this pandemic was a surge in innovation
GE is integrating artificial intelligence into most of its imaging and information technology software. AI can aid fast critical care decision making. Above left is the vScan Air wireless point-of-care ultrasound system. It integrates AI for immediate, automated assessment of a patient's ejection fraction, right.

GE is integrating artificial intelligence into most of its imaging and information technology software. AI can aid fast critical care decision making. Above left is the vScan Air wireless point-of-care ultrasound system. It integrates AI for immediate, automated assessment of a patient's ejection fraction, right.

Feature | Artificial Intelligence | June 10, 2021
The digital transformation of healthcare is underway, but it will advance further and faster if key stakeholders work
AI Med will present its Virtual Clinical Series: Imaging Built by Clinicians, for Clinicians, June 29-30, 2021.
News | Artificial Intelligence | June 09, 2021
June 9, 2021 — AI Med will present its...
The Eko digital stethoscope can record heart soubnds and use an artificial intelligence  (AI) analysis algorithm to detect heart murmurs. I new study in the JAHA showed it has comparable performance to that of an expert cardiologist. Eko Digital Stethoscope AI Analysis Algorithm Validated in JAHA article for Detecting Heart Murmurs

The Eko digital stethoscope can record heart soubnds and use an artificial intelligence  (AI) analysis algorithm to detect heart murmurs. I new study in the JAHA showed it has comparable performance to that of an expert cardiologist.

News | Artificial Intelligence | May 10, 2021
May 10, 2021 — Eko announced the peer-reviewed publication of a clinical study that found that the Eko...
Cloud AI software-as-a-service (SaaS) can help streamline workflows and increase throughput, enabling echocardiographers to better measure global longitudinal strain (GLS) more routinely without impacting productivity. This is an example of the Ultromics EchoGo Core artificial intelligence algorithm with fully automates GLS.

Cloud artificial intelligence (AI) software-as-a-service (SaaS) can help streamline workflows and increase throughput, enabling echocardiographers to better measure global longitudinal strain (GLS) more routinely without impacting productivity. This is an example of the Ultromics EchoGo Core artificial intelligence algorithm, which fully automates GLS. Learn more at www.ultromics.com.

Feature | Artificial Intelligence | March 16, 2021
Heart failure (HF) is a prevalent ye