Artificial Intelligence | News | Insights | AiThority
[bsfp-cryptocurrency style=”widget-18″ align=”marquee” columns=”6″ coins=”selected” coins-count=”6″ coins-selected=”BTC,ETH,XRP,LTC,EOS,ADA,XLM,NEO,LTC,EOS,XEM,DASH,USDT,BNB,QTUM,XVG,ONT,ZEC,STEEM” currency=”USD” title=”Cryptocurrency Widget” show_title=”0″ icon=”” scheme=”light” bs-show-desktop=”1″ bs-show-tablet=”1″ bs-show-phone=”1″ custom-css-class=”” custom-id=”” css=”.vc_custom_1523079266073{margin-bottom: 0px !important;padding-top: 0px !important;padding-bottom: 0px !important;}”]

Biobeat’s Chest Patch and Remote Patient Monitoring Platform Demonstrate Capability as a Pre-Symptomatic and Real-Time Detection and Warning Tool for Patient Deterioration

Biobeat, a global leader in wearable remote patient monitoring solutions for the healthcare continuum,announced the publication of clinical data demonstrating that the company’s remote patient monitoring chest monitor may be utilized as a pre-symptomatic and real-time detection and warning tool for patients’ clinical deterioration, when combined with its AI-based ML tools. The article titled, “Developing a real-time detection tool and an early warning score using a continuous wearable multi-parameter monitor,” was published online on March 20, 2023, in the peer-reviewed Frontiers in Physiology.

Recommended AI: The Future of AI Is Here. Now Let’s Make It Ethical

“Current early warning score methods like the standard National Early Warning Score relies on infrequent data measurements collected from patients only once or twice a day and requires clinicians and medical staff to perform multiple tests to obtain vital signs,” commented Dr. Dean Nachman, M.D., cardiologist from the Hadassah Medical Center in Jerusalem and study investigator. “There is immense clinical utility in a novel early warning score algorithm like the Multi-Parameter Real Time Warning Score that is based on a wearable device that continuously monitors several health parameters. Utilizing MPRT-WS with a remote patient monitoring platform allows physicians to receive timely alerts of pre-symptomatic and real-time deterioration and may lead to earlier intervention of high-risk patients with both acute and chronic medical conditions.”

“Biobeat’s unique Multi-Parameter Real Time Warning Score was developed using both artificial intelligence and physicians’ inputs seeking more precise and frequent monitoring tools for predicting patient health deterioration. Our disposable chest monitor, combined with our remote patient monitoring platform, allowed for early detection of high-risk deterioration more than 40 hours before deterioration occurred,” added Prof. Arik Eisenkraft, Chief Medical Officer at Biobeat. “There is tremendous potential to shift the patient monitoring paradigm for patients at risk of deterioration, and we look forward to further investigating the capabilities of our devices, our remote patient monitoring platform, and MPRT-WS to provide clinicians with continuous insights into patient health.”

Related Posts
1 of 41,050

Recommended AI: AiThority Interview with Jessica Kipper, Senior Director, Software Product Management at Schneider Electric

The study analyzed more than 2 million datapoints collected from 521 individuals in total. 361 patients were monitored in general hospital wards with 160 healthy participants acting as control subjects. The current standard early warning score methodology, National Early Warning Score (NEWS), measures five metrics of systolic blood pressure, heart rate, respiratory rate, blood oxygen saturation, and temperature. Biobeat developed a novel multi-parameter real-time warning score (MPRT-WS) that measures nine vital signs including the five health parameters obtained from the NEWS, as well as four additional metrics of diastolic blood pressure, stroke volume, cardiac output, and systemic vascular resistance. MPRT-WS was compared to the NEWS for patients in three discrete levels of “Low,” “Medium,” and “High” risk of deterioration and showed a superior performance in flagging patients at high risk of deterioration with a 77% positive predictive value vs 20% with the NEWS.

Recommended AI: AiThority Interview with Pete Wurman, Director at Sony AI

[To share your insights with us, please write to sghosh@martechseries.com]

Comments are closed.