News

Weimer receives NSF CAREER Award

Weimer receives NSF CAREER Award to improve safety and efficacy of machine learning, AI systems

James Weimer, assistant professor of computer science and noted medical-device entrepreneur, has received a National Science Foundation CAREER Award to improve the safety and efficacy of systems that use advanced machine learning and artificial intelligence techniques. Learning-enabled medical cyber-physical systems (LE-MCPS) are smart medical systems that provide actionable feedback to caregivers. They use machine learning and AI to enhance their functionality and decision-making capabilities. One example is a stroke detection device in hospitals that processes…

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New Device Could Detect In-Hospital Strokes Faster

In an episode of WebMD’s YOUR HEALTH ON TECH with John Whyte, MD, Steven Messe, MD, discusses an innovation in stroke detection: a wristband that could alert hospital professionals for earlier intervention. TRANSCRIPT OF VIDEO JOHN WHYTEA person has a stroke nearly every 40 seconds in the United States. Despite recent advances in treatment, there are still significant challenges after suffering a stroke. That’s why diagnosis is so important. We tend to think about strokes…

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American Heart Association publishes Neuralert’s research regarding the use of our algorithm to detect stroke

Philadelphia, PA – Neuralert Technologies is pleased to announce our clinical research regarding the use of our algorithm to detect stroke was published in the Journal of the American Heart Association. The original research paper, “Derivation and Validation of an Algorithm to Detect Stroke Using Arm Accelerometry Data,” documents a multi-year, two-part prospective case-controlled study to validate that constant monitoring of arm movement data can be used to detect asymmetry indicative of stroke in hospitalized…

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Neuralert Technologies Stroke Detection Wristband Named to TIME’s List of the Best Inventions of 2022

Philadelphia, PA – Neuralert Technologies has announced that its lightweight, non-invasive wristband device that automates stroke detection and alerting, has been selected for TIME’s List of the Best Inventions of 2022. TIME revealed its annual list of the Best Inventions November 10, featuring 200 extraordinary innovations changing our lives today. One of the hallmark indicators of stroke is asymmetrical arm movement (e.g., weakness, neglect or less movement on one side). Neuralert’s stroke detection device can…

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Neuralert Technologies Stroke Detection Wristband Achieves Minimum Viable Product Status

Non-invasive stroke detection device hits major milestone Philadelphia, PA – Neuralert Technologies, makers of a lightweight, non-invasive wristband device that automates stroke detection and alerting, has announced that it has achieved Minimum Viable Product (MVP) status. To achieve this milestone, recently developed purpose-built wearable devices are now combined and working in conjunction with its patented algorithm and alerting software, completing the functional arc of stroke detection, data analysis, and medical staff alerting. One of the…

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FDA

FDA awards Neuralert Technologies Breakthrough Device designation

Philadelphia, PA – The Center for Devices and Radiological Health (CDRH) of the Food and Drug Administration (FDA) has granted the Neuralert Monitor designation as a Breakthrough Device. The Neuralert Technologies device is indicated for use to “detect the onset of asymmetric movement in hospitalized patients with medical conditions or procedures that are established risks for stroke and who have no baseline asymmetric upper extremity weakness.” Neuralert is a spin-out from the University of Pennsylvania,…

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Neuralert selected for University City Science Center Accelerator and Funding up to $50,000

Philadelphia, PA – Neuralert Technologies LLC (www.neuralerttechnologies.com) was one of eight startups from the U.S. and Canada selected for the latest iteration of University City Science Center Launch Lane Accelerator. This is the fifth cohort for Launch Lane (formerly the Digital Health Accelerator (DHA)). Launch Lane focuses on the equitable sourcing of companies, with the selection process utilizing a blind application to eliminate biases. Neuralert is a spin-out from the University of Pennsylvania, founded by…

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Neuralert receives $25,000 funding from Bucks Built Startup Fund

Philadelphia, PA – Neuralert Technologies LLC (www.neuralerttechnologies.com) was one of five recipients in the inaugural batch of the Bucks Built Accelerator Fund, a program administered by Startup Bucks and funded by the County of Bucks. Startup Bucks, a 501(c)3 organization founded in 2019, exists to help innovative companies start, grow, and scale in and beyond Bucks County by supporting founders and connecting the startup ecosystem across and beyond the County. Neuralert is a spin-out from…

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Neuralert awarded Ben Franklin PRIMA Grant

Philadelphia, PA – Neuralert Technologies LLC (www.neuralerttechnologies.com) has been awarded PRIMA (Philadelphia Regional Integrated Medicine Alliance) Grant funding by Ben Franklin Technology Partners of Southeastern PA. PRIMA links discovery, infrastructure, information and analysis systems and commercialization resources to enable startups, large companies, universities, hospitals, and other nonprofit organizations and regional life science stakeholders to collaborate to accelerate technology innovation and reduce barriers to commercialization. Neuralert is a spin-out from the University of Pennsylvania, founded by…

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Neuralert selected for NextFab RAPID Hardware Accelerator

Philadelphia, PA – Neuralert Technologies LLC (www.neuralerttechnologies.com) has been selected to participate in the Fall 2020 NextFab Studio LLC RAPID Hardware Accelerator program. NextFab is a pre-seed stage hardware-focused investor and a network of makerspaces in the Greater Philadelphia area. Neuralert is a spin-out from the University of Pennsylvania, founded by Steven Messe, MD (Department of Neurology) and James Weimer, PhD (Department of Computer and Information Science). The company focuses on early detection of stroke…

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