BioSig Technologies, Inc. announced a new collaboration agreement in June with Reified Labs, a technical advisory service specializing in advanced artificial intelligence (AI). Together, BioSig and Reified will research and develop an AI medical device platform with the potential to transform the way doctors treat a range of common health problems from heart arrhythmias to peripheral nerve disorders like Amyotrophic Lateral Sclerosis (ALS) or nerve damage.
Reified Labs is headed by Dr. Alexander D. Wissner-Gross, one of the advisory firm’s founders and a Harvard- and MIT-trained computer scientist, physicist, investor and entrepreneur. Dr. Wissner-Gross has spent decades researching AI, machine learning, and its applications in healthcare. Through Reified Labs, he and his team of scientists and engineers have collaborated with dozens of biotechs and medtechs to develop cutting-edge diagnostic and treatment tools for healthcare providers.
In a statement on the collaboration, Dr. Wissner-Gross said that the potential applications of AI and digital signal processing “continues to present a promising opportunity for realizing key medical advances relating to disorders of the peripheral nervous system.”
Past collaborations with Reified have already been fruitful for BioSig, resulting in published research on AI-enhanced ECG mapping and multiple patent applications. In fact, back in September of 2020, an abstract titled Computational Reconstruction of Electrocardiogram Lead Placement, co-authored by Dr. Alexander D. Wissner-Gross of Reified LLC and Dr. Suraj Kapa of the Mayo Clinic, et al., was published illustrating that the transformative potential of artificial intelligence and machine learning in healthcare is vast.
To develop the platform, the companies will train the AI platform using electrocardiogram (ECG) ad intra-cardiac electrogram (IECG) data from BioSig’s patented PURE EP platform, which has already been used in over 3,000 procedures and featured in peer-reviewed clinical research.
PURE EP is a breakthrough technology that captures cardiac signals while eliminating environmental noise for clearer, sharper data, even for the subtler or more complex signals that are easy to miss with conventional ECG and iECG tech. This has potentially helped make cardiac ablations — a procedure used to treat irregular heartbeats — faster and more precise. It’s provided similar benefits to other procedures as well as become a helpful tool in leading labs, including Mayo Clinic, Cleveland Clinic, Texas Cardiac Arrhythmia Institute and Kansas City Heart Rhythm Institute.
By training the AI on this precision signaling data along with additional healthcare datasets, the team hopes to develop more advanced electrophysiology tech for healthcare providers. Once trained, the AI could help with real-time data analysis and improve every stage of the clinical workflow. The resulting tech could then be integrated into PURE EP to add even more functionality to the platform.