An artificial intelligence-enabled diagnosis system using a 3D pulse perception flexible pressure sensor array achieved an 80% recognition rate for detecting atrial fibrillation in hospitals.
Does an AI-enabled 3D pulse perception flexible pressure sensor array accurately diagnose atrial fibrillation?
A novel AI-enabled flexible pressure sensor array based on Traditional Chinese Medicine pulse theory can detect atrial fibrillation with an 80% recognition rate in a clinical setting.
Atrial fibrillation (AF) as one of the most common cardiovascular diseases has attracted great attention due to its high disability and mortality rate. Thus, a timely and effective recognition method for AF is of great importance for diagnosing and preventing it. Herein, we proposed a novel intelligent sensing and recognition system for AF which combined Traditional Chinese Medicine (TCM), flexible wearable electronic devices, and artificial intelligence. Experiment and simulation synergistically verified that the flexible pressure sensor arrays designed according to the TCM theory could synchronously obtain the 3D pulses at Cun, Guan, and Chi. Combined with a homemade signal acquisition system and the pulse signals labeled by doctors of cardiovascular diseases, the differences in the 3D pulse signals between ones with AF and without can be picked up clearly. Enabled the convolutional neural network (CNN) and the pulse database, the recognition model was formed with a recognition rate of up to 90%. As a proof of concept, the artificial intelligence-enabled novel atrial fibrillation diagnosis system has been used to detect patients with AF in hospitals, showing 80% recognition rate. This work provides a new strategy to precisely diagnose and remotely treat AF, as well as to accelerate the development of Modern Chinese Medicine treatment.
Cao et al. (Mon,) conducted a other in Atrial fibrillation. AI-enabled 3D pulse perception flexible pressure sensor array vs. Patients without atrial fibrillation / Doctor labels was evaluated on Recognition rate of atrial fibrillation. An artificial intelligence-enabled diagnosis system using a 3D pulse perception flexible pressure sensor array achieved an 80% recognition rate for detecting atrial fibrillation in hospitals.