Senzime announced a new clinical study with the TetraGraph system published in the British Journal of Anesthesia Open (BJA Open). The study is the first of its kind and validates TetraGraph system waveforms using an AI-based neural network with an accuracy of more than 99%. The new study was performed by a research team at the University of Miami using clinical data from Mayo Clinic and the University of Debrecen to develop and validate an artificial intelligence (AI)-based convolutional neural network (CNN) that correctly identifies valid compound muscle action potentials (CMAPs) from the TetraGraph quantitative neuromuscular monitoring system.

The study used Senzime's TetraGraph system to demonstrate the feasibility of using AI to separate valid cMAPs from artifact. The CNN algorithm showed an accuracy exceeding 99.5% in distinguishing the TetraGraph's valid CMAPs from artifact. The study Validation of a convolutional neural network that reliably identifies electromyographic compound motor action potentials following train-of-four stimulation: an algorithm development experimental study has been published in British Journal of Anesthesia Open.

A related abstract was selected as one of the 12 Best Basic Science abstracts presented at the 2023 Annual Meeting of the American Society of Anesthesiologists in San Francisco, USA.