(0800) An Algorithmic Approach for Transcutaneous Electrical Nerve Stimulation in Dysphagia Therapy

Introduction: Dysphagia is a common neuromuscular disorder affecting approximately 1 in 25 individuals in the United States. A new therapeutic approach to treating swallowing disorders is the use of transcutaneous electrical nerve stimulation (TENS) therapy. Current therapeutic approaches lack the capability to assess patient muscle function and deliver adjusted stimulation without a dedicated operator. Herein, we present an algorithm to evaluate patient swallowing dysfunction and simulate individualized stimulation therapy.

Methods: A MATLAB program was created and connected to an EMG system through an Arduino UNO R3 microcontroller. The program was created to ensure real-time filtering and smoothing of EMG signals while simultaneously assessing the occurrence of high, medium, and low amplitude signals corresponding to a user’s ability to perform deglutition with the Suprahyoid muscles of the anterior neck. A simple push button would allow the user to switch modes between EMG sensing and simulated TENS delivery. Trials were conducted with one user performing full and partial swallows to assess the algorithm's capabilities.

Results: In a series of 10 trials, with one user performing five complete swallows and five partial swallows per trial, the algorithm was able to classify the events with an accuracy of 85.45% and a precision of 92.16%. Appropriate TENS waveforms were simulated according to the muscle strength detected in each trial.

Conclusions: This study introduces a novel algorithm for TENS therapy in dysphagia, employing EMG sensing for personalized stimulation. This concept has the capability to enhance treatment efficacy with autonomous adjustment, offering advancement in swallowing disorder therapies.