A sensor association to acquire respiratory patterns: A pilot study
People with respiratory failure can be submitted to automatic synchronized transcutaneous functional electrical stimulation (TFES) with the person's respiration activity to improve respiratory function and airway clearing. Automatic detection of respiratory patterns for synchronizing TFES is a difficult task because different events such as cough and speaking can happen during stimuli application. The purpose of this study is to verify if a sensor association composed of a strain gage-based sensor, an airflow direction detector and a mechanomyography sensor can work together to facilitate the creation of an algorithm to differ all events of cough, normal breathing and speaking, in a complete system of automatic synchronized TFES. Two volunteers were asked to breath normally, cough and speak. The developed sensor association provided three different signals that were combined to create an algorithm. This algorithm can distinguish three different respiratory patterns: normal breathing, cough and speaking.