Abstract
The increasing number of hospitalizations due to the ongoing pandemic has brought medical devices to the forefront of clinical management. For instance, mechanical ventilation is managed via administration of analgesia in combination with neuromuscular blocking agents, and hence, Neuromuscular Blockade Monitoring (NBM) devices are often needed in intensive care units. However, NBM devices are costly and, consequently, not widely available across low- and middle-income countries. Here, we present a prototype of an acceleromyography-based NBM device that we built using low-cost, over-the-counter, open-source software and hardware. Our prototype includes an accelerometer to record finger movement in response to electrical stimulation delivered by a TENS unit, and is able to detect muscle twitches in real-time to calculate and display metrics of the Train-of-Four (ToF) protocol used in clinics. Experimental measurements in a healthy subject suggest that our prototype can be used to quantify clinical variables in an apparently reliable manner, and so this prototype shows great promise in being able to transition into higher developing stages.
Leo Medina
Principal Investigator
Leo teaches computer engineering courses at Usach, and his research interests are in the neural engineering and computational neuroscience fields. His work has contributed to understand how nerve fibers respond to electrical stimulation.