title: Monitoring respiratory mechanics during mechanical ventilation: where do the signals come from?
abstract: Graphical patient data have become essential to the understanding and management of ventilator-dependent patients. These electronically generated data often reveal clues to subtle complications that, if corrected, could lead to improved patient-ventilator harmony. The apparent precision of the waveforms and the 3- or 4-place display of numeric data imply high accuracy. Laboratory devices and equipment, with their required certification, generally exhibit accuracies of approximately 2% for flow and significantly less than 1% for pressure. But the cost constraints placed on hospital-grade medical equipment dictate the use of commercial sensors-transducers, which means that pressure measurements will range between 3% and 5% of reading, and flow measurements will range between 6% and 10% (+/- 3 standard deviations of the mean). Other direct and indirect influences, such as temperature, humidity, absolute pressure, system pressure, type of gas, contamination, and myriad additional effects further interfere with the transformation of the variable of interest into an electrically equivalent signal. The abundance of viewable information pertinent to the management of the ventilated patient can be traced to the availability of the many types of transducers combined with microprocessor electronics. The process of capturing a variable of interest (sensing and signal transduction), converting it to a digitized electronic signal (analog-to-digital-conversion), operating on that signal (such as for control of the breathing algorithm and checking for violation of alarm thresholds), and finally converting it back to an analog signal that appears on a monitor generally receives scant appreciation. The process, however, lies at the core of data management in modern ICU ventilators.
authors.affiliation: Tyco Healthcare, Carlsbad, California 92008, USA. warren.sanborn@tycohealthcare.com
authors.forename: Warren G
authors.initials: WG
authors.lastname: Sanborn
mesh_terms: D000465:Algorithms; D006801:Humans; D008991:Monitoring, Physiologic / Q000295:instrumentation* / Q000379:methods; D012121:Respiration, Artificial / Q000295:instrumentation* / Q000379:methods; D015656:Respiratory Mechanics; D012815:Signal Processing, Computer-Assisted; D014160:Transducers, Pressure / Q000592:standards; D012122:Ventilators, Mechanical / Q000592:standards