title: Dynamic model inversion techniques for breath-by-breath measurement of carbon dioxide from low bandwidth sensors.
abstract: Respiratory CO(2) measurement (capnography) is an important diagnosis tool that lacks inexpensive and wearable sensors. This paper develops techniques to enable use of inexpensive but slow CO(2) sensors for breath-by-breath tracking of CO(2) concentration. This is achieved by mathematically modeling the dynamic response and using model-inversion techniques to predict input CO(2) concentration from the slow-varying output. Experiments are designed to identify model-dynamics and extract relevant model-parameters for a solidstate room monitoring CO(2) sensor. A second-order model that accounts for flow through the sensor's filter and casing is found to be accurate in describing the sensor's slow response. The resulting estimate is compared with a standard-of-care respiratory CO(2) analyzer and shown to effectively track variation in breath-by-breath CO(2) concentration. This methodology is potentially useful for measuring fast-varying inputs to any slow sensor.
authors: University of Minnesota, Twin Cities, MN 55455, USA. shyams@me.umn.edu
authors: Shyam
authors: S
authors: Sivaramakrishnan
authors: Rajesh
authors: R
authors: Rajamani
authors: Bruce D
authors: BD
authors: Johnson
mesh_terms: D000465:Algorithms; D001944:Breath Tests / Q000379:methods; D019296:Capnography / Q000295:instrumentation* / Q000379:methods*; D002245:Carbon Dioxide / Q000737:chemistry*; D004563:Electrochemistry / Q000379:methods; D004867:Equipment Design; D006801:Humans; D015233:Models, Statistical; D008962:Models, Theoretical; D008991:Monitoring, Physiologic / Q000379:methods; D015203:Reproducibility of Results; D012815:Signal Processing, Computer-Assisted; D013997:Time Factors
chemical_list: D002245:Carbon Dioxide