Cigarette Smoke Exposure Computation using Bioimpedance Sensor

Understanding the smoking habit and the amount of smoke exposure of a smoker is crucial for smoking intervention. The parameters extracted from breathing patterns, such as puff duration, inhale-exhale duration, etc. can play an important role in defining the amount of smoke exposure. This paper is the first to assess the suitability of a bio-impedance sensor for measurement of the smoke exposure metrics from breathing. The Personal Automatic Cigarette Tracker version 2.0 (PACT 2.0) was used in this study. The bio-impedance sensor was placed at the thoracic level with the help of an instrumented T-shirt. The bio-impedance signal during the smoking event was observed and the Respiratory Smoke Exposure Measurement (RSEM) algorithm was used to compute the smoke exposure metrics. The metrics computed by the RSEM algorithm were compared statistically with gold standard obtained from video annotations. The paired t-test for puff duration and inhale-exhale duration obtained from bio-impedance signal and video annotations indicated that the values were statistically similar. The results of this study indicate the potential use of bio-impedance sensor for measurement of smoke exposure metrics.