Patent ID: 8635053

Claim:
An automated method of identifying and classifying reflux episodes in data comprising a plurality of impedance versus time measurements obtained simultaneously at a plurality of different locations spaced apart from each other along a length of an esophagus between the pharynx and the stomach collected and stored in a collection device, wherein the data is indicative of impedance versus time waveforms, including proximal waveforms from locations closest to the pharynx, distal waveforms from locations closest to the stomach, and mid-channel waveforms between the proximal waveforms and the distal waveforms, said method comprising: providing the impedance versus time data to a data analysis device, which performs wavelet transformation to the impedance versus time waveforms to obtain smoothed curves of the impedance versus time waveforms and detail curves showing local positive and negative maxima peaks corresponding to positive and negative slopes in the smoothed impedance versus time waveforms; determining with the data analysis device whether the smoothed impedance versus time waveforms exhibit either normal baseline impedance levels that are characteristic of conductivity of healthy esophageal tissue or low baseline impedance levels that are characteristic of conductivity of diseased esophageal tissue; determining with the data analysis device whether change in impedance in the smoothed impedance versus time waveforms during gastrointestinal tract events are either: (i) large as indicated by the ratio of the mean distribution of minimum impedance to baseline impedance levels being not greater than a value; or (ii) low as indicated by the ratio of the mean distribution of minimum impedance to baseline impedance levels being greater than the value; if it is determined by the data analysis device that the smoothed impedance versus time waveforms exhibit low baseline levels and that the change in impedance during gastrointestinal tract events are low, then applying an adaptive filter with the data analysis device to at least one of the smoothed impedance versus time waveforms, wherein a primary input for the adaptive filter comprises a delayed sequence of the said at least one smoothed impedance versus time waveform, and determining a candidate episode by transition of impedance level in the adaptive filter output to a gastric contents impedance level; and if it is determined by the data analysis device that either the smoothed impedance versus time waveforms do not exhibit low baseline levels or the change in impedance during gastrointestinal tract events are not low, then determining a candidate episode by transition of impedance level in the smoothed waveforms to a gastric contents impedance level.