A B s m A mOne way to autaMtically detect periods of sleep or hypcpnea in a respiratory airflcw reocadirg is to first segment the airflcrw waveform i n t o individul breaths.This is difficult if the waveform has a high degree of artifact or a wide range of breath magnitudes.A nonparmnetric statistic applied to a digitized airflw waveform is used to create twu new "trend" wavf2fom whose properties make it easier to analyze t+in the original t i m e damin waveform. certavl wlell defined points a l m g the trend wavefornrs cOrreSpOnd to the beginning and end of individual breaths within the airflcrw wavefonn. lNlRouJcrIoN For a sleeping individual, intends of apnea and hypqmea can be identified by recozding respiratory airflaw at the level of the nose and mouth. 'Ihis can e done with properly positioned MsdL/oral therrmstors [l]. Manual analysis of this type of recording is time and subject to human error so an autcanatic techuque is preferred.To autclmaticaZly rf?cosnize apnea and h m , a computer would fust segment the ~gitized respiratory airflcrw waveform into its individual constituent bmths. Individual breaths are often difficult to recognize because the depth of respiration varies over a wide range and the respiratory waveform is often artifactudl [2]. prwiaus breath detection techniques have varied in caplexity f m s-le single-threshold magnitude ccpnparisons to caplex heuristic @-detecting algorithm using Ntiple arbitrary magnitude and duration thresholds [2,3]. Ihe method described in this paper uses a nonparametric statistic to identify change-points along the respiratory waveform that mrreqmn3 to shifts between inspiration and expiration thereby segmenting the airflm waveform into discrete breaths. MGIHOD Given a seqence of respiratozy airflm q l e s yi, i=1, 2, -* -changepoints c a w at the transitions b e t w e e n '~ and trends. TO detect these trends, the waveform samples are o m z e d into N-tuple~ 'Ihe N-tuple i s divided %half (assumbq N is an even mmbr). If the 3 N-tuple represents no trend (the null hypothesis, Q) then where m = 1+(N/2) and P(Y1 = Ym) = 0 If T is a rardan variable equal to the m m b r of times y is less than ym then T has a bincmial distrdion b(n,1/2) where n is the nunber of untied pairs (ylrym). Given this, dcrcJlward and upward *values equal to 1 minus the probability of camut a type I1 error 141 can be calculated for the j@-tuple as whexe (7. NI-1 1 for YI * Y m 1 = 1 'k+j, ((I-I)N)+b+j with '8.m = 1 0 for y l = y, k-0 Z (A Rotionol Number) L 1/2 s.t. 1 L N.2 ( INT[N/2] and where nI I Z As Defined Above Equations (1) and (2) are generalized f o m of 0330--1EEE ENGINEERING IN MEDICINE L BIOLOGY SOCIETY llTH ANNUAL INTERNATIONAL CONFERENCE

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