Patent Abstract:
A method and apparatus for characterizing gastrointestinal sounds includes a microphone array to be positioned on a body for producing gastrointestinal sound signals. The signals are digitized and their spectra and duration is determined by a processor. A characterization as to the state of the gastrointestinal tract is made on the basis of the spectra and duration of the sound or event.

Full Description:
CROSS REFERENCE TO RELATED APPLICATIONS 
     This is a continuation of prior application Ser. No. 08/970,026, filed on Nov. 13, 1997, now abandoned, which is a continuation in-part of Ser. No. 08/717,184, filed on Sep. 20, 1996, now U.S. Pat. No. 6,056,703, which is a continuation-in-part of 08/649,081, filed on May 17, 1996, now abandoned, which is a continuation-in-part of 08/627,309, filed on Apr. 3, 1996, now abandoned. 
    
    
     BACKGROUND OF THE INVENTION 
     The invention relates in general to a method and apparatus for characterizing gastrointestinal sounds and in particular to a method and apparatus employing a microphone array attachable to a patient&#39;s body for collecting sounds from multiple sources in the body and a computer system for receiving digitized gastrointestinal sound signals and determining the spectra and duration of the sounds and characterizing states of the gastrointestinal tract on the basis of the spectrum and duration. 
     It has been known in the past to employ electronic analysis of sounds from the gastrointestinal tract as an adjunct to the physician auscultating the gastrointestinal tract in an attempt to determine quickly and with a minimum of diagnostic equipment the condition of the patient. In the past, for instance, as disclosed in U.S. Pat. No. 5,301,679, a method and system was provided for providing diagnostic information for various diseases including diseases of the gastrointestinal tract by capturing body sounds in a microphone placed on the body surface or inserted orally or rectally into the gastrointestinal tract. The spectrum analyzer used a real time audio one-third octave technique using a plurality of analog filters and a peak detector provide a log calculation of envelope amplitudes. Other systems also used microphones sensitive to specific frequency ranges and are exemplified by Dalle, et al. “Computer Analysis In Bowel Sounds,”  Computers in Biology and Medicine  February 1975 4(3-4) pp. 247-254; Sugrue et al., “Computerized Phonoenterography: The Clinical Investigation of the New System,” Journal of  Clinical Gastroenterology , Vol. 18, No. 2, 1994, pp. 139-144; Poynard, et al., “Qu&#39;attendre des systemes experts pour le diagnostic des troubles fonctionnes intestinaux,”  Gastroenterology Clinical Biology , 1990, pp. 45C-48C. Also of interest are U.S. Pat. Nos. 1,165,417; 5,010,889; 4,991,581; 4,792,145. Unfortunately, none of the systems relate to using specific morphological filtering and event characterization of the type which might be able to identify ileus or small bowel obstruction or the like. The prior systems seem to have suffered from the inability to cope with relatively irregular sounds and irregular signals and to pick events of detail from the signal. Many of the systems used averaging techniques on the raw signal, which would tend to obscure the event of interest in noise or other unwanted portions of the signal and thus actually work against the diagnostician attempting to characterize genuine gastrointestinal sounds as opposed to other sounds coming form the body. Thus, it would appear that despite the use of sophisticated spectral techniques and the like the prior art, having been unable to identify events, appeared to operate on relatively noisy data from which it would be difficult to extract meaningful conclusions. Accordingly, what is needed is a system which can quickly and easily identify such conditions. 
     SUMMARY OF THE INVENTION 
     The invention is directed to a method and apparatus including a microphone array including three microphones fixed on a mount for precise positioning with respect to key location of the anatomy of the patient with a fourth free microphone which may be placed adjacent to the sternum of the patient for picking up breathing, cardiac and environmental sounds and the like which are to be subtracted from the gastrointestinal sounds and are treated as noise. The microphones feed a sound equalizing system for selection of certain sound frequency ranges which in turn feeds analog sound signals representative of gastrointestinal sounds to a tape recorder. The tape recorder is connectable to a computer which includes an analog to digital converter. Digitized multiple gastrointestinal sounds may then be processed by a computer in accordance with morphological filtering algorithms which characterize both the spectra and the duration of the sounds emanating from the gastrointestinal tract. In addition, the computer can subtract out components of sounds related to the background noise from the surrounding room or from the breathing which is picked up by a free microphone. An output indication may be provided to the physician or other health care worker through a printer or a video display screen which provides an indication as to the type of sound and a characterization in some cases as to the condition of the patient such as ileus and the like. 
     The present system is particularly characterized by the fact that the initial processing of the digitized audio signals relates to selecting gastrointestinal events of interest from extended noisy audio signals. One way in which this has been done in the present application is to use an amplitude thresholding system to look for events of interest and then to focus additional processing on those events. This approach does not appear to have been taken in the previous systems and may have reduced their ability to extract meaningful data from the relatively noisy environments in which they operate. 
     Approximately ten percent of the U.S. population has gastrointestinal symptoms each year for which physician consultation is sought. The symptoms include abdominal pain, distension, diarrhea and vomiting. The causes vary from benign conditions such as irritable bowel syndrome or self-limiting viral illness to life-threatening bowel blockage. Current diagnostic methods for determining what is occurring include a host of expensive and invasive tests, including such techniques as CT scans and colonoscopy. 
     The instant invention provides utility for diagnostic data for conditions involving small bowel obstruction, delayed gastric emptying, inflammatory disorders and motility disorders. For instance, small bowel obstruction, which includes various types of mechanical bowel obstruction, is a common reason for emergency surgical admission to the hospital and results in over 9,000 deaths each year. Signs and symptoms of small bowel obstruction may mimic benign viral or other illnesses. Many patients, especially medically complex subjects also having cancer, diabetes, previous gastrointestinal surgery and sepsis may present diagnostic dilemma of small bowel obstruction versus non-mechanical pseudo-obstruction or ileus. It is critical to distinguish these patients promptly since small bowel obstruction patients typically require surgical intervention while ileus patients are usually managed without surgery. Delay in proper diagnosis may lead to improper and dangerous surgical intervention in the non-obstructive patient or, conversely, may lead to complications or death in those with bowel obstruction. The instant invention provides a rapid, safe, accurate, low cost, lightweight and comfortable apparatus for assisting in small bowel diagnosis. 
     In addition, the apparatus can determine conditions involving delayed emptying of gastric contents, a condition called gastroparesis, to which millions are subject. Symptoms of gastroparesis include bloating, heartburn, belching, decreased appetite and upper abdominal pain. The preferred diagnosis method is scintigraphy scanning, whereby a liquid or solid meal is labeled with a gamma ray emitting radioisotope, usually radioactive technetium, and counts are obtained using a gamma camera over a period of 60 to 120 minutes. The test is expensive and requires special scheduling. 
     Inflammatory disorders are the most common of all gastrointestinal disorders and include peptic ulcer disease, viral, bacterial and other infections and the inflammatory bowels disease such as Crohn&#39;s disease and ulcerative colitis. Inflammatory changes of the gastrointestinal tract lead to altered mechanical properties including changes in acoustic resonance and reflective characteristics. The instant invention, through the use of its sophisticated signal processing, provides pattern recognition techniques for examining patients for inflammatory disorders. 
     Motility disorders are a diverse set of less well-defined conditions that pertain to derangement in the control and function of the propulsive or peristaltic activity of the gastrointestinal tract. Gastroparesis is one example of this type of disorder. Again, the instant invention can aid in determining when motility disorders are present. 
     It is a principal aspect of the present invention to provide a gastrointestinal sound processing system which can characterize individual gastrointestinal events on diagnostic basis. 
     It is another aspect of the present invention for providing a gastrointestinal sound characterization system which intercepts sounds from multiple locations in the human body for diagnostic purposes. 
     Other aspects of the present invention will be apparent to one of ordinary skill in the art upon a perusal of the following specification and claims in light of the accompanying drawings. 
    
    
     BRIEF DESCRIPTION OF THE DRAWINGS 
     FIG. 1 is a block diagram of an apparatus embodying the present invention for gastrointestinal sound processing; 
     FIG. 2 is a block diagram of a computer and associated hardware shown in FIG. 1; 
     FIG. 3 is a perspective view of a portion of a human torso showing the location of multiple microphones on the torso for picking up gastrointestinal sounds and background noise; 
     FIG. 4 is an elevational view showing portions of the interior organs of the body in dotted form showing the arrangement of the microphone array on the body; 
     FIGS. 5 and 6 are upright and upside down perspective views of one of the microphones of the array; 
     FIG. 7 is a flow diagram of a system for collecting and processing gastrointestinal sounds; 
     FIG. 8 is a flow diagram of a core process for processing gastrointestinal sounds; 
     FIG. 9 is a flow diagram of a telemedicine version of the system; 
     FIG. 10 is a flow diagram of a process for collecting ambulatory gastrointestinal sounds and storing them; 
     FIG. 11 is a flow diagram similar to FIG. 10 showing use of a multiple channel analog tape recorder in ambulatory settings; 
     FIG. 12 is a flow diagram related to finding acoustic events and their features; 
     FIG. 13 is a flow diagram related to localization and characterization of gastrointestinal acoustic events; 
     FIGS. 14 a  and  14   b  are flow diagrams for calculating a gastrointestinal sound envelope; 
     FIG. 15 is a flow diagram for calculating structuring elements; 
     FIG. 16 is a flow diagram for calculating filter coefficients; 
     FIG. 17 is a flow diagram for calculating frequency domain Hilbert filter coefficients; 
     FIG. 18 is a flow diagram for calculating frequency domain band pass filter coefficients; 
     FIG. 19 is a flow diagram for an envelope smoothing process using dilation; 
     FIG. 20 is a flow diagram for determining the amplitude threshold; 
     FIG. 21 is a flow diagram for producing a histogram of the envelope; 
     FIG. 22 is a flow diagram for calculating a smoothed average slope of the histogram; 
     FIG. 23 is a flow diagram for finding gastrointestinal sound events in each channel; 
     FIG. 24 is a flow diagram for pasting neighboring signals on the same channel into a single event; 
     FIG. 25 is a flow diagram for finding related events in other channels; 
     FIG. 26 is a flow diagram for determining an interchannel event delay threshold; 
     FIG. 27 is a flow diagram for finding nearby events and saving their time and amplitude; 
     FIG. 28 is a flow diagram of a checking process for determining whether a nearest event is part of a related gastrointestinal event; 
     FIG. 29 is a flow diagram for checking gastrointestinal event overlap on other channels; 
     FIG. 30 is a flow diagram for localizing each of the gastrointestinal events; 
     FIG. 31 is a flow diagram for defining sound regions of origin; 
     FIG. 32 is a flow diagram for determining a sound region of origin; 
     FIG. 33 is a flow diagram for determining the average transabdominal speed of sound and abdominal damping characteristics; 
     FIG. 34 is a flow diagram for determining a location of a sound source; 
     FIG. 35 is a flow diagram for combining event features; 
     FIG. 36 is a flow diagram for recognizing gastrointestinal events; 
     FIG. 37 is a flow diagram for recognizing environmental events of the type picked up by the free microphone; 
     FIG. 38 is a flow diagram for recognizing signals representative of vascular events; 
     FIG. 39 is a pattern recognition flow diagram; 
     FIG. 40 is a flow diagram to test whether a subject is a control, has small bowel obstruction or ileus; and 
     FIG. 41 is a flow diagram for nearest neighbor classification; 
     FIG. 42 is a flow chart of a method of adaptively filtering a channel signal; 
     FIG. 43 is a flow chart of specific channel filtering steps of the process shown in FIG. 42; 
     FIG. 44 is a plot of the number of events versus frequency versus duration from the epigastraeum of a normal subject; 
     FIG. 45 is a plot of the lower quadrant of a subject with ileus; 
     FIG. 46 is a plot of a subject with small bowel obstruction; 
     FIG. 47 is a plot from the lower right quadrant of a normal subject; 
     FIG. 48 is a plot from the lower left quadrant of a normal subject; 
     FIG. 49 is a spectrogram of four events in a normal subject; and 
     FIG. 50 is an event in a subject with small bowel obstruction. 
    
    
     DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS 
     Referring now to the drawings and especially to FIG. 1, an apparatus for characterizing gastrointestinal sound is generally shown therein and identified by numeral  10 . The apparatus  10  includes a microphone array  12  having a free microphone  14 , an array microphone  16 , a second array microphone  18  and a third array microphone  20  coupled to filter and amplifier  22  which feeds multiple analog signals representative of the gastrointestinal sounds over leads  24  to a Tascam 2000 multichannel tape recorder  26  where the analog signals may be recorded in analog format. The sound signals may then be transferred over lead  28  to a computer  30  for analysis. Following analysis output results may be displayed on a video display terminal  32  or output through a printer  34 . 
     Referring now to FIG. 2, a block diagram of the computer  30  is shown therein. The computer  30  receives the analog gastrointestinal sound signals on a line  23  at an analog to digital converter. The gastrointestinal signals are digitized and fed over lines  40  to a system bus  42  of the computer  30 . The computer  30  includes a disk controller  44  having connected to it a hard disk drive  46  and a floppy disk drive  48 . The hard disk drive  46  stores a program as represented by the flow charts of FIGS. 7 through 37 inclusive. Upon receipt of sound signals from a patient the software routines are transferred from the hard disk drive  46  through the disk controller  44  to the system bus  42  and are loaded into random access memory  50  connected to the system bus for execution by a microprocessor  52 . Portions of the code and data of the software may be stored from time to time in a cache memory associated with the microprocessor  52 . Read only memory  54  contains operating system information and outputs may be provided from the system bus by a video controller  56  to a video output line  31  connected to the display  32 . Likewise, outputs may be connected through an input/output module, having parallel and serial ports  58 , through a line  33 . The microphone array  12 , as may best be seen in FIGS. 3 and 4, microphones  14  through  20  placed on a torso  70  of a human being with the free microphone  14  being placed near the sternum and the array microphones  15  through  20  attached slidingly to array arms  72 ,  74  and  76 . The sliding adjustable microphone harness is necessary to accommodate subjects of a wide variety of sizes. The microphones respectively are located to pick up multiple gastrointestinal sound sources from the human torso to provide analog signals to the computer  30 . 
     The computer  30 , by execution of the routines shown in FIGS. 7 through 43, inclusive, determines the spectra and the duration of the individual gastrointestinal events and provides an output indication thereof in response to the signal and the variables input as set forth in the tables below. The use of the multiple microphone array in combination with the routines set forth in the flow charts which are executed by computer allows quick and easy analysis of the gastrointestinal sounds for the determination of conditions such as small bowel obstruction, ileus and the like. 
     Referring now to the drawings and especially to FIG. 7, an overall flow diagram for gastrointestinal sound capture is shown herein wherein in a first step a patient  200  is fitted with the microphone array in a step  202  following which sounds captured by the microphone array  202  are fed to an analog amplifier and filter. Prior to analyzing captured sound the variable set found in Table 2 are in initialized to proper values. Table 2 provides optimized values of these settings for the current hardware and system. 
     
       
         
               
             
               
               
               
             
           
               
                 TABLE 1 
               
               
                   
               
               
                 ABBREVIATIONS 
               
               
                   
               
             
             
               
                   
               
             
          
           
               
                   
                 AMP S   
                 Amplitude of structuring elements 
               
               
                   
                 BNDFLT 
                 Name of band-pass filter array of 
               
               
                   
                   
                 coefficients 
               
               
                   
                 chr_mx 
                 Maximum coherence value 
               
               
                   
                 cntr 
                 Dummy counter variable 
               
               
                   
                 d_c 
                 Duration of current event 
               
               
                   
                 dd1, dd2, dd3 
                 Duration of detected events in 
               
               
                   
                   
                 other channels 
               
               
                   
                 DIST_CLASS 
                 Average distance between subjects 
               
               
                   
                   
                 in the same class excluding current 
               
               
                   
                   
                 subject 
               
               
                   
                 DIST_SUBJ 
                 Average distance between current 
               
               
                   
                   
                 subject and other members in the 
               
               
                   
                   
                 same class 
               
               
                   
                 dly1, dly2, dly3 
                 Interchannel delay, in seconds 
               
               
                   
                 DT_LNS 
                 length of data processing array 
               
               
                   
                 DT_RD 
                 Number of data points to read from 
               
               
                   
                   
                 file 
               
               
                   
                 dn 
                 Number of elements 
               
               
                   
                 DT_PTS 
                 Number of data points in file 
               
               
                   
                 DTRD 
                 Number of data points to read 
               
               
                   
                 dr1, dr2, dr3 
                 Duration of related events in other 
               
               
                   
                   
                 channels 
               
               
                   
                 dur 
                 Event duration 
               
               
                   
                 DUR_MED 
                 Median duration for all events 
               
               
                   
                 ed, ed1, ed2, ed3 
                 End times of detected events 
               
               
                   
                 ENPARR 
                 Name of envelop array 
               
               
                   
                 ENPMAX 
                 Envelope value at the envelop 
               
               
                   
                   
                 histogram maximum 
               
               
                   
                 ENPPOS 
                 Envelop value when histogram slope 
               
               
                   
                   
                 first becomes positive 
               
               
                   
                 env_val 
                 A point of the digital envelope 
               
               
                   
                   
                 data 
               
               
                   
                 er, er1, er2, er3 
                 End times of the related event 
               
               
                   
                 ev_ch 
                 Channel of current event 
               
               
                   
                 EV_RATE 
                 The average event rate during the 
               
               
                   
                   
                 recording time 
               
               
                   
                 EV_TSR 
                 Event time series 
               
               
                   
                 f_dom 
                 Dominant frequency of an event 
               
               
                   
                 F_DOM_MED 
                 The median dominant frequency of 
               
               
                   
                   
                 all events 
               
               
                   
                 FH S   
                 Value of the higher frequency (for 
               
               
                   
                   
                 low-pass filter) 
               
               
                   
                 FL S   
                 Value of the lower frequency (for 
               
               
                   
                   
                 high-pass filter) 
               
               
                   
                 FL_SZ 
                 Data file size in bytes 
               
               
                   
                 FO S   
                 Filter order 
               
               
                   
                 FS S   
                 Sampling frequency 
               
               
                   
                 G 
                 The filtered signal 
               
               
                   
                 H 
                 Filter coefficients 
               
               
                   
                 HLBFLT 
                 Name of Hilbert filter array of 
               
               
                   
                   
                 coefficients 
               
               
                   
                 HMIN_D 
                 Delay value corresponding to the 
               
               
                   
                   
                 minimum in the histogram of 
               
               
                   
                   
                 interchannel delay 
               
               
                   
                 HSTENP 
                 Name of envelope histogram array 
               
               
                   
                 HSTMAX 
                 Maximum value of histogram 
               
               
                   
                 HSTSLOP 
                 Name of histogram slope array 
               
               
                   
                 i 
                 Dummy variable 
               
               
                   
                 ich_dly 
                 Interchannel event delay 
               
               
                   
                 ICH_TH 
                 Interchannel event delay threshold 
               
               
                   
                 i_dur 
                 Index of event duration 
               
               
                   
                 i_n 
                 Index for the noise data array 
               
               
                   
                 i_p 
                 Index for the primary data array 
               
               
                   
                 i_strt 
                 Index of event start (equals the 
               
               
                   
                   
                 start of event start in number of 
               
               
                   
                   
                 points) 
               
               
                   
                 j 
                 The square root of (-1) 
               
               
                   
                 K S   
                 Number of nearest neighbors 
               
               
                   
                 mxlc 
                 Location of the maximum 
               
               
                   
                 mxlc_r 
                 Location of the maximum of 
               
               
                   
                   
                 correlation 
               
               
                   
                 mxlc_h 
                 Location of the maximum of 
               
               
                   
                   
                 coherence 
               
               
                   
                 MU S   
                 The adaptation parameter 
               
               
                   
                 N_EV 
                 Total number of events in the whole 
               
               
                   
                   
                 the recording 
               
               
                   
                 nf 
                 The filter noise data element 
               
               
                   
                 N_MIC 
                 Number of microphones 
               
               
                   
                 n_rt 
                 Number of related events 
               
               
                   
                 nxcr_mx 
                 Maximum of normalized cross 
               
               
                   
                   
                 correlation 
               
               
                   
                 OVLAP S   
                 Number of overlap points 
               
               
                   
                 P 
                 Primary input channel data array 
               
               
                   
                 REC_RUR 
                 The recording duration 
               
               
                   
                 rt_strt 
                 Related event start time, in 
               
               
                   
                   
                 seconds 
               
               
                   
                 rt_pp 
                 Peak to peak amplitude of related 
               
               
                   
                   
                 event, in volts 
               
               
                   
                 sdev 
                 Deviation of event spectral 
               
               
                   
                   
                 morphology from that of known 
               
               
                   
                   
                 vascular sounds 
               
               
                   
                 SMOARR 
                 Name of smoothed envelop array 
               
               
                   
                 spcg 
                 Event spacing 
               
               
                   
                 SPCG_TH S   
                 Event spacing threshold for pasting 
               
               
                   
                   
                 events 
               
               
                   
                 STR_ELE 
                 Name of structuring elements array 
               
               
                   
                 SUBJ_CLASS_RATIO 
                 Ratio of subject/class distance 
               
               
                   
                 SUPARR 
                 Name of supplementary array 
               
               
                   
                 tr1, tr2, tr3 
                 Start time of related events in 
               
               
                   
                   
                 other channels 
               
               
                   
                 td1, td2, td3 
                 Start time of detected events in 
               
               
                   
                   
                 other channels 
               
               
                   
                 t_c 
                 Start time of current event 
               
               
                   
                 t_dur 
                 Event duration, in seconds 
               
               
                   
                 t_dur_n 
                 Duration of the newer event, in 
               
               
                   
                   
                 seconds 
               
               
                   
                 t_strt 
                 Event start time, in seconds 
               
               
                   
                 t_strt_n 
                 Start time of newer event, in 
               
               
                   
                   
                 seconds 
               
               
                   
                 tn_amp 
                 Amplitude of the nearest event 
               
               
                   
                 tn_dur 
                 Duration of the nearest events, in 
               
               
                   
                   
                 seconds 
               
               
                   
                 tn_strt 
                 Start time of near events, in 
               
               
                   
                   
                 seconds 
               
               
                   
                 td 
                 Start time of detected events 
               
               
                   
                 tr 
                 Start time of the related events 
               
               
                   
                 x 
                 A complex signal 
               
               
                   
                   
               
             
          
         
       
     
     
       
         
               
             
               
               
               
               
             
           
               
                 TABLE 2 
               
             
             
               
                   
               
               
                 Settings 
               
             
          
           
               
                   
                   
                 DEFAULT 
                   
               
               
                 NAME 
                 DESCRIPTION 
                 VALUE 
                 RANGE 
               
               
                   
               
               
                 AMP S   
                 Amplitude of 
                 0 
                 0-2 
               
               
                   
                 structuring elements 
               
               
                 AUT_TH s   
                 Turning the auto 
                 0 
                 0,1 (off, 
               
               
                   
                 threshold on and off 
                   
                 on) 
               
               
                 DmaxG S   
                 Maximum GAP event 
                  3 S 
                 3-5s 
               
               
                   
                 duration 
               
               
                 DmaxV S   
                 Maximum vascular 
                 70 ms 
               
               
                   
                 event duration 
               
               
                 DminG S   
                 Minimum GAP event 
                  2 ms 
                 2-5 ms 
               
               
                   
                 duration 
               
               
                 DminV S   
                 Minimum vascular 
                 20 ms 
               
               
                   
                 event duration 
               
               
                 DT_LN S   
                 Length of envelope 
                 1024 
                 A power 
               
               
                   
                 data processing array 
                   
                 of 2 
               
               
                 DLY_TH S   
                 Threshold of 
                 ICDL_L 
                 max mic 
               
               
                   
                 environmental sound 
                   
                 spcg / C 
               
               
                   
                 delay 
                   
                 air 
               
               
                 ENP_PRE S   
                 The preset value of 
                 30 Mv 
                 25-100 Mv 
               
               
                   
                 envelop threshold 
               
               
                 ENP_SMT S   
                 Smooth envelope 
                 0 
                 0,1 (no, 
               
               
                   
                 control 
                   
                 yes) 
               
               
                 FH S   
                 Low pass frequency 
                 1800 Hz 
               
               
                 FL S   
                 High pass frequency 
                  70 Hz 
               
               
                 FLTR_B S   
                 Band pass filter 
                 1 
                 0,1 (no, 
               
               
                   
                 control 
                   
                 yes) 
               
               
                 FmaxG S   
                 Maximum GAP event 
                 1500 Hz 
                 800-1800 
               
               
                   
                 frequency 
                   
                 Hz 
               
               
                 FmaxV S   
                 Maximum vascular 
                  100 Hz 
                 30-120 
               
               
                   
                 event frequency 
                   
                 Hz 
               
               
                 FminG S   
                 Minimum GAP event 
                  20 Hz 
                 10-70 
               
               
                   
                 frequency 
                   
                 Hz 
               
               
                 FminV S   
                 Minimum vascular 
                  30 Hz 
                 5-30 Hz 
               
               
                   
                 event frequency 
               
               
                 FOs 
                 Filter order 
                 3 
                 1-50 
               
               
                 FS S   
                 Sampling frequency 
                 4096 Hz 
                 2048 and 
               
               
                   
                   
                   
                 up 
               
               
                 ICDL_H S   
                 Upper limit of 
                 30 ms 
                 function 
               
               
                   
                 interchannel delay 
                   
                 of C in 
               
               
                   
                   
                   
                 abd. 
               
               
                 ICDL_L S   
                 lower limit of 
                 0 ms 
                 function 
               
               
                   
                 interchannel delay 
                   
                 of C in 
               
               
                   
                   
                   
                 air 
               
               
                 K S   
                 Number of nearest 
                 4 or 
                 Number of 
               
               
                   
                 neighbors 
                 more 
                 subjects/ 
               
               
                   
                   
                   
                 3 
               
               
                 OVLAP S   
                 Data overlap length 
                 14 
                 5- 
               
               
                   
                   
                   
                 (DT_LN S   
               
               
                   
                   
                   
                 /2) 
               
               
                 MU S   
                 Adaptation parameter 
                 5 
                 0.01 - 10 
               
               
                 N_ENP S   
                 Number of envelope 
                 DT_PTS 
                 1-DT_PTS 
               
               
                   
                 data points 
               
               
                 N_HST S   
                 Number of points of 
                 4094 
                 2 12  for 
               
               
                   
                 envelope histogram 
                   
                 12-bit 
               
               
                 N_SMTH S   
                 Number of points for 
                 10 
                 3-20 
               
               
                   
                 data smoothing 
               
               
                 N_STR S   
                 Number of structuring 
                 5 
                 3-15 
               
               
                   
                 elements 
               
               
                 RL_TH S   
                 Threshold on related 
                 0.5 
                 0.1-0.9 
               
               
                   
                 events 
               
               
                 SPCG_TH S   
                 Event spacing 
                 30 ms 
                 5-30 ms 
               
               
                   
                 threshold for pasting 
               
               
                 SP_TH S   
                 Threshold of the 
                 0.5 
                 0.1-0.9 
               
               
                   
                 spectral deviation 
               
               
                 TYP S   
                 Type of structuring 
                 0 
                 0,1 
               
               
                   
                 elements 
               
               
                   
               
             
          
         
       
     
     In addition, the sounds may be fed into the multichannel tape recorder in a step  206  which may then also feed the sounds to the analog amplifier filter  204 . The amplifier filters and then feeds sounds to an analog to digital converter in the step  208  which converts the sounds to digitized sound signals for analysis by the computer in a step  210 . 
     As shown in FIG. 8, the computer is able to find acoustic events in a step  212  and to characterize the acoustic events in the step  214 . It recognizes gastrointestinal acoustic phenomena (GAP) events in a step  216 . In addition, from other portions of the routine other patient acoustic characteristics such as trans-abdominal spectra and velocity modulation are determined in a step  220 . Clinical information may also be input through a keyboard or other appropriate means in a step  222 , all of which are fed to a pattern recognition algorithm in a step  224  for providing diagnoses with probabilities in a step  226 . In addition, the information received by the pattern recognition algorithm may be output in a step  228  and subject to physician interpretation in a step  230 . 
     In an alternative version as shown in FIG. 9, the patient may be attached to a microphone array in a step  240 . The microphone array captures sounds in a step  242  and provides electrical signals to a single or multichannel analog tape recorder in a step  244  and also to an analog amplifier and filter in a step  246 . The sounds are converted from analog form to digital form in a step  248  and the digitized sound signals may be provided to a modem in a step  250  for transmission to a centralized computer facility. 
     In an ambulatory monitoring system the patient may be connected to the microphone array in a step  262  as shown in FIG.  10 . The microphone captures sounds in a step  264  and the sound signals are recorded by a single channel analog tape recorder in a step  266  for provision to other systems. The patient or the system may supply timing markers indicative of symptoms, events or time duration in a step  268 . The same monitoring schema may also be used for long term monitoring over extended periods of time at low tape speed. In that case the electronic marker signal would comprise a timing signal impressed upon one of the channels. The timing signal would be used by digital processing to remove or reduce timing perturbations introduced by low speed flutter and wow in the tape recorder. 
     In a still further alternative, as shown in FIG. 11, the patient may be connected to a microphone belt or pad in a step  270 . The microphone belt or pad may convert the sound signals to analog signals in a step  272  and the analog sound signals are recorded in a step  274  for later provision to a computer. The patient or the system may supply timing markers indicative of symptoms, events or time duration in a step  276 . 
     In general, as shown in FIG. 12, in order to find acoustic events and features in a step  300  the amplitude envelope is calculated for each of the sound channels. An amplitude threshold is then determined in a step  302  for each channel. In a step  304  the events in each channel are determined using the channel amplitude threshold by using the thresholding as a filtering or screening tool. In a step  306  neighboring signals are designated on the same channel signals as a single event. In a step  308  correlated and nearby events are determined in other channels. In a step  310  a determination is made whether the nearest event is part of an actually related event or is merely coincidental. In a step  312  related events are labeled in other channels to avoid double event counting and the nearest events that are part of related events are also labeled following which the return is exited in a step  314 . 
     The step  300 , involving the calculation of the amplitude envelope, is shown in further detail in FIGS. 14A through B. A data file stores the digitized sound signals and the file size is read in a step  320 . The number of data points in the file is determined to be equal to the file size divided by 2 in a step  322 . The length of the data processing array is then read from a variable indicator in a step  324  and an overlap length previously set is read in a step  326 . The number of data points to be read from the file is calculated to be equal to the data processing array length minus two times the overlap length in a step  328 . The first two times overlap length of data points in the processing array are packed with zeros in step  330  and the counter is set equal to zero in a step  332 . A determination is made if the envelope smoothing flag is on in a step  334 , and if it is, structuring elements are calculated in a step  336 . 
     Referring now to FIG. 15, the number of structuring elements is read in a step  340  and the amplitude of the structuring elements is read in a step  342 . The type of the structuring elements previously determined is read in a step  344  and a type test is made in a step  346 . If the structuring elements are of type  1  they are calculated according to structuring element equal to the amplitude times the size of the quantity i times π over number of structuring elements minus 1 taken from i=zero to the number of structuring elements in a step  348 . If the type from  346  has been set equal to zero, the structuring element is packed with zeros in each of the elements of the array in a step  350  and the routine is exited in a step  352  to transfer control to a step  354  as shown in FIG. 14A to calculate the filter coefficients. 
     The filter coefficients are calculated in a routine as shown in FIG. 16 where the frequency domain filter coefficients are calculated in a step  370 . 
     Step  370  is carried out as shown in FIG. 17 in a step  372  where the Hilbert filter coefficient zero is set equal to one and Hilbert filter coefficients one through half the data length minus 1 are set equal to two in a step  374 . The next coefficient is set to one in a step  376 . The last Hilbert filter coefficients are set equal to zero in a step  378  and return to step  380  to a step  382  shown in FIG.  16 . The request of band pass filtering is tested in  382  and if found to be true, the frequency domain band pass filter coefficients are calculated in a step  384 . In a step  386  each of the Hilbert filter coefficients is multiplied by a corresponding band pass filter coefficient to form a final filter coefficient following which the routine is exited in a step  388  to the prior routine. 
     The step  384  is carried out in FIG. 18 wherein a step  400  the sampling frequency, high pass frequency and low pass frequencies previously preset to 4096, 70 and 1800 Hz, respectively, are read. The size of the band pass filter coefficient is determined in a step  402  and normalizing occurs in a step  404 . In steps  406  to  412  the band pass filter coefficients are computed and the routine is exited in a step  414  back to step  386  in the filter coefficient calculation routine shown in FIG.  16 . 
     Referring now to FIG. 14A, the data points are read from the file and placed at the end of the processing array in a step  430 . The counter is incremented in a step  432  and an end of file test is done in a step  434 . If the file processing is ended, the routine is exited in a step  436 . If not, a Fourier transform is calculated in a step  438  following which the transformed frequency domain function is multiplied by filter coefficients in a step  440 , as shown in FIG.  14 B. The inverse Fourier transform is taken in a step  442  to convert back to the time domain and the instantaneous amplitude of the complex signal is taken by taking the square root of the sum of the squares of the real and imaginary portions of the signal in a step  444 . The signal envelope is set equal to the instantaneous amplitude in step  446  and a test is made in a step  448 . 
     If the test is positive the envelope is smoothed using dilation in a step  450  as may be seen in further detail in FIG. 19 wherein the number of data points of the envelope is read in a step  460 . The size of the structuring element is read in step  462 . The amplitude of the structuring element is read in step  464  and a variable dn is set equal to the structuring element length less one, the whole quantity divided by two in a step  466 . That quantity is assigned to a counter in a step  468  and the counter is incremented in a step  470 . A test is then made to determine whether the number of points is between the original dn number from step  464  or the current counter number in a step  472 . If it is not, the step is returned from in a step  474 . If it is, a supplementary array is loaded in a step  476 . The supplementary array is updated in a step  478  and the i th  element of the array is determined in a step  480  following which the routine loops back to the counter in step  470 . 
     In the event that the envelope is not to be smoothed or the step  450  is completed as shown in FIG. 14B, the last two times the overlap length of data points of processing data array is copied into the beginning of the array in a step  500 . A test is made to determine whether the counter is equal to one in a step  502 . If it is, a number of the data envelope points, equal to the read data points minus the overlap length, starting at two times the overlap length is written to an output file in a step  501 . In the event that the counter is not equal to one the points are written to the output file from the envelope data array starting at envelope element overlap in a step  506 , following which the control is transferred back to step  430 . 
     In order to perform the amplitude threshold determining step for each channel, step  302  shown in FIG. 12, an amplitude threshold routine is provided as set forth in FIG.  20 . In a step  520  a test is made to determine whether the amplitude threshold has previously been set. If it has, the end position is set equal to the preset in a step  522 , following which the routine is exited in a step  524 . If it has not, the envelope data is read in a step  526  and a histogram of the envelope data is constructed in a step  528 , as shown in greater detail in FIG. 21. A smoothing moving average filter is applied to the histogram data in the step  530  and the peak on histogram and corresponding envelope value are determined in the step  532 . The average slope of the histogram over data segments of preselected length is determined in a step  534  which is shown in greater detail in FIG. 22, wherein in a step  540  the first envelope value is determined. In a step  542  the slope is set equal to the current envelope value minus the next envelope value. An end of data test is made in a step  544 . If the end of data has not been reached, the next envelope value is considered in a step  546  following which control is returned to step  542 . If it has not, a moving average filter is applied in a step  548  to smooth the slope, following which the routine is exited in a step  550 , returning control to a step  552  shown in FIG.  20 . When the histogram slope values are scanned starting at the histogram peak and moving in the direction of increasing envelope values to find an envelope value where the slope first becomes positive. Upon finding the value when the slope first becomes positive, the amplitude threshold value is set equal to that value in a step  556  and the routine is exited in step  524 . 
     In order to calculate the histogram of the step  528 , as shown in FIG. 21, all elements of the histogram array are set equal to zero in a step  570 . The ADD range previously set is read in a step  572  and the first envelope value is considered in step  574 . Variable i is set equal to the current envelope value times the quantity 4,096 divided by the analog to digital converter range in a step  576  and in a step  578  the i th  element of the histogram vector is increased by one step to the next point. An end of data test is made in a step  580 . If the end of data has been reached the routine is exited in return step  582 . If not, control is transferred to a step  584  causing the next envelope value to be considered and then transferring control back to step  576 . 
     After the amplitude threshold for each channel has been found in step  302 , events in each channel must be located using the channel amplitude threshold in the step  304 . This is carried out in the routine shown in FIG. 23 wherein in a step  600  the amplitude threshold value previously calculated is read as is a preset sampling frequency. The variable i_strt is set equal to zero in step  604 ; and the variable i_dur is set equal to zero in step  606 . First point of the digital envelope data is read in a step  608  and the i_strt value is incremented in a step  610  following which an end of file determination is made in a step  612 . If the end of file has been reached control is transferred to a step  614 . If it has not, the envelope value is tested for whether it is greater than the amplitude threshold; in other words, is there a real reading or a noise reading in a step  616 . If it is not, control is transferred to a test to determine whether i_dur is greater than zero in a step  618 . If i_dur is not greater than zero, control is transferred back to step  608 , causing the next data point to be read. If i_dur is greater than zero, the event number of points is set equal to i_dur in the step  620 . The event duration is set equal to the event number of points divided by the sampling frequency in the step  622  and the event duration is saved to disk in a step  624  following which step  606  is executed. 
     If the event value is greater than the great amplitude threshold, control is transferred from step  616  to a step  626  causing the duration variable to be incremented. A test is made to determine whether the duration value variable is equal to one in a step  628 . If it is not, control is transferred back to step  608 . If it is, the starting point of the event is set equal to i_start in a step  630 . The event start time is set equal to i_start divided by the sampling frequency in a step  632 . The event start time is then saved to disk in a step  634  following which the next point of the digital envelope data is read in a step  608 . 
     In order to perform Step  306  where neighboring signals, which are neighboring in time are designated on the same channel signals as belonging to a single gastrointestinal acoustic phenomenon or event, as is shown in FIG. 24 the signals from the first channel are accessed in a step  640 . The first event, which has been previously identified, is accessed in a step  642 . The current event occurrence time and duration previously determined are accessed in a step  644  and the second event in the channel is accessed in a step  646 . The current event occurrence time and durations for the second event are accessed in a step  648  and the event spacing spcg is calculated in a step  650 . In a step  652  if the calculated event spacing is less than a threshold event spacing, control is transferred to a step  654  and the event occurrence time and duration are saved in a step  654  and the second event&#39;s occurrence time and duration are stored as the event occurrence and duration in a step  656  following which in a step  658  the next event is considered. In the event that the spacing is less than the threshold, in a step  660  a new duration is calculated as the sum of the spacing, the second event duration and the original duration, and the next event is then considered in a step  658 . Following step  658  a test is made to determine whether any more events are present. If they are not, in step  662  control is transferred to a step  664 , causing the next channel to be analyzed as set forth in the previous steps. A test is then made in a step  666  to determine whether any additional channels need to be analyzed. If there are no more channels to be analyzed, the routine is exited in a step  668 . If there are more channels to be analyzed, control is transferred back to step  642 . 
     In order to find correlated in nearby gastroacoustical phenomenon or events in other channels as set forth in step  308  shown in FIG. 12, the steps shown in FIG. 25 are performed. 
     The first channel is taken under consideration in the step  670  and in a step  672 , the first event is to be examined. In a step  674  the current event start time and its duration are read and in a step  676  the event time series is read. In addition, in a step  678  the interchannel event delay threshold, which is determined as set forth in FIG. 26, is read. In a step  680  the search region on other channels is set as well as the search duration which is dependent upon the interchannel event delay threshold. In a step  682  the maximum normalized cross-correlation coefficient and maximum coherence between the events and the sliding window in the search region and in other channels for use in determining the location of maximum on each channel is calculated. In the event that the maximum normalized cross correlation coefficient exceeds a threshold on related events previously set in a step  683 , control is transferred in a step  684  to a step  686 , causing a holding variable to be located with the location of the maximum. In the event the test in the step  684  is negative, control is transferred directly to a step  688 , causing a test to be made to determine whether the maximum coherence between the event and the sliding window in the search region is greater than a threshold on related events. If it is, the second local maximum location is loaded in step  692 . If it is not, control is transferred to a step  690 , causing nearby events to be found and their start times to be saved, as set forth in FIG.  27  and described hereinafter. Control is then transferred to a step  700  where the next event is accessed and processed. A test is made in a step  702  for end of file. if end of file has not been reached, control is transferred back to step  674 . If the end of file for that channel has been reached, control is transferred to a step  704 , causing the next channel to be incremented to and a test is made in a step  706  to determine whether any more channel information is available. If it is, control is transferred back to step  672  for further processing. if it is not, control is transferred to a step  708 , following which the routine is exited and control is transferred back to step  310  to determine whether the nearest event is part of a related event. 
     Referring now to FIG. 26, the steps for determining the interchannel event delay threshold, which has been previously applied or set forth therein, in a step  710  the event start time for each of the channels is loaded separately and then consideration is shifted to the first channel in a step  712 . The first event is accessed in a step  714  and current event start time is read in a step  716 . Starting at the current event start time a search is made along each of the other channels for the first event to occur and their individual start times are determined. Interchannel delays are calculated as being the difference between each of the other channel start times and the current event start time in a step  720 . In a step  722  indexing is done to the next event and a test is made in a step  724  to determine whether any more events are present on that channel. If they are not, control is transferred to a step  726  where indexing is done to the next channel, and a test is made in a step  728  to determine whether any more channels of data are available. If there are more channels of the data, control is transferred back to step  714 . If there are no more channels of data to be processed, a histogram of the interchannel delay is generated in a step  730 . The histogram is smoothed, with a smoothing average filter in a step  732  and a delay value corresponding to the histogram minimum for delay ranging between preset high and low values is determined in a step  734 . The delayed threshold is then set equal to the delay value in a step  736  and routine is exited in a step  738 . 
     In order to find nearby events and save their start times and their amplitudes as required in step  690  appearing on FIG. 25, the process set forth in FIG. 27 is employed. In a step  740  the interchannel delay threshold previously determined, the current event channel, the start time and the duration are all read. The first channel is considered in the step  742  and in a step  746  other channels starting at the starting time for the first event are searched and the events&#39; start time, duration and amplitude are found. The interchannel delay is then calculated in a step  748  as being the difference between the initial start time and the first event start time. A test is made in a step  750  to determine whether the interchannel delay is less than the interchannel delay threshold. If it is, control is transferred to a step  752  in which a test is made to determine whether the current event duration is greater than the first event duration on the other channel. If the current event duration is greater than the first event duration on the other channel, control is transferred to a step  754 , causing the start time of the first event on the other channel and its amplitude to be saved. If the responses to step  750  and  752  are either in the negative, control is transferred to a step  756  causing the next channel to be accessed and processed. Control is then transferred to a step  758 , checking for additional channels to be processed. If there are no more channels the routine is exited in a step  760 . If there are more channels to be processed, control is transferred back to the step  746 . 
     In order to perform the step  310  in which a check is made to determine if the nearest event is part of a related event, the routine set forth in FIG. 28 is carried out. In a step  762  the event start time for each channel is loaded and the first channel is considered in a step  764 . The first event in the current channel is accessed in a step  766  and the current event start time and its duration are read. Related event start times are also read, all in a step  768 . The end time for the related events is calculated as a different between the related event start times and the current event start time. Beginning at the current event start time, each of the remaining channels is searched for the first events to occur other than related events and their start times and durations are determined. The end time of the nearest detected event is determined in a step  774  and the event overlap on channels is checked in a step  776  as set forth in further detail in FIG.  29 . The next event is considered in a step  778  and a test is made in a step  780  to determine whether there are more events. If there are more events, control is transferred back to step  768 . If there are not, the next channel is accessed in step  782 . An end of channel test is made in a step  784 . If the end of channel&#39;s test indicates further channels are to be processed, control is transferred to a step  766 . If not, the routine is exited in a step  786 . 
     The step  776  is performed as set forth in FIG.  29 . The first channel is considered in a step  788  and the start time and end time of the related events as well as the start time and end time of the detected event are obtained in step  790  from storage. A test is made in a step  792  to determine whether the start time of the related event is greater than the start time of the detected event and whether the start time of the related event is less than the end time of the detected event. If it is, control is transferred to a step  794 , causing the events to be labeled as overlapped. If it is not, control is transferred to a step  796  wherein the end time of the related event is tested to determine whether it is greater than the start time of the detected event together with the end time of the related event being tested to determine whether it is less than the end time of the detected event. If both of those equalities are true, control is transferred to step  794  and the events are labeled as overlapped. If not, control is transferred to step  798  wherein a test is made to determine whether the start time of the related event is less than the start time of the detected event and the end time of the related event is greater than the end time of the detected event. If true, the events are labeled as overlap in step  794 . If not, control is transferred to step  800  and the events are labeled as not overlapped, following which in a step  802 , the next channel is considered. A test is made in a step  804  to determine whether any more channels are to be examined. If they are to be examined, control is transferred back to step  790 . If they are not, the routine is exited in a step  806 . 
     In addition, it is important to characterize the events once they have been identified as set forth in FIG. 13, in a step  810  a test is made to localize each event followed by which in a step  812  event features are combined, including a start time, duration, amplitude, location, spectrum, morphological characteristics, including attack and delay characteristic, and a transmission transfer function followed by exiting the routine in a step  814 . 
     In order to localize each event, the steps set forth in FIG. 30 are carried out. 
     In order to perform the step  810  as shown in FIG. 30, the regions of origin are defined in the step  816 , which is shown in more detail in FIG.  31 . The first channel is then considered in a step  818  and the first event on the first channel is accessed in a step  820 . The event start time and peak to peak amplitude are read and the number of related events and the time delay of the related events and the peak to peak amplitudes is also read. If the number of related events is equal to zero as tested for in step  824 , the event location is assigned to the microphone corresponding to the current channel in step  826  and the event has been localized. In the event that the number of the related events is not equal to zero, the origin of the sound region is determined in a step  828  as is more fully set forth in FIG.  32 . 
     A test is made in a step  830  to determine whether the number of related events is greater than one. If it is, the sound source location is determined in a step  832  as more fully set forth in FIG.  34 . In addition, an input is received from a step  834  wherein the transabdominal speed of sound and abdominal damping characteristics have been determined as set forth in FIG.  33 . Control is then transferred to the step  836 , causing the next event to be considered. In a step  840  a test is made to determine whether there are any more events. If there are more events, control is transferred back to the step  822 . If not, the next channel is considered in a step  842 . A test is made in a step  834  to determine whether all channels have been processed. If they have not, the channel is incremented and control is transferred back to the step  820 . If they have, the routine is exited in a step  846 . 
     In order to define the regions of origin in step  816 , the number of microphones and their positions are read in a step  850  as shown in FIG. 31. A midline is determined for each microphone pair in a step  852  and in a step  854  the middle point for each microphone triplet is determined. In a step  856 , the abdominal regions are determined, including the border regions, and in a step  858  the order of arrival corresponding to each region, including equal arrival times, is determined following which the routine is exited in a step  860 . 
     In order to determine the sound region of origin in step  828 , in a step  862  the event order of arrival is read and the event amplitude on each channel is also read, as shown in FIG.  32 . The order of arrival and amplitude information is compared to those of the predetermined regions of origin in a step  864 . In a step  866  an event is assigned to a region of origin on the basis of the comparison and in a step  870  the routine is exited. In order to determine the average transabdominal speed and the abdominal damping characteristics in step  834 , in a step  872  a tape containing prerecorded pure tones and white noise is played through a tape player in a step  874 . that signal is fed through a filter and preamplifier in a step  876  and is boosted by a power amplifier in a step  878 . A shaker coupled to an accelerometer in steps  880  and  882  provides vibration motion to a patient and a pair of transabdominal microphones in a step  886  pick up the resulting vibrational energy. That energy is recorded as electrical signals in a step  888  in a multichannel recorder and is converted in an analog to digital converter in a step  890  and stored in a computer in step  892 . Transmitted signals and events are found in a step  894  and a time delay is calculated in a step  896 . The time delay is fed in a step  900  to calculate the frequency dependent transabdominal speed of sound and spectral modulation and step  900  also receives the measured distances between the microphones from a step  898 . 
     In order to determine the sound source location after learning the transabdominal speed and abdominal damping characteristics, in a step  902  as shown in FIG. 34 the difference in travel distances of the events are calculated on the basis of the time delay and the average speed of sound obtained from step  834 . In a step  904 , for each microphone pair a hyperbolic curve is determined that describes the locus of sources that would produce the same difference in the sound travel differences. In a step  906  an intersection point of each of the curve pairs is determined and any points that are located outside the abdominal region are excluded from consideration. In a step  908  the middle location of intersection points is determined by averaging their coordinates. In a step  901  the middle point coordinates are assigned to event location coordinates and the routine is exited in a step  912 . 
     In order to combine the event features as set forth in step  812 , the sampling frequency is read in step  914  as shown in FIG.  35 . The start of the event time is read from disk as is the event duration in a step  916 . The event time series is then read from disk in a step  918 , and the spectrum of the event and its dominant frequency are determined in a step  920 . The peak to peak amplitudes and root-mean-square amplitudes of the event are calculated in a step  922 . In a step  924  other event features, including the instantaneous frequency, spectrogram, attack and decay characteristics, spatial event damping and the like are determined from the amplitude envelope and spectrum of the event and from analyzing nearby and related interchannel events and calculating a transmission transfer function. The event transmission speed is also determined. These event features are saved in a step  926  and the routine is exited in a step  928 . 
     Recognition of GAP events is carried out in the routine shown in FIG.  36 . The event dominant frequency and duration are read in a step  930  and a test is made to determine whether the duration is greater than the minimum. If it is, control is transferred to a step  936  to determine whether the duration is less than the maximum. If it is, determinations are made in steps  938  and  940  to determine whether the dominant frequency is within a predetermined frequency range. In the event none of those tests hold true, control is transferred to a step  936  and the event is labeled as of an unknown kind. In the event that the duration of frequency range is within the windowed limitations, the event is labeled as a possible gastroacoustic phenomenon in step  942 . A test is made in a step  944  to determine whether environmental noise, for instance, from the fourth channel, may have masked GAP event and a test is made in a step  946  to recognize vascular events. The routine is then exited in step  948 . In order to perform step  944  to recognize environmental noise or events, the threshold of the interchannel delay for environmental sounds is read in a step  950 , as shown in FIG. 37. A reading is made to determine if nearby or related labeled events were found in other channels and their interchannel delay times are read in step  952 . In a step  954 , a test is made to determine whether such a related or nearby event was detected on all microphones. If it was not, control is transferred to the return step  960 . if it was, a test is made to determine whether the absolute value of the time delays is less than the interchannel delay for environmental sounds. If not, the routine is exited. If it is, the event label is changed to being one of environmental noise in a step  958 . 
     Vascular events are recognized in step  946 , as set forth in FIG.  38 . In a step  962 , the dominant frequency and duration of the event are read and a test is made to determine whether the duration and the dominant frequency are within window values in steps  964  through  970 . If they are not, control is transferred to the return step  982 . If they are, an event spectrum is calculated in a step  972  and normalized. In a step  976 , a series of data related to a library of vascular sound spectra are fed to a step  974  which receives the event spectrum and calculates the deviation of the event spectrum morphology from that of known vascular sounds. If the deviation is less than a spectral threshold value as tested for in step  978 , the routine is exited. If the deviation is greater than or equal to the spectral threshold, the event is labeled as vascular in step  980  and the event is exited. 
     The system is also capable of performing pattern recognition and as set forth in FIG. 39, a test is made in a step  984  to determine if the patient or subject is a control or has small bowel obstruction or has ileus, as set forth in greater detail in FIG.  40 . In a step  986 , a test is made to determine whether the variables indicate possible inflammatory conditions with location and severity and in a step  988 , diagnostic or probabilities are calculated and output and the routine is exited in a step  990 . 
     The step  984  is carried out as shown in FIG.  40 . In a step  992  the total number of events and the recording duration is read. In a step  994  the average event rate based on the previous value is determined and the dominant frequency and duration of all events is read in a step  996 . The median duration for all events is calculated in step  998 , and the median dominant frequency for all of the events is calculated in a step  1000 . A nearest neighbor classifier receives the average event rate median duration and median dominant frequency and operates on values in a step  1004 , as set forth in further detail in FIG.  41 . The routine is then exited in step  1006 . 
     In order to perform the nearest neighbor classification, the distance in the feature space is calculated between the current subject and prediagnosed subjects in a step  1008 . The nearest preclassified or prediagnosed neighbors are determined in a step  1010  and the current subject class is set to the class of the majority of nearest neighbor preclassified neighbors in a step  1012 . The average distance between a current subject and other members of the same class is determined within the space in a step  1014  and the average distance between the subjects in the same class, excluding the current subject is determined in a step  1016 . The ratio of the subject class distance is then determined in the step  1018  and returned to the step  1020  exiting. 
     Referring now to FIG. 42, a procedure is generally shown therein which may be executed at the microprocessor for filtering multiple channels when a noise estimate is received from a noise channel. In a step  1021 , multiple channel signals are accessed and the first channel is accessed in a step  1022 . A noise channel signal is accessed in a step  1024  and the channel selected is filtered adaptively in a step  1026 . The next channel in the step  1028  and the test is done in the step  1030  to determine whether any more channels are available. If more channels are available, step  1026  is returned to. If not, the routine is exited. 
     The step  1026  is shown in further detail in FIG. 43, wherein in a step  1034  the primary input channel data is stored in an array P and the reference noise channel data from step  1024  is stored into an array NR. The filter order which has been preselected is read in a step  1036  and is divided by two in a step  1038  to provide i_p. 
     In a step  1040  the initial filter weights which were set to zero in step  1042  are inputted as is any update filter weights from step  1024  which may have been affected by an adaptation parameter μ. All are provided to step  1040  where in i_n is determined as the difference between i_p and half of the filter order. The initial filter weights in the updated filter weights, however, are available at step  1040  but are not used in the calculation. In a step  1044  the filtered noise referenced input nf is calculated as the sum of the vector product of the initial or updated filter weights multiplied by the reference noise channel data. An output is calculated in step  1046  related to the difference between the primary input channel data and the reference noise input at that point. In a step  1048  the process is indexed to the next sample and a test is done in a step  1052  to determine whether there are more samples. If there are more samples, the filter weights are updated in a step  1054  on the basis of an adaptation parameter MU, which is doubled and then multiplied by the G output and the noise channel data array. The MU value is preset and the entire quantity is added to the previous filter weights to provide updated filter weights available at step  1040  for calculation of the filtered noise reference input in step  1044 . 
     The system provided outputs in, among other forms, pseudo three-dimensional plots of acoustic frequency event duration and the number of events. For instance, as shown in FIG. 44, there is a clustering of GAP events with a given duration and dominant frequency. These GAP events were detected from the epigastraeum of a normal subject. It should be appreciated that the epigastraeum can have long duration events. A subject with ileus had a relatively small number of events and did not have long duration low frequency events as is shown in FIG.  45 . GAP events collected from the right lower quadrant of a patient with small bowel obstruction showed a generally downward shifting of dominant frequencies plus very low frequency events in the near right hand corner of the plot as shown in FIG.  44 . Tehse were not seen in normal patients or patients having ileus, as shown in FIG.  46 . 
     In FIG. 47, a pseudo three-dimensional plot is shown of events from the right lower quadrant of a normal subject. The events are characterized by the absence of long duration and low frequency events. In FIG. 48 events taken from the left lower quadrant of a normal subject are similar in characteristic to those shown in FIG.  47 . In FIG. 49 a spectrogram is shown of four events from a normal subject. The events are short and have a dominant frequency at about 500 Hz. In FIG. 50 a spectrogram is shown of a subject with small bowel obstruction which is characterized by long event duration and lowering of the dominant frequencies. 
     The bowel sound computerized analysis was performed in the diagnosis of human mechanical small bowel obstruction (SBO) after preliminary studies suggested diagnostic gastrointestinal acoustic phenomena (GAP) changes in a rat SBO model. 
     Fifty-three 20-minute GAP recordings were performed in 43 human subjects [37±18 (mean±SEM) years of age, range 2-94] using a four-microphone array. Recordings were digitized, and each GAP event analyzed for spectrum and duration. Follow-up was obtained on all patients, who were assigned to 1 of 5 categories: proven SBO by laparotomy or contrast radiography (5); suspected but unproved SBO (3); suspected but unproved ileus (3); definite ileus (7); and normal fasted controls (25). 
     The 8 proven and suspected SBO patients had similar findings, demonstrating major consistent differences from the 10 proven and suspected ileus subjects, and both these groups had significant differences from normal controls. 
     
       
         
               
               
               
               
               
             
               
               
               
               
               
               
               
             
           
               
                   
                   
               
               
                   
                 SBO 
                 Ileus 
                 Control 
                 Significant (p &lt; .05) 
               
               
                   
                   
               
             
             
               
                   
               
             
          
           
               
                 n 
                 8 
                 10 
                 25 
                 yes 
                 yes 
                 yes 
               
               
                 Number 
                 50 
                 5 
                 25 
                 yes 
                 yes 
                 yes 
               
               
                 Events/min 
                 (29-60) 
                 (1.6-10) 
                 (7-46) 
               
               
                 Frequency 
                 210 
                 235 
                 325 
                 no 
                 yes 
                 yes 
               
               
                 (in Hz) 
                 (192- 
                 (213- 
                 (248- 
               
               
                   
                 285) 
                 280) 
                 454) 
               
               
                 Duration 
                 34 
                 34 
                 31 
                 no 
                 no 
                 no 
               
               
                 (in ms) 
                 (32-35) 
                 (32-35) 
                 (30-33) 
               
               
                   
               
               
                 Values are median (25th-75th%). p values are for SBO- Ileus (S-I), SBO-Control (S-C), and Ileus-Control (I-C).  
               
             
          
         
       
     
     Beyond the median data, every obstructed patient but no non-obstructed subject demonstrated intermittent very long duration (1054±188 ms) and low frequency (168±62 Hz) events (&gt;0.0001). Computerized bowel sound analysis may provide a noninvasive method to rapidly and safely diagnose mechanical bowel obstruction and differentiate it from ileus. 
     The auscultory finding of “high pitched rushes” with SBO may in fact be “low pitched rushes.” 
     While there has been illustrated and described a particular embodiment of the present invention, it will be appreciated that numerous changes and modifications will occur to those skilled in the art, and it is intended in the appended claims to cover all those changes and modifications which fall within the true spirit and scope of the present invention.

Technology Classification (CPC): 0