WO2010054481A1 - Method and apparatus for monitoring breathing cycle by frequency analysis of an acoustic data stream - Google Patents

Abstract

Disclosed herein is a method and apparatus for monitoring, identifying and determining the breathing cycle of an individual from processed acoustic signal waveform data. The breathing sounds of an individual are recorded using a microphone and digitized such that the breathing sounds may be plotted. The data is segmented and transformed to form a plurality of segments representative of a frequency spectrum. The frequency spectrum data is transformed so as to produce magnitude bins and the sum of lower magnitude bins and the sum of higher magnitude bins are determined in a sampling of segments. A Bands Ratio is determined from the sum of lower magnitude bins and the sum of higher magnitude bins in the sampling of segments. A first bands ratio is then determined within a given segment and compared to the mean bands ratio. If the first bands ratio of the given segment is greater than the mean bands ratio by at least a predetermined multiplier, the given segment is labeled as inspiration. If the first bands ratio of the given segment is less than the mean bands ratio by at least a predetermined multiplier, the given segment is labeled as expiration.

Description

MF THOD AND APPARATUS FOR MONITORING BRF ATH ING CYCLE BY FREQUENCY ANALYSIS OI AN ACOUSTIC DATA STREAM

RFI Al LD APPLICATIONS

[0001 1 The present application is related to and claims benefit of priority to U S Provisional

Patent Application No 6 T I 93,320, filed November 1 7, 2008 entitled ' TRACKING PHASES OF TI I F BREATH ING CYCLE BY FREQUENC Y ANALYSIS OF ACOUSTIC DATA", the disclosui e of w hich is hereby full} incorporated herein by refei ence

FIEl D OF FHE DISCLOSURE

[0002] The present disclosure relates to a method and appaiatus for the analysis of breathing cycles and the monitoring, identifying and/or detei mining the inspiration phase and expiration phase of breathing cycles

BACKGROUND

[0003] Respiratory disorders are known to disturb sleep patterns For example, recurrent apneas and hypopnea lead to intermittent hypoxia that provokes arousals and fragmentation of sleep, which in turn may lead to restless sleep, and excessive daytime sleepiness Repetitive apnoeas and intermittent hypoxia may also elicit sympathetic nervous system activation, oxidative stress and elaboration of inflammatory mediators which may cause repetitive surges in blood pressure at night and increase the risk of developing daytime hypertension, atherosclerosis, heart failure, and stroke independently from other risks There remains a need for improved methods for monitoring, identifying and/or determining breathing cycles, in order to obviate these risks

SUMMARY OF THE GENERAL INVENTIVE CONCEPT

1

TRI-MP2/PCT |0004| In an exemplary embodiment there is pi ovided a method for processing acoustic signal data for use in monitoring the bi eathing cy cle ot an individual I he method comprises collecting and genei ating a data set representative of an acoustic data stream plot of w ave amplitude versus time, the data set originating from breathing sounds of an individual and segmenting the acoustic data stream plot into segments wherein each segment spans a predetermined time pei iod 1 he acoustic data is transfoi med so as to produce a fi equency spectrum in each segment and the frequencv spectrum in each segment is transformed so as to produce a plurality of magnitude bins A sample including a plurality of segments is identified and a sum of lower frequenc\ magnitude bins w ithin a pi edetermined lower frequency range and a sum of highei frequency magnitude bins w ithin a predetermined higher frequency range are detei mined The sum ot higher frequency magnitude bins in the sampling is divided by the sum of lower frequency magnitude bins so as to produce a mean bands ratio A sum of lower frequency magnitude bins and a sum of higher frequency magnitude bins w ithin a given segment is detei mined and the sum of higher frequency magnitude bins is divided by the sum of lower frequency magnitude bins within said given segment so as to produce a first bands ratio and it is determined w hether said first bands ratio is greater or less than said mean bands ratio by at least a predetermined multiplier so as to provide an indication of said breathing cycle

|0005| In some exemplary embodiments, the predetermined multiplier is at least 1 In other exemplary embodiments, the predetermined multiplier is greater than 1 5 In still other exemplary embodiments, the predetermined multiplier is greater than 2

|0006| In some exemplary embodiments, the first bands ratio is labeled as inspiration if the first bands ratio is greater than the mean bands ratio by at least the predetermined multiplier

|0007| In some exemplary embodiments, the first bands ratio is labeled as expiration if the first bands ratio is less than the mean bands ratio by at least the predetermined multiplier

2 FRI-MP2/PC1 [0008| In some exemplary embodiments, the breathing sounds are collected for a period of time of from about 10 seconds to about 8 hours. In some exemplar} embodiments, the breathing sounds are collected for a period of time of from about 10 seconds to about 20 minutes. In some exemplar) embodiments, the breathing sounds are collected for a period of time of from about 10 seconds to about 25 seconds. In some exemplary embodiments, the breathing sounds are collected for a period of time of greater than 20 minutes. In some exemplary embodiments, the breathing sounds are collected for a period of time about 25 seconds.

|0009| In some exemplary embodiments, each of the segments represents a time period of from about

50 ms to about I second. In some exemplar) embodiments, each of the segments represents a time period of from about 100 ms to about 500 ms. In some exemplary embodiments, each of the segments represents a time period of about 200 ms.

|0010| In some exemplary embodiments, the lower frequency range is from about 0 Hz to about 500

Hz. In some exemplary embodiments, the lower frequency range is from about 10 Hz to about 400 Hz.

|00111 In some exemplary embodiments, the higher frequency range is from about 500 Hz to about

25,000 Hz. In some exemplary embodiments, the higher frequency range is from about 400 Hz to about 1 ,000 Hz.

|0012| In some exemplary embodiments, the sampling of the plurality of segments is selected from the recording randomly. In other exemplary embodiments, the sampling of the plurality of segments includes substantially all of the segments in the recording. In still other exemplary embodiments, the mean bands ratio is determined from at least two segments preceding the first bands ratio segment.

TRI-MP2/PCT |0013| In some exemplai v embodiments the method turthei comprises before the generating step recording the breathing sounds vuth at least one microphone

|0014) In some exemplary embodiments the audio collecting of breathing sounds of an individual comprises airflow sounds resultant from the individual s breathing applying air pressure to a diaphragm of the microphone In some exemplai) embodiments the collecting of breathing sounds of an individual comprises breathing sounds resultant fiom the breathing of the individual being recoided by the miciophone In some exemplary embodiments the collecting of breathing sounds of an individual comprises airflow sounds resultant from the individual's breathing applying air pressuie to a diaphragm of the microphone and actual bieathmg sounds resultant from the individual being recorded by the microphone

(00151 In some exemplary embodiments the collection of breathing sounds is digitized in real-time

In some exemplary embodiments the processing of the collected waveform data is perfoi med in real-time

|0016| In some exemplary embodiments breathing sounds aie collected by at least a first microphone and a second microphone The fiist microphone is operable to collect breathing sounds and airflow sounds resultant from the individual s breathing appl> ing air pressure to a diaphragm of the first microphone and the second microphone is operable to collect breathing sounds of the individual In some exemplaiy embodiments, the method furthei comprises, before the geneiating step, filtering acoustic data of an output representative of second miciophone from the acoustic signal data representative of an output of the first microphone so as to provide an acoustic data stream of an audio recording of substantially airflow sounds of the individual

TR1-MP2/PCT |0017| In some exemplai N embodiments the at least one microphone is provided in a structure including one or more openings oi sufficient size to minimize ait flow resistance and be substantially devoid ot dead space

10018) In another exemplai v embodiment there is provided an apparatus for transforming acoustic signal data breathing sounds into a graphical representation indicative of breathing c> cle phases including inspiration phases and expiration phases The apparatus compi ises at least one microphone for collecting acoustic signal data resultant fr om the breathing of an individual during a given time period and an acoustic signal data digitizing module foi digitizing the acoustic signal data to produce an acoustic data stream plot l epi esentative of wave amplitude vei sus time At least one processor operable for receiving the acoustic data stream plot is provided 1 he processor is configui ed for segmenting the acoustic data stream plot into a plurality of segments of a predetermined length of time, ti ansfoi ming the acoustic data stream in each of the plurality of segments so as to produce a plurality of frequenc) spectra wherein each frequenc) spectrum is representative of one of the plural ity of segments, transfoi ming each frequency specti um so as to produce a plurality of magnitude bins in each segment, determining a sum of lower frequency magnitude bins w ithin a predetermined lower frequency range and a sum of higher frequency magnitude bins within a ptedetermined higher frequency range within a sampling ot the plurality segments dividing the sum of higher frequency magnitude bins by the sum of lower frequency magnitude bins in the sampling so as to produce a mean bands ratio, detei mining a sum of lower frequency magnitude bins and a sum of higher frequency magnitude bins within a given segment, dividing the sum of higher frequency magnitude bins by the sum of lower frequency magnitude bins within said given segment so as to produce a first bands ratio, comparing said mean bands ratio to said first bands ratio and detei mining whether said first bands ratio is greater or less than said mean bands ratio by at least a predetermined multiplier so as to determine if said given segment is an inspiration phase or an expiration phase of the breathing cycle An information relay module in communication with the at least one processor for providing the transformed data to an operator as first indicia representing inspiration and expiration is also provided

5 TRI-MP2/PCT |00 I 9| In some exemplai y embodiments the apparatus fui ther comprises a sensor for sensing respiratory movements of an abdomen or l ib region of the indiudual and generating a signal indicative thereof The processor is opei ative to receive the signal and to identity respirator} expansion during inspiration and respiratory conti action during expiration T he information relay is operable to provide data to an operator generated as second indicia representing the i espiratory movements

[0020| In some exemplary embodiments, the infoi mation i elay module is provided as a display module for displaying the ti ansformed data as a processed v\ ave amplitude vei sus time plot The inspiration phases are identifiable by rising regions of said processed wave amplitude vei sus time plot and the expiration phases are identifiable by falling regions of said processed wave ampl itude vei sus time plot In some exemplary embodiments the information relay module is operable so as to prov ide an operator audio cues representing the inspiration and expiration phases of an individual s breathing In some exemplary embodiments the infoi mation relay module is provided as a display module operable for displaying visual cues representing the inspiration and expiration phases of an individual s breathing In some exemplary embodiments the information relay module is operable so as to provide an operator printed visual indicia representing the inspiration and expiration phases of an individual s breathing

|0021 1 In some exemplary embodiments, the breathing sounds are collected b> at least a first microphone and a second mici ophone The first microphone is operable to collect acoustic signal data breathing sounds and airflow sounds resultant from the individual's breathing applying air pressure to a diaphragm of the first microphone and the second microphone is operable to collect acoustic signal data breathing sounds of the individual In some exemplary embodiments, the acoustic signal data collected by the second microphone are subtracted from the acoustic signal data collected by the fϊi st microphone so as to provide an acoustic signal data recording of substantially airflow sounds of the individual

TRI-MP2/PC r |0022] In some exemplary embodiments the at least one microphone is prov ided in a structure including one or moi e openings sufficient to reduce an flow resistance and be substantial!} devoid of dead space

[0023| In another exemplar} embodiment ther e is provided an apparatus toi transforming acoustic signal data bi eathing sounds into a graphical repi esentation indicative of breathing cycle phases including inspiration phases and expiration phases The appai dtus comprises at least one m ici ophone for collecting acoustic signal data resultant from the breathing of an individual during a given time period and an acoustic signal data digitizing module for receiving and digitizing sounds via a ti ansducing link fi om the at least one microphone The audio signal digitizing module is operable to produce an acoustic data stream plot representative of w ave ampl itude versus time A module for segmenting a plural ity of ad|acent audio samples from the acoustic data stream plot into a plur al ity of segments of a predetermined length of time is provided A module foi transforming the acoustic data sti eam in each of the plui al ity of segment so as to produce a plurality of frequency spectra wherein each frequency spectrum is representative of one of the plurality of segments is provided A module for transforming each frequency specti um so as to produce a plurality of magnitude bins in each segment is provided A module for determining a sum of lower frequency magnitude bins w ithin a predetermined low ei fi equency range and a sum of higher frequency magnitude bins within a predetermined higher frequency range within a sampling of the plurality segments is provided A module for dividing the sum of higher fi equency magnitude bins by the sum of low er frequency magnitude bins in the sampling of the plurality of segments so as to produce a mean bands ratio is provided A module for determining a sum of lower frequency magnitude bins and a sum of higher frequency magnitude bins within a given segment is provided A module for dividing the sum of higher frequency magnitude bins by the sum of lower frequency magnitude within said given segment so as to produce a first bands ratio is provided A module for comparing said mean bands ratio to said first bands ratio and determining whether said first bands ratio is greater or less than said mean bands ratio by at least a predetermined multiplier so as to determine if said given segment is an inspiration phase or an expiration

7 TRI-MP2/PCT phase of the breathing c\ cle is provided An information rely module in communication with the module for comparing said mean bands ratio to said fii st bands ratio for providing the ti anstormed data to an operator as indicia repi esenting inspiration and expiration

[0024| In > et another exemplary embodiment there is prov ided a computei implemented apparatus for transforming acoustic signal data breathing sounds into a graphical repi esentation indicative of breathing cycle phases including inspiration phases and expiration phases The apparatus comprises at least one microphone for collecting acoustic signal data bi eathing sounds resultant from the breathing of an individual during a given time period and an acoustic signal data digitizing module for receiving and digitizing sounds via a tr ansducing link from the at least one microphone The audio signal digitizing module is operable to pi oduce an acoustic data stream plot representative of a w ave amplitude versus time At least one processoi operable for receiving the acoustic data stream plot is pr ov ided The processor is configured for segmenting a plurality of ad|acent audio samples fi om the acoustic data stream plot into a plurality of segments of a predetermined length of time transforming the acoustic data stream in each of the plurality of segments so as to produce a plui alit> of fi equency spectra wherein each frequency spectrum is representative of one of the plurality of segments ti ansforming each frequenc} spectrum so as to produce a plurality of magnitude bins in each segment determining a sum of lower frequency magnitude bins within a predetermined lower frequency range and a sum of higher frequency magnitude bins within a predetermined higher frequency range within a sampling of the plurality segments dividing the sum of higher frequency magnitude bins by the sum of lower frequency magnitude bins in the sampling of the plurality of segments so as to produce a mean bands ratio determining a sum of lower frequency magnitude bins and a sum of higher frequency magnitude bins within a given segment, dividing the sum of higher frequency magnitude bins by the sum of lower frequency magnitude bins within said given segment so as to produce a first bands ratio, comparing said mean bands ratio to said first bands ratio and determining whether said first bands ratio is greater or less than said mean bands ratio by at least a predetermined multiplier so as to determine if said given segment is an inspiration phase or an expiration

8

TRI-MP2/PC I phase of the breathing cycle An information iel\ module in communication w ith the at least one processoi for providing the tiansformed data to an operatoi as indicia representing inspiration and expiration is also provided

|0025] In still another exemplary embodiment there is provided a method foi processing acoustic signal data for use in monitoring a breathing c>cle of an individual The method comprises generating a data set representative ol an acoustic data stieam plot of wave amplitude versus time The data set originating from bi eathing sounds of an individual 1 he acoustic data stream plot is transformed to yield at least one relatively higher frequency spectral chai acteπstic and at least one lelatively lower frequency, spectral characteristic A proportional value oi the relatively higher frequency spectral characteristics to the relatively lowei frequency spectral charactei istics is determined, and least fiist output indicative ot an inspirational breathing phase according to a first iange of the proportional value and or at least one second output indicative of an expirational breathing phase according to a second range of the second proportional value is generated

|0026] In yet another exemplary embodiment there is provided a de\ ice tor processing acoustic signal data for use in monitoring a breathing cycle of an individual The device comprises a means for generating a data set representative of an acoustic data stieam plot of wave amplitude versus time The data set originating from breathing sounds of an individual Means for transforming the acoustic data stream plot to yield at least one relatively higher frequency spectral characteristic and at least one relatively lower frequency spectral characteristic is provided Means for determining a proportional value of the relatively higher frequency spectral characteristic to the relatively lower frequency spectral characteristic is provided and means for generating at least first output indicative of an inspirational breathing phase according to a first range of the proportional value and/or at least one second output indicative of an expirational breathing phase according to a second range of the second proportional value is provided

TRI-MP2/PCT [0027] In still another exemplary embodiment there is provided a method for processing acoustic signal data for use in monitoring inspirational and expirational phases of a bieathing cycle of an individual The method comprises generating a data set representative of an acoustic data stream plot of wave amplitude versus time The data set originating Ii om breathing sounds of an individual The acoustic data stream plot is transformed to yield inspiiational spectral data for at least one inspirational phase and expirational spectral data for at least one expirational phase and the shape of the inspirational and expirational frequency spectra tor tracking bieathing activities is character ized to identify inspirational and expirational breathing phases in subsequent bieathing cycles

[0028] In another exemplary embodiment there is provided a device for processing acoustic signal data for use in monitoring inspirational and expnational phases of a breathing cycle of an individual The device comprises means for generating a data set representative of an acoustic data stream plot of wave amplitude versus time The data set originating from breathing sounds of an individual Means for transforming the acoustic data stream plot to \ ield inspirational spectral data for at least one inspirational phase and expirational spectral data for at least one expirational phase as piovided and means for characterizing the shape of the inspirational and expirational frequency spectia for tracking breathing activities to identify inspirational and expirational breathing phases in subsequent breathing cycles is also provided

BRIEF DESCRIPTION OF THE FIGURES

|0029] Several embodiments of the present disclosure will be provided, by way of examples only, with reference to the appended drawings, wherein

|0030| Figure 1 is a plot of an exemplary microphone response curve of an exemplary embodiment,

10

TRI-MP2/PCT |00311 I igure 2a is side view of an exemplary embodiment of a miciophone and transducer set-up on an individual wherein the microphone is attached to a face mask located on the front of an individual s face,

|0032| figure 2b is side view of an exemplary embodiment of a 2-mιcrophone and transducer set-up on an individual wherein the microphones ai e attached to a face mask located on the front of an individual s face

[0033| f igure 3 is a schematic computer s\ stem in accordance w ith an apparatus for transfoi ming breathing sounds in inspiration and expiration phases

|0034| I igure 4 is a block diagram of a computer system in accordance with the apparatus of figure

4,

[0035| F igure 5 is a digitized ιaw data wave plot lepresentative of bieathing sound amplitude versus time,

|0036| Figure 6a is an exemplary set-up of Respiratory Inductance Plethysmogrphy (RIP) on an individual and the microphone and transducer equipment of figures 2a and 2b,

|0037] Figure 6b is an exemplary plot of 2^-SCCOiId long recording of breathing sounds and simultaneous RIP signals from a representative individual wherein the dashed line indicates the sepaiation of inspiration and expiration cycles,

|0038] Figure 7a is a representative digitized raw data breathing sound amplitude versus time plot of a single breathing cycle with the three phases of respiration,

|0039| Figure 7b is a representative frequency spectrum of the inspiration phase of figure 7a,

1 1

TRI-MP2/PCT |0040| Figure 7c is a representative frequency spectrum of the expiration phase of figui e 7a

[0041 1 Figure 8a is a representative plot of the average frequency magnitude spectrum and standard deviations of breathing sounds for inspiration in an individual

[0042| F igure 8b is a representative plot of the average frequency magnitude spectrum and standard deviations of breathing sounds for expiiation in an individual,

[0043) Figure 9 is a flow diagram of the method for monitoring identifying and determining the breathing phases from breathing sound data

|0044| Figure I Oa is representative amplitude versus time plot of breathing sound data and simultaneous RIP data, and

[0045] Figure 10b is a comparative plot of the RIP data of figure 10a and the breathing phases found using the method of figure 9 for monitoring identify ing and determining bi eathing phases wherein the positive values of the dashed line represent inspiration and the negative values of the dashed line repi esent expiration

DESCRIPTION OF THE PREFERRED EMBODIMENTS

|0046| It should be understood that the disclosure is not limited in its application to the details of construction and the arrangement of components set forth in the following description or illustrated in the drawings The disclosure is capable of other embodiments and of being practiced or of being carried out in various ways Also, it is to be understood that the phraseology and terminology used herein is for the

12

TRI-MP2/PCT purpose of description and should not be iegaided as limiting The use of "including " "compr ising " or "having" and variations thereof herein is meant to encompass the items listed thereafter and equivalents thereof as well as additional items Unless limited otherwise the terms "connected," "coupled ' and "mounted " and variations thereof heiein are used broadly and encompass direct and indirect connections, couplings and mountings In addition the terms "connected" and "coupled" and variations theieof are not restricted to physical or mechanical oi electi ical connections or couplings Furthermore and as described in subsequent paragraphs, the specific mechanical or electrical configurations illustrated in the draw ings are intended to exemplify embodiments of the disclosure However othei alternative mechanical or electrical configurations are possible which ai e considered to be within the teachings of the instant disclosure Furthermore, unless otherwise indicated the term "or" is to be considered inclusive

[0047] With reference to the disclosuie herein and the appended figures, a method foi monitoring identifying and/or determining charactei istics of an individual s breathing, including bieathing phases thereof is henceforth described using a piocessed acoustic signal data stream collected and 01 recorded waveform data In one example the waveform data is collected from or is associated w ith breathing sounds and other sounds from one or more microphones or othei sound wave collecting equivalents thereof

|0048| In this case the system and method may involve the use of a control unit, in which some or all of its associated components are computer implemented that may be provided in a number of forms They may be embodied in a software progiam configured to run on one or more general purpose computers, such as a personal computer, or on a single custom built computer, such as a programmed logic controller (PLC) which is dedicated to the function of the system alone The system may, alternatively, be executed on a more substantial computer mainframe The general purpose computer may work within a network involving several general purpose computers, for example those sold under the trade names APPLE or

13

TRI MP2/PCT IBM oi clones thereof which aie programmed w ith operating sv stems known by the trade names WINDOW S™, LINUX™ MAC O S™ or other well known oi lessei known equivalents of these The system ma) involve pre-programmed software using a numbei of possible languages or a custom designed version of a programming softwart sold under the trade name ACCESS or other programming software The computer network may be a w ned local area network or a w ide area network such as the Internet or a combination of the two, with or w ithout added security, authentication protocols, or under peer-to-peer' or "client-server ' or other networking aichitectures The network may also be a wireless netwoi k or a combination of wired and wireless networks The wireless netwoi k ma) operate undei fi equencies such as those dubbed radio frequenc) oi Rf using piotocols such as the 802 I I TCP/IP, Bf UL TOOTH and the like 01 other well known lntei net wireless, satellite or cell packet protocols Also the pi esent method maj also be implemented using a microprocessor-based battery powered device

[0049] FIG 3 shows a genei al computer system on which embodiments may be practiced The geneial computer system comprises information relay module ( M ) In some embodiments the information relay module ( 1 1 ) comprises a means for providing audible cues, such as speakei s In some embodiments, the information relav module is comprised of a display device or module ( 1 1 ) w ith a display screen ( 1 2) Examples of display dev ice are Cathode Ray l ube (C RT) devices, Liquid Cry stal Display (LCD) Devices etc The general computer system can also have other additional output devices like a printer The cabinet ( 1 3) houses the additional basic components of the general computei system such as the microprocessor, memory and disk drives In a general computer system the microprocessor is any commercially available processor of which x86 processors from Intel and 680X0 series from Motorola are examples Many other microprocessors are available The general computer system could be a single processor system or may use two or more processors on a single system or over a network The microprocessor for its functioning uses a volatile memory that is a random access memory such as dynamic random access memory (DRAM) or static memory (SRAM) The disk drives are the permanent storage medium used by the general computer system This permanent storage could be a magnetic disk, a flash

14

TRI-MP2/PC I memory and a tape This storage could be removable like a floppy disk or permanent such as a hard disk Besides this the cabinet ( 1 3) can also house other additional components like a Compact Disc Read Only Memory (CD-ROM) drive sound caid, video card etc The general computer system also includes various input devices such as for example a keyboard ( I 4) and a mouse ( 1 5) The keyboard and the mouse are connected to the general computei sy stem through w ired oi v\ ireless links The mouse ( M) could be a two- button mouse three-button mouse or a scioll mouse Besides the said input devices thei e could be other input devices like a light pen a track ball, etc The micropiocessor executes a program called the operating system for the basic functioning of the general computer sy stem T he examples of opeiating systems are UNIX™. WINDOWS™ and OS X™ These operating sy stems allocate the computer s\ stem resources to various programs and help the users to inteiact with the sy stem It should be undei stood that the disclosure is not limited to any particular hardware comprising the computer system or the softwaie i unning on it

[0050] FIG 4 shows the internal structure of the general computer system of F IG 3 The general computer system (2 1 ) includes various subsystems interconnected with the help of a system bus (2 2) The microprocessor (2 3) communicates and controls the functioning of other subsystems Memoiy (2 4) helps the microprocessor in its functioning by storing instructions and data during its execution Fixed Drive (2 5) is used to hold the data and instructions permanent in nature like the operating system and other programs Display adapter (2 6) is used as an interface between the system bus and the display device (2 7). which is generally a monitor The netw oik interface (2 8) is used to connect the computer with othei computers on a network through wired or wireless means The system is connected to various input devices like keyboard (2 10) and mouse (2 1 1 ) and output devices like a printer (2 12) oi speakers Various configurations of these subsystems are possible It should also be noted that a system implementing exemplary embodiments may use less or more number of the subsystems than described above The computer screen which displays the recommendation results can also be a separate computer system than that which contains components such as database 360 and the other modules described above

15

TRI-MP2/PC1 [00511 The method in accordance with the instant disclosure, provides a microphone 12 located in a position pioximal to an individual s mouth as shown in PIGS 2a and 2b in this case b\ a dimension A of approximately 3 cm in front of the individual's face 1 he miciophone 12 ma) be configured to communicate with the microprocessor by way of an intei tace oi other data acquisition system, via a signal transducing link or data path 18 to provide one or more data collection modules w ith the miciophone 12 T hus such data collection modules and the microphone are operable to collect breathing sounds emanating from the individual's mouth and nose, during the inspiration and/or expiration phases of breathing For example, an exemplar) microphone response curve is show n in PIG 1 The acoustic signal data breathing sounds collected from the indiv idual may be comprised of both airflow sounds from the individual's breathing applying air pressuie to the microphone diaphiagm and actual breathing sounds iesultant from the individual's breathing being recorded and/or collected by the microphone 12 I urthermore, the acoustic signal data breathing sounds collected from the individual may be, in another exemplarx embodiment, comprised of substantially only actual sounds resultant from the individual's breathing being recorded and or collected by the microphone 12 In still yet another embodiment, the acoustic signal data breathing sounds collected from the individual may be comprised of substantially only airflow sounds resultant from the individual's breathing appl> ing air pressure to the miciophone diaphragm and being recorded and/or collected by the microphone 12 As used hereinaftei term airflow sounds" refers to the air pressure resultant fiom an individual's breathing being applied to and causing the microphone s diaphragm to move such that the microphone collects and produces data for the audio recording

[0052) The microphone 12 for example, may be coupled in or to a loose fitting full face mask 16 as shown in F IGS 2a and 2b Furthermore, the face mask 16 may include at least one opening 14 to allow for ease of breathing of an individual 20 For example, the microphone 12 may be in a fixed location with a spacing of dimension "A", of about 3 cm in front of the individual's face as shown schematically in FIG 2a, however other distances in front of the individual's face may be desirable in some embodiments The

16

ΓRI-MP2/PCT microphone 12 in this case is embedded in a i espn atoiy mask 16 w hich is modified b\ cutting away material so as produce opening 14 such that onl\ a striictui al frame portion remains to keep the microphone 12 in a fixed location relative the nostrils and the mouth of an individual 20 In one example, the audio signals from the microphone may be digitized using an audio signal digitizing module and digitized sound data to be transferred via transducing link 18 to the computer using a USB preamplifier and audio interface (M-Audio Model Fast 1 l ack Pro USB) with a sampling i ate of 22,050 Hz and i esolution of 16 bits Although various types of audio interfaces may be used in the instant exemplars embodiment, an external audio intei face provides suitable results over the other ts pes of audio adapters foi example, built-in audio adapters due to the superior signal to noise (S/N) ratio of the external adaptor w hich is about 60 dB at I kHz Sound recordings mas then be passed through a 4'¹' order band-stop digital fi lter w ith a centre frequenc> of about 60 Hz to suppress line intei fei ence Othei structures may also be used to locate the microphone in position as including support structui es positioned against a plural ity of locations on the individual or stationed ad|acent the individual as l equired

100531 Furthermore, in another exemplary embodiment, a two microphone system may be useful In such a system, as shown in I IG 2b, one of the microphones a first microphone 12b, may be configured to collect actual breathing sounds and airflow sounds w hereas the other microphone a second microphone 12c may be configured to collect substantially only actual bi eathing sounds In this embodiment, the waveform sounds and/oi data collected from the second microphone 12c may be subtracted or filtered from the waveform sounds collected from the first mici ophone 12b, thereby resulting in a waveform data stream of substantially only airflow sounds The airflow sounds may be resultant of pressure air from an individual's breathing being collected as applied to the diaphragm of a microphone as noted above Subsequently, the airflow sounds may then be used as a waveform amplitude acoustic data stream in accordance with the forgoing method

17 TR1-MP2/PCT [0054| A raw acoustic data sti eam ot bi eathing sounds as shown in a representative plot for example in FIG 5 is then collected for each of a plui alitv of respirator) phases to form a bioacoustics signal recording w hei ein the acoustic data sti eam is subsequently transformed

|0055] As w ill be described below, in at least one embodiment a method and an apparatus are provided to monitoi identify and determine the inspir atory and or expiraton phases of the respiratory cycle of an individual 20 from the frequency chai actei istics bi eathing sounds It is understood that a numerical comparative analysis of the frequency spectrum as transformed from waveform amplitude data of breathing sounds and/or airflow sounds of an individual 20 mav be useful to differentiate between the inspiration and expiration phases of breathing

DATA ACQUISITION

|0056] Data were collected from 10 consecutive men and women at least 1 8 vears of age referred foi overnight polysomnogi aphy (PSG) The subjects chai acteristics are shown in Table I Breath sounds were recorded by a cardoid condenser microphone (Audi-Technica condenser microphone Model PRO 35x) The microphone s cardioid polar pattern reduces pickup of sounds from the sides and rear improving isolation of the sound source The microphone 12 used for recording breath sounds has a relatively flat frequency response up to 2000 Hz as shown in FIG 1 Furthermore the microphone 12 as used herein has a higher output when sound is perpendicular to the microphone's diaphragm as show n by the solid line in FIG 1 w hich helps reduce low frequency ambient noise interference The microphone 12 was embedded in the centre of a loose fitting full face mask 16 modified to reduce airflow resistance and eliminate dead space by way of large openings 14 as shown in FIGS 2a and 2b The microphone 12 attached to the face mask 16 and was is located in front of the individual's face The mask 16 provides a structural frame portion to keep the microphone in a fixed location, at a dimension A of approximately 3 cm in front of the individual's face so as to record breathing sounds to an audio recording device, such as a computer as described above, to make an audio recording thereof In some exemplary embodiments the

18 TRl MP2/PC ) audio recording of breathing sounds may be made and recorded in analog format prior to digitizing the audio recording However, in other embodiments the audio recording ot breathing sounds ma) be digitized in real-time Furthermore in some exemplary embodiments the processing ot the audibly recorded waveform data or acoustic signal data may be pei iormed in real-time, so as to provide substantially instantaneous information regarding an individual s bieathing In an exemplarv embodiment, digitized sound data were transferred to a computer using a USB pieamplifier and audio interface (M-Audio Model MobilePre USB) with a sampling rate of 22 0*>0 Hz and resolution ot 16 bits Although various types of audio interfaces may be used, in the instant exemplary embodiment, an external audio interface was preferred over a built-in audio adapter due to the better signal to noise (S'N) iatio of the external audio interface, which was 91 dB TIG 5 shows a 2vsecond waveform amplitude recording plot However in other exemplary embodiments, it may be desirable to record breathing sounds for a time period of from about I O seconds to 8 hours In some exemplaiy embodiments it may be desirable to record breathing sounds for a time period of from about 10 second to about 20 minutes In othei exemplary embodiments it may be desirable to iecord breathing sounds for greater than 20 minutes

BREATHING ACOUSTICS ANALYSIS

|0057| In an exemplary embodiment full night breath sound recordings were displayed on a computer screen similai to the computer screen I 2 of FIG 3 A representative raw acoustic data waveform plot, as may be shown on a computer screen I 2, is provided in FIG 5 for a 25-second recording Each increase in amplitude represents a single breath The individual phases of a breathing cycle are not readily resolvable in FIG 5 owing to the time scale being too large to resolve single breath details For example, FIG 7a more clearly shows the inspiration and expnation phases of a breathing cycle in a waveform amplitude versus time plot The recordings were visually scanned to identify periods of regular breathing After visual scanning, the recordings were played back for auditory analysis

19 TRI-MP2/PCT |0058] Sequences of normal breaths that did not have signs of obstructive breathing such as snoi ing and interruptions or other irregularities such as tachypnea (rapid breathing) or hyperventilation (deep breathing) were then included in the subsequent frequency analysis I his pi otess was repeated to select three random parts of an individual's sleep If a portion of the recording fulfilled the aforementioned inclusion criteria then 3 to 4 consecutive bieaths were selected from that poition A total of I O breaths were selected from each individual Dui ing the process of selecting the individual's breathing sound portions the investigator did not have a pre\ ious knowledge of the sleep stage Therefore, the investigator was blind to the sleep stage of an individual w hile selecting the analyzed bi eaths except for know ing that sampling started after the onset of sleep The real-time stamp of each breath was registered in ordei to retrieve the sleep stage in which it took plact in afterwards Subsequently the investigator listened to these breathing sounds again to divide each breath into its inspiratory expiratoiy and interbreath phases bach phase was labeled manually

|0059| The data array of each breathing phase was passed through a hamming window and a 2048- point Fast Fourier Transform (FFT) of the w indowed data with 50% overlap was calculated The resultant frequency spectrum was displayed on a computei screen for visual analysis Fhe frequency spectra of the interbreath pauses were also calculated and incoi porated in the analysis to control for the effect of ambient noise Careful visual examination of spectra revealed that during inspiration the amplitude of signals above 400 Hz was consistently higher than during expnation Therefore, it was determined that the bands ratio (BR) of frequency magnitude between 400 to 1000 Hz, to frequency magnitude between 10 to 400 Hz is higher in the inspiration phase as compaied to the expiration phase The BR of each breathing cycle was then calculated using equation ( 1 )

1000// 400//

BR = ∑ FFTU)I ∑FFT( f) (1)

400« 1OW

20 1 RI-MP2/PCT [0060] Using equation ( 1 ) the numei atoi i epresents the sum of FF T higher frequency magnitude bins which lie betw een 400 and 1000 Hz and the denominator represents the sum ot FFT lower frequency magnitude bins w hich lie between 10 and 400 H/ Bins bel low 10 Hz wei e not included to avoid anv DC contamination (referring to drift from a base l ine) and frequencies above 1000 Hz were not included since preliminary work (not show n) revealed insignificant spectral power at frequencies above 1000 Hz Therefoi e the computation may also be i educed To verify repeatability of the results BR was calculated for 3 to 4 successive breaths in the included sequence and for a total of three sequences from diffei ent parts of the individual s sleep A total of 100 bi eaths w ere collected from the 10 subjects The mean numbei of breaths per subiect was 1 O i- O

SLEEP STAGING

|0061 1 Sleep stages were recoi ded dui ing the course of the night using standard polysomnography techniques that included electro-encephalogi aph) (EEG), electro-oculography and submental electromyography (Rechtschaffen A and Kales A 1968 4 Manual of Standai dized Tei nunology Technic/ia s and Scoring Sy stem foi Sleep Stages of Human Sub/etts (Los Angeles UC I A Brain Information Service Brain Research Institute) The coπ esponding sleep stage for the selected breath samples was determined from the PSG recording (not shown)

STATISTICAL ANALYSIS

[0062| Data are expressed as mean±SD unless otherwise stated A Wilcoxon Signed Ranks Test was performed using SPSS statistical package (SPSS Chicago, Illinois) This test compares two related variables drawn from non-normally distributed populations One-sample sing test was performed using Minitab 15 statistical package (Minitab Inc State College, PA)

COMPARISION OF BANDS RATIO TO RESPIRATORY INDUCTANCE PLETHYSMOGRAPHY SUBJECTS

21 TRI-MP2/PCT [0063] Healthy subjects at least 1 8 v eai s of age w ere recruited w ith no history of respiratorv oi cardiopulmonary disease in addition to being free from prescribed medications Data w ere collected fi om 15 subjects 6 men and 9 women health\ volunteers Individuals used in the study were reci uited b\ advertisement and w ere divided randomlv intro 2 groups with 5 sub|ects in one group (test group) and 10 in the other (validation group) The data fi om the S subjects in the test group were used to examine acoustic characteristics of breathing phases w hich w ere then incorporated into a method having an algorithm as described below The resultant method w as tested on the data of 10 sub|ects in the validation group to determine the validity of the method foi determining the inspiration and expiration phases of an individual s bi eathing sounds

BREATH SOUND RECORDING

|0064| Bi eath sounds were recorded using a unidirectional electi et condenser microphone ( Know les

Acoustics Model MB6052USZ-2) 1 he microphone s unidirectional pattern reduces the pickup of sounds from the sides and rear thereby improving isolation of the sound source The microphone 12 was embedded in a respiratory mask 16 that was modified b\ cutting away material so as to produce opening 14 such that only a structural frame remained to keep the microphone 12 in a fixed location relative the nostrils and the mouth of an individual 20 at a dimension A of approximately 3 cm in front of the individual s face as shown in FIG 2a The audio signal was digitized using an audio signal digitizing module and digitized sound data w ere transferred via transducing link 18 to a computer using a USB preamplifier and audio interface (M-Audio Model Fast Track Pro USB) with a sampling rate of 22 050 Hz and resolution of 16 bits Although various types of audio interfaces may be used, in the instant exemplary embodiment, an external audio interface was preferred ovei the other types of audio adapters, for example, built-in audio adapters due to the superior signal to noise (S TM) ratio of the external adaptoi which was about 60 dB at I kHz Sound recordings were then passed through a 4^th order band-stop digital filter with a centre frequency of about 60 Hz to suppress line interference

22 TRI-MP2/PCT RESPIRATORY INDUCTANCF PL I 1 1 IYSMOGRAPHY

[0065| Respirator} inductance plethy smography (RIP) (Respitiace Ambulatory Monitoi ing Inc

White Plains NY USA) was used to monitor respiratory pattern ot individuals and the timing oi the breathing phases In contiast to other bi eathing monitoring appaiatus such as pneumotacographv RIP has the advantage of being applied away from the face of an individual to allow capture of bieathing phases Briefly RIP is a system comprising two flexible sinusoidal w ires Each w ire is embedded in stretchy fabric band One band 28 is placed around the chest of an individual and the other band 30 is placed around the abdomen of the individual as shown in I IG 6a The inductance of each band changes upon πb cage and abdomen displacements and generates a voltage signal proportional to its inductance The signals from the RIP bands 28 and 30 were digitized at I 50 Hz and stored in a computer memory as substantial describe above w ith reference to FIGS 3 and 4 The electrical sum of the ribcage and abdominal signals is displayed on a readable medium for example a computer screen or a ph> sιcal plot and provides the total thoracoabdominal displacement The thoiacoabdominal displacement iecorded from the Rl P s\stem reflects changes of tidal volume during respiration

|0066] In ordei to compare the inspiration and expiration phases of an individual's breathing to RIP the microphone 12 as noted above was coupled to a modified mask 16 in front of the subject s face Simultaneously the RIP bands 28 and 30 were placed around the sub|ect s chest and abdomen to measure thoracoabdominal motion as noted above Recording were captured fiom both the microphone 12 and the RIP bands 28 and 30 simultaneously to assess the timing of breath sounds against the RIP waveform data

STUDY PROTOCOL

|0067] Individuals were studied in the supine position and were instructed to breathe normally

Microphone holding frame 16 was placed on individual's face Each individual was asked to breath for two minutes at their regular breathing rate In order to mimic all possible breathing conditions, the individuals were asked to breath through their nose only for half of the experiment time, and through their nose while

23 TRI-MP2/PC r mouth v\as slightly open in the other half Incomplete breaths at the beginning and end ot recording were discarded and all the breaths in between were included in the anah sis

ANALYSIS OF BREATH ACOUSI ICS

|0068| In a first stage, spectral variables of breath sounds that characterize the inspιi atoι \ and expiratoiy phase components of a respiratory cycle were determined The data of five sublets 3 females and 2 males was chosen randomly from total 15 subjects and used to study the frequency chai acteπstics of the acoustic signals of different respiratoiy phases Inspiraton and e\pιrator> segments of bieath sounds were determined and extracted horn the acoustic data b> comparing it to the inspiratory (i ising edge) and expιιatoι\ (falling edge) of the RIP tiace as shown in FIG 6b A 25-second long recoiding ot breath sounds and simultaneous summed thoiacoabdominal RIP signals fiom a representative sub|ect is show n, for example in FIG 6b Dashed vertical lines are shown to sepaiate inspiration and expiration phases of the second c>cle at 32

|0069| I he first 10 complete breaths of each subject were analyzed which yielded a total of 50 inspirations and 50 expirations acoustic data sets from the 5 subjects Subsequently, the frequency spectrum of each phase was calculated separateh using Welch's method (ι e the average of a 2048-point Fast Fourier Transform (FFT) of sliding hamming windows with 50% overlap) FFT arrays were normalized in amplitude in order to compare the relative changes in power spectium among resultant spectral arrays

|0070| Using variables derived from frequency spectra of the 5 test individual's noted above, the inspiratory and expiratory phases of the breathing cycle were determined for the remaining 10 individuals in order to test the validity of the method Furthermore, the method was tested for the ability to determine breathing phases from acoustic data independently from other inputs The data analysis was performed with Matlab R2007b software package (Mathworks, Natick, Massachusetts)

24 I RI-MP2/PCT RF- SU L TS

[00711 The characteristics ot the individuals in this stud\ are shown in Table 1 A total of 100 breaths were sampled fiom 10 patients w ith a mean number of 10 breaths per sub|ect Sevent\ percent of the breaths analyzed were from non-rapid-eye movement sleep (NREM) and 18% from rapid eve movement sleep (REM) and 12% while patients were awake according to the pol>somnographic criteria

Table 1. Characteristics ol sublets

Subject Age (years) Sex Bod\ Mass Index

Subject 1 5 1 r 39 1

Subject 2 43 M 25 6

Subject 3 49 M 23 7

Subject 4 27 M 36 8

Subject 5 64 M 26 3

Subject 6 60 M 33 0

Subject 7 68 r 28 5

Subject 8 3 1 M 30 3

Subject 9 48 F 3 1 6

Subject 10 56 M 26 7

[0072] The bands ratio (BR) value was calculated for the inspiration phase bands ratio (BRi) 24, the expiration phase bands ratio (BRe) 26, and the interbreath pause bands ratio (BRp) 22 using equation 1 Inspiration and expiration showed consistent patterns of their frequency spectra as depicted in FlG 7a for a given breathing cycle

25

TRI-MP2/PC r ]00731 As shown in a repiesentative example in FKJ 7b, there was a sharp narrow band of harmonics usuall} below 200Hz for inspiration The spectium exhibited a valley between 200Hz and 400Hz and a peak again after 400Hz as shown in FIG 7b Another vanation ot the inspirator} specti um was the same initial narrow band followed b> a telatively smooth spectrum w ithout the 400 Hz drop (not shown) The expiratory spectrum, as shown in a representative example in FIG 7c on the other hand ioi med a wider band that spanned frequencies up to 500Hz and whose powei di opped off rapidly above this frequency The inspiratory spectrum (F IG 7b) showed a peak close to the line frequency The spectrum of the interbreath pause (not shown) was inconsistent and showed random variations without an\ consistent pattern To rule out the effect ot line frequency on inspiiation bands ratio (BRi). a Wilcoxon signed rank test was used to test the relation between BRi and bands ratio intei breath pause (BRp) Fhe test was significant (p<0 001 ), thus it was determined that BRi is dilfei ent from BRp and that line interference does not significantl} contribute to the frequenc} spectrum ot inspiration

[0074| The relationship between BRi and BRe was examined using the Wilcoxon Signed Ranks Test

The test showed that a BRi is not equal to BRe (P<0 001 ) w ith 95% of breathes having BRi greater than BRe Since minute differences between BRi and BRe might be atti ibuted to randomness two thresholds of 50°o and 100% difference between BRi and BRe were tested The ratio BRi/BRe was calculated for each breath By taking the ratio, BRi and BRe may be treated as dependant pairs These ratios were then tested foi being greater than 1 5 (50% difference) and greater than 2 ( 100% difference) The one-sample sign test showed that BRi/BRe is greater than I 5 (p<0 001 ) and greater than 2 (p<0 001 ) In order to account for potential differences between subjects in the analysis, the mean BRi/BRe was calculated for each individual subject as displayed in Table 2 The one-sample sign test of the median was significant for mean BRi/BRe greater than 1 5 (p=0 001 ) and significant for mean BRi/ B Re greater than 2 (p=0 001 ) Breaths that were drawn when subjects were polysomnographically awake did not differ significantly in terms of BRi/BRe from the rest of breaths (p=0 958) and, therefore, were included in the aforementioned analysis

26

TRI-MP2/PCT Table 2. Mean BRi BRe tor the sub|ects

Subiect Mean BRi BRe (value±SD)

Subiect 1 1 66 t 0 60

Subiect 2 2 30 i 1 33

Subject 2 43 t 0 71

Subject 4 3 17 i 1 17

Subject 5 2 67 i 1 60

Subiect 6 3 86 i 2 65

Sub|ect 7 23 01 9 65

Subiect 8 14 99 J 8 86

Sub|ect 9 I S 66 9 42

Subiect 10 1 1 56 t 2 60

|00751 The sensitivity of this method was tested loi each of the two cut-offs Out of 100 breath samples, 90 had BRi 50% greater than BRe and 72 had BRi 100% greater than BRe thereb> giving an overall sensitivity of 90% and 72% lespectively

|0076| A total of 346 breaths met the inclusion cπtena The average number ot breaths per individual was 23 0 t 7 79 Only the first 10 complete breaths w ere used to study the spectral frequency characteristics from the 5 individuals in the test gi oup From the validation group 218 breaths (l e 436 phases) were included in the analysis with an average of 21 8 ± 8 2 breaths per subject

ANALYSIS OF BREATH SOUNDS

|0077| Data obtained from the test group of 5 individuals yielded 100 arrays of FFT magnitude bins normalized in amplitude with one half being from inspiratory acoustic inputs or phases and the other half

27 TRI-MP2/PCT from expiratory acoustic inputs or phases The average spectrum of all normalized array s belonging to the inspiration and expiration phases w ith the corresponding standard deviation are shown in FIGS 8a and 8b respectively FIGS 8a and 8b demonstrate that the irequency spectra of the 2 phases have different energy disti ibutions The mean inspiratory spectrum, shown in FIG 8a peaked between 30 Hz and 270 Hz The spectrum exhibited flatness between 300 Hz and 1 100 Hz before the next ma|or peak with a center frequency of 1400 Hz The expiratory spectrum on the other hand peaked between 30 to 180 Hz as shown in FlG 8b Its power dropped off exponentially until SOO Hz after which it flattened at low power

|0078| The signal power above 500 Hz was consistent!) higher in inspiration than expiration Since the ratio of frequency magnitudes between SOO to 2500 Hz the higher frequenc\ magnitude bins, to frequency magnitude between 0 to 500 Hz the lower fi equenc} magnitude bins, is higher during the inspiration phase than during the expiration phase for each breathing cycle, frequency ratio can be used to differentiate the two phases of the breathing cycle 1 his ratio is presented in equation (2) as the frequenc> bands ratio (BR)

2M)QIl: I₀₀//.

BR = ∑ FFTU)I ∑ FFl ( f ) (2)

M)OH: OH:

|0079| The numeratoi of equation (2) represents the sum of FFT higher magnitude bins between 500 to 2500 Hz, and the denominator represents the sum of F hT lower magnitude bins below 500 Hz BR was calculated for each of the six curves shown in FIGS 8a and 8b which include the curve of the mean and the positive and negative standards deviation for both inspiration and expiration These results are presented in Table 3

Table 3. BR calculated for inspiration and expiration spectra

Inspiration BR Expiration BR

28 TRI-MP2/PCT Mean inspiration spectrum 2 27 Mean expiration specti um 0 1 5

Mean inspiration spectrum +^■ Std 2 34 Mean expiration specti um + Std 0 21

Mean inspiration spectrum - Std 2 14 Mean expiration spectrum - Std 0 02

|0080| The numbers in Table 3 represent the BR which is a ratio calculated from various curves

(0081 J Table 3 shows that the mean BR foi inspit ation (BRi) is 1 5 I times higher than mean BR toi expiration (BRe) BRi is higher than that foi BRe f-ot example, by compai ing the two extremes, ' BR toi mean inspiration - Std and BR for mean expn ation + Std". as noted in T able 3 and show n in FIGS 8a and 8b, BRi may be 10 2 time greater than that lor BRe However, other predetermined multipliers may be acceptable for determining the inspiration and expii ation phases of breathing For example, the multiplier maybe from about 1 to about to about 20 Therefoi e the frequency-based variable BR may be used to distinguish the various phases of a given breathing cy cle

|0082| In order to validate the results of the piocedure as found using the test group, the BR parameters as determined above were utilized to track the breathing phases in the individuals in the validation group A method that depends on past readings of acoustic data was developed to predict the current phase A flow diagram of this method is show n schematically in FIG 9 For example, a benefit of using past values rather than post-processed statistics is that the technique can be adopted for real-time implementation According to this exemplary embodiment, the acoustic data stream is segmented into 200 ms segments However, it may be desirable for the segments to be of a length greater than or less 200 ms For example the segments may be from about 50 ms to about I second Preferably, the segments are from about 100 ms to about 300 ms Each segment is then treated as described above in relation to the test group For example, Welch's method was applied to calculate frequency spectrum and it's BR, a first bands ratio (first BR) Subsequently the mean BR of the past 1 4 seconds (7 segments x 200 ms) or the

29

I RI-MP2/PCT mean of all the past BR s whichever is grtatei was calculated Each new ly found BR said first BR w as then compared w ith the past BR average oi mean bands ratio If the first BR is greater than the mean BR by at least a pi edetermined multiplier, then it is labeled as inspiration The predetermined multiplier may be from about 1 I to about 10 Preferably the multipliei is from about 1 to about S Most preferably the multiplier is from about 1 5 to 2 For example if the first BR is tw ice the past 1 4 seconds BR average (mean BR) then it is labeled as inspiration Likew ise if the first BR is less than mean BR by at least a predetermined multiplier then it is labeled as expiration Therefore, for example a segment is labeled as expiration if the coi responding BR is 2 times below the average of the past two segments FIG 10a show s an exemplary representative plot of an embodiment of all BR values calculated from the acoustic data v\ ith the corresponding RI P tor comparison Visual examination shows that thei e is a correlation between BR waveform and its RI P counterpart Averaging ot the BR s is performed in order to smooth out intra-phase oscillations in BR such as in the case of the BR cui ve at time 5- 10 seconds seen in FIG 10a

|0083| The method was tested prospectiveK on the breathing acoustic data of 10 subjects in the validation group The breathing phases found using the presently described method as applied to the data of FIG 10a are shown in FIG 10b With refei ence to FIG 10b, the dashed line represents the respiratoi y or breathing phases found utilizing the currently described method Out of 436 breathing phases 425 breathing phases were labeled correctly, 8 phases were partially detected and 3 phases were labeled as being the opposite phases Therefore, utilizing the method, about 97 4% of the breathing phases were detected correctly using acoustic data as compared with RIP trace

[0084] With reference to FIG 10b, the breathing cycles are shown as a processed wave amplitude versus time plot The processed wave amplitude data are shown by the dashed line and indicate the respiration phase ot an individual's breathing In an exemplary embodiment, the processed wave amplitude versus time plot may be displayed on a display module such as that shown in FiG 3 at 1 1 The processed wave amplitude versus time plot may also be, in some exemplary embodiments, provided to an operator by

30 TRI-MP2/PCT way of an information relay or relaying module in a printed form or other suitable form for example audio cues, such that the breathing of an individual may be monitored in accordance with the method by an operator In some exemplary embodiments the information relay module may display 01 provide the processed data in terms ot inspiration and or expiration indicia

|0085| T he fiequency spectrum of inspiration may be characterized by a narrow band below 200 Hz, a trough starting from about 400 Hz to about 600 Hz In the exemplaiy embodiments noted herein the trough begins at about 400 Hz in one the first embodiment (FIG 7b) and at about 500 Hz in another second, embodiment (FIG 8a) A wider but shorter peak above may be seen at about 400 Hz to about 600 Hz The peak is seen at about 400 Hz in the llist embodiment (FIG 7b) and at about 500 Hz in the second embodiment (HG 8a) In the embodiments noted herein, a smooth frequency distribution is noted after the decline of the initial narrow peak (FIGS 7b and 8a) However, it maybe desirable in older embodiment to utilize various other frequencies and trequencx langes, for example b> wa\ of illustration and not limitation greatei than or less than about 400 I Iz or 500 Hz

[0086] Expiration, on the other hand may be characterized b> a w ider peak with a relatively sharp increase from about 10 to 50 Hz and a smooth drop from about 50 to 400 Hz as seen in the first embodiment shown in FIG 7c or in the second exemplary embodiment as shown in FIG 8b, above about 500 Hz There is a relatively sparse frequency content above about 400 Hz in the first exemplary embodiment of FIG 7c and likewise in the exemplary second embodiment of FIG 8b above about 500 Hz A cut-off point of 400 Hz in the first exemplary embodiment and 500 Hz in the second exemplary embodiment was chosen to distinguish between inspiration and expiration phases based upon these observations Although recordings of breathing sounds have frequency content up to 10 kHz, most of the power lies below 2 kHz, and therefore higher frequencies may not be required to be considered Additionally, frequencies below 10 Hz may also be excluded in order to avoid the effect of baseline shift (DC component) Therefore, a considering the aforementioned factors a simple ratio between the sums of

31 I RI-MP2/PCT magnitudes of bins of higher frequenc} (above about 400 Hz in the fii st embodiment and above about 500 Hz in the second embodiment) to those of lower frequency (about 10 H/ to about 400 Hz in the first embodiment and about 0 Hz to about 500 Hz in the second embodiment) distinguished the inspiration phase from the expn ation phase of breathing However, as the preceding embodiments are for exemplary purposes onl> and should not be considered limiting, othei frequencv ranges may be utilized Additionally, the method may be fine tuned and/or modified as desired according to the location and type of the microphone

|0087| Λs shown by way of the exemplary embodiments disclosed herein expiration ma\ have a lower BR value than inspiration Thei efoi e the ratio of BRi/BRe tor each breathing cycle w as calculated in order to detei mine the intra-breath relationship between BRi and BRe BRi'BRe was surprisingly found to be significant!} greater than one In other words for each individual bi eath BRi is significantly higher than BRe Since this exemplary method employs relative changes in specti al characteristics, it is not believed to susceptible to variations in overall signal amplitude that result from intei -individual variations

[0088] The sensitivity of the exemplar, method in certain embodiments is about 90% and 72% for

1 5-fold and 2-fold difference between the two phases respectively However, there may be a trade-off between sensitivity and robustness, choosing a higher frequency cut-of f may make the method more specific and less susceptible to noise but sensitivity may decrease

[0089] As disclosed herein, a method for monitoring breathing by examining BR variables of short segments of breathing acoustic data is provided The data was divided into 200 ms segments with subsequent Welch's method applied on each segment However, longei or shorter segments may be desirable in various applications The method involves applying FFT's on each segment and averaging the resultant arrays Averaging FFT results within the segment further provides a random-noise-cancelling effect The method of utilizing BRi/BRe in order to determine the breathing phase sound data a showed

32 TRI-MP2/PCT correlation w ith thoracoabdominal movement as seen in FIGS I Oa and 10b Therefore the cui i ently provided method may be useful foi monitonng, identify ing and detei mining the breathing cycle phases of an individual The method may, for example, be utilized for monitoring, identifying and determining the breathing phase from a pre-recorded audio track, or the method ma\ also be utilized, for example for realtime monitonng of breathing

|0090| For example, in a real-time breathing monitoring situations, BR variables maj be examined in sequence and each BR variable is compared with a predetermined number of preceding BR values or preceding BR values The preceding BR variables may be sub|ect to a moving averaging w indow w ith the length ot a bieathing phase, which is appioximately, for example I 4 seconds However, a longei oi shorter w indow may be utilized as lequired Although in one exemplary embodiment, there is shown a 10- 15 fold dittei ence in the BR between the breathing phases, a lowei threshold may be considered For example since the moving averaging w indow incorporates transitional BR points between the inspiration and expn ation phases which dilute the BR average of a pure breathing phase a greater or less fold- difference than that noted herein in the exemplary embodiments mav be observed Accordingly an empirical threshold of 2 was chosen for the testing and illustration pui poses of an example of the present method Utilizing the method as provided herein, about 97 4% of the breathing phases were classified correctly

|00911 The method and apparatus as defined herein may be useful for determining the breathing phases in sleeping individuals as well as being useful for determining the breathing phases of awake individuals It provides a numerical method for distinguishing each phase by a comparison of segments of the frequency spectrum The present exemplary method may, if desired, be used for both real-time and offline (recorded) applications In both cases (online and offline) phase monitoring may be accomplished by tracking fluctuations of BR variables

33 TRI-MP2/PCT [0092 | The present exemplar, method may be applied to other applications w hich l equire close monitoi ing of respiration such as in intensive care medicine anesthesia, patients with ti auma or severe infection and patients undergoing sedation for various medical procedures 1 he present exemplary method and apparatus provides the ability of integrating at least one microphone and a transducing link with a medical mask thereby eliminating the need to attach a standalone transducer on the patients' body to monitoi respiration The present exemplary method may also be used for accurate online breathing rate monitoi ing and for phase-oriented inhaled drug delivery, for classification of breathing phases during abnoi mal ty pes of breathing such as snoring obstructive sleep apnoea, and postapnoeic h\ pei ventilation

[0093| Thus, the present method may thus be useful to classify bi eathing phases using acoustic data gathered fi om in front of the mouth and nostrils distal to the an outlets of an individual A numerical method lor distinguishing each phase by simple comparison of the frequency spectrum is pi ovided Furthei moi e a method which employ s relative changes in spectral characteristics, and thus it is not susceptible to variations in overall signal amplitude that result fi om inter-individual variations is provided and ma\ be applied in real-time and i ecorded applications and breathing phase analysis

|0094| The entire subject matter, of each of the references in the following list or othei wise listed heremabove, is incorporated herein by reference

Abeyratne U R. Wakwella A S and Hukins C 2005 Pitch ]ump probability measures for the analysis of snoring sounds in apnea Phy siological Measurement 26 779-98 Arzt M, Young T, Finn L, Skatrud J B and Bradley T D 2005 Association of sleep-disordered breathing and the occurrence of stroke Am J Respir Crit Care Med 172 1447-5 1 Bieger-Farhan A K, Chadha N K, Camilleπ A E, Stone P and McGuinness K 2004 Portable method for the determination of snoring site by sound analysis Journal of Laryngology & Otology 1 18 135-8 Bradley T D and Floras J S 2003 Sleep apnea and heart failure Part I obstructive sleep apnea Circulation

107 1671 -8 Campbell S S and Webb W B 1981 The peiception of wakefulness within sleep Sleep 4 177-83

34

TRI-MP2/PCT Duckitt W D Tuomi S K and Niesler T R 2006 Automatic detection segmentation and assessment of snoring from ambient acoustic data Ph] siologic al \k ement 27 1047-56 Fiz J A Abad J Jane R Riera M Mananas M A, Caminal P Rodenstein D and Morera I 1996 Acoustic analysis of snoring sound in patients w ith simple snoi ing and obstructive sleep apnoea Eui opean

Respiratory Journal 9 2365-70 Fiz J A Jane R Horns A, Salvatella D Izquierdo J, Ruiz J Caminal P and Morera J 1999 Wheezing identification in asthma sublets during forced exhalation AMERK Ah JOURN AL OF

RESPIRATORY AND C RITIC AL ( ARE MEDIL I\E 159 A652 Folke M Cernerud L, Ekstrom M and Hok B 2003 Critical κ\ iev\ of non-invasive respirator} monitoring in medical care Mec/ Biol Fn% C υmpul 41 377-83 Gulei b C Sankur B, Kah>a Y P and Raudys S 2005 Two-stage classification of respiratorv sound patterns

C υmpul Biol Med 35 67-83 Hill P D Lee B W Osbome J L and Osman E Z 1999 Palatal snoi ing identified by acoustic crest factor analysis Physiologic al Measurement 20 167-74

Hoifstein V, Mateika S and Anderson D 1994 Snoi ing is it in the ear of the beholder⁹ SLcp 17 522-6 HuIt P Fjallbrant T Wranne B bngdahl O and Ask P 2004 An improved bioacoustic method for monitoring of respiration Techno/ Health C ai e 12 323 32 HuIt P Wranne B and Ask P 2000 A bioacoustic method tor timing of the different phases of the breathing cvcle and monitoring of breathing frequency Med Fug Ph\ s 22 425-33 Jane R Cortes S, Fiz J A and Morera J 2004 Analysis of wheezes in asthmatic patients during spontaneous iespiration Con/ Pi υc ItEE Eng Med Biol Sυc 5 3836 Jane R Fiza J A Sola-Soler J, Blanch S Artis P and Morera I Automatic snoring signal analysis in sleep studies In (20Oi) Proceedings of the 25th Annual Intel national Conference of the IEEE

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35 TRI-MP2/PC1 Mattel A Tabbia G and Baldi S 2004 Diagnosis of sleep apnea Minerva Med 95 213-3 I

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36

TRI-MP2/PCT Yu W , Baghaei H Hongdi L Yaqiang L T ao X Uπbe J Ramirez R Shuping X Soonseok K . and Wai-Hoi W Λ simple iespiration gating technique and its application in high-resolution PEl camera, IELL I iansactions on Nuclear Science 52 ( 1 ) (2005) 125

|0095| While the piesent disclosure has been desci ibed for what are presently considered the preferred embodiments the disclosure is not so limited 1 o the contrary, the disclosure is intended to cover various modifications and equivalent arrangements included w ithin the spirit and scope of the appended claims The scope of the following claims is to be accoided the broadest interpretation so as to encompass all such modifications and equivalent structures and functions

37 TRI-MP2/PCr

Claims

CLAIMS:

1. A method for processing acoustic signal data for use in monitoring the breathing cycle of an individual comprising:

collecting and generating a data set representative of an acoustic data stream plot of wave amplitude versus time, the data set originating from breathing sounds of an individual;

segmenting the acoustic data stream plot into segments, each spanning a predetermined time period;

transforming the acoustic data so as to produce a frequency spectrum in each segment;

transforming the frequency spectrum in each segment so as to produce a plurality of magnitude bins;

identifying a sample including a plurality of segments and determining therein a sum of lower frequency magnitude bins within a predetermined lower frequency range and a sum of higher frequency magnitude bins within a predetermined higher frequency range;

dividing the sum of higher frequency magnitude bins in the sampling by the sum of lower frequency magnitude bins so as to produce a mean bands ratio;

determining a sum of lower frequency magnitude bins and a sum of higher frequency magnitude bins within a given segment;

38 TRI-MP2/PCT dividing the sum of higher frequency magnitude bins by the sum of lower frequency magnitude bins within said given segment so as to produce a first bands ratio; and

determining if said first bands ratio is greater or less than said mean bands ratio by at least a predetermined multiplier so as to provide an indication of said breathing cycle.

2. The method as defined in claim 1 , wherein the predetermined multiplier is at least 1.

3. The method as defined in claim 1, the predetermined multiplier being greater than 1.5.

4. The method as defined in claim 1 , the predetermined multiplier being greater than 2.

5. The method as defined in any one of the preceding claims, said first bands ratio being labeled as inspiration if the first bands ratio is greater than the mean bands ratio by at least the predetermined multiplier.

6. The method as defined in any one of the preceding claims, said first bands ratio being labeled as expiration if the first bands ratio is less than the mean bands ratio by at least the predetermined multiplier.

7. The method as defined in any one of the preceding claims, the breathing sounds being collected for a period of time of from about 10 seconds to about 8 hours.

8. The method as any one of claims 1 to 6, the breathing sounds being collected for a period of time of from about 10 seconds to about 20 minutes.

39 TR1-MP2/PCT

9. The method as defined in any one of claims 1 to 6, the breathing sounds being collected for a period of time of from about 10 seconds to about 25 seconds.

10. The method as defined in any one of claims 1 to 6, the breathing sounds being collected for a period of time of greater than 20 minutes.

1 1. The method as defined in any one of claims 1 to 6, wherein the breathing sounds are collected for a period of time about 25 seconds.

12. The method as defined in any one of the preceding claims, each of the segments representing a time period of from about 50 ms to about 1 second.

13. The method as defined in any one of claims 1 to 1 1 , each of the segments representing a time period of from about 100 ms to about 500 ms.

14. The method as defined in any one of claims 1 to 1 1, each of the segments representing a time period of about 200 ms.

15. The method as defined in any one of the preceding claims, the lower frequency range being from about 0 Hz to about 500 Hz.

16. The method as defined in any one of claims 1 to 14 the lower frequency range being from about 10 Hz to about 400 Hz.

17. The method as defined in any one of the preceding claims, the higher frequency range being from about 500 Hz to about 25,000 Hz.

40 TRI-MP2/PCT

18. The method as defined in any one of claims I to 16, the higher frequency range being from about 400 Hz to about 1 ,000 Hz.

19. The method as defined in any one of the preceding claims, the sampling of the plurality of segments being selected from the recording randomly.

20. The method as defined in any one of claims 1 to 18, the sampling of the plurality of segments including substantially all of the segments in the recording.

21. The method as defined in claim I , the mean bands ratio being determined from at least two segments preceding the first bands ratio segment.

22. The method as defined in any of the preceding claims, further comprising, before the generating step, collecting the breathing sounds with at least one microphone.

23. The method as defined in claim 22, the audio collecting of breathing sounds of an individual comprising airflow sounds resultant from the individual's breathing applying air pressure to a diaphragm of the microphone.

24. The method as defined in claim 22, the collecting of breathing sounds of an individual comprising breathing sounds resultant from the breathing of the individual being recorded by the microphone.

25. The method as defined in claim 22, the collecting of breathing sounds of an individual comprising airflow sounds resultant from the individual's breathing applying air pressure to a diaphragm of the microphone and actual breathing sounds resultant from the individual being recorded by the microphone.

41 TRI-MP2/PCT

26. The method as defined in claim 22, wherein the collection of breathing sounds is digitized in realtime.

27. The method as defined in claim 22, wherein the processing of thecollected waveform data is performed in real-time.

28. The method as defined in claim 22, wherein the breathing sounds are collected by at least a first microphone and a second microphone;

the first microphone operable to collect breathing sounds and airflow sounds resultant from the individual's breathing applying air pressure to a diaphragm of the first microphone; and

the second microphone operable to collect breathing sounds of the individual.

29. The method as defined in claim 28, further comprising, before the generating step, filtering acoustic data of an output representative of second microphone from the acoustic signal data representative of an output of the first microphone so as to provide an acoustic data stream of an audio recording of substantially airflow sounds of the individual.

30. The method as defined in claim 22, the at least one microphone being provided in a structure including one or more openings of sufficient size to minimize airflow resistance and be substantially devoid of dead space.

42 TRI-MP2/PCT

3 1 An apparatus for transforming acoustic signal data breathing sounds into a graphical representation indicative of breathing cycle phases including inspiration phases and expiration phases comprising

at least one microphone for collecting acoustic signal data resultant from the breathing of an individual during a given time period,

an acoustic signal data digitizing module for digitizing the acoustic signal data to produce an acoustic data stream plot representative of wave amplitude versus time,

at least one processor operable for receiving the acoustic data stream plot, the processor configured for

segmenting the acoustic data stream plot into a plurality of segments of a predetermined length of time,

transforming the acoustic data stream in each of the plurality of segments so as to produce a plurality of frequency specta wherein each frequency spectrum is representative of one of the plurality of segments,

transforming each frequency spectrum so as to produce a plurality of magnitude bins in each segment,

determining a sum of lower frequency magnitude bins within a predetermined lower frequency range and a sum of higher frequency magnitude bins within a predetermined higher frequency range within a sampling of the plurality segments,

43 TRI-MP2/PCT dividing the sum of higher frequency magnitude bins by the sum of lower frequency magnitude bins in the sampling so as to produce a mean bands ratio;

determining a sum of lower frequency magnitude bins and a sum of higher frequency magnitude bins within a given segment;

dividing the sum of higher frequency magnitude bins by the sum of lower frequency magnitude bins within said given segment so as to produce a first bands ratio;

comparing said mean bands ratio to said first bands ratio and determining if said first bands ratio is greater or less than said mean bands ratio by at least a predetermined multiplier so as to determine if said given segment is an inspiration phase or an expiration phase of the breathing cycle; and

an information relay module in communication with the at least one processor for providing the transformed data to an operator as first indicia representing inspiration and expiration.

32. The apparatus as defined in claim 31 , further comprising a sensor for sensing respiratory movements of an abdomen or rib region of the individual and generating a signal indicative thereof, the processor being operative to receive the signal and to identify respiratory expansion during inspiration and respiratory contraction during expiration, the information relay being operable to provide data to an operator generated as second indicia representing the respiratory movements.

44 TRI-MP2/PCT

33. The apparatus as defined in claim 31 , the information relay module being provided as a display module for displaying the transformed data as a processed wave amplitude versus time plot;

the inspiration phases being identifiable by rising regions of said processed wave amplitude versus time plot; and

the expiration phases being identifiable by falling regions of said processed wave amplitude versus time plot.

34. The apparatus as defined in claim 31 , the information relay module operable so as to provide an operator audio cues representing the inspiration and expiration phases of an individual's breathing.

35. The apparatus as defined in claim 31 , the information relay module being provided as a display module operable for displaying visual cues representing the inspiration and expiration phases of an individual's breathing.

36. The apparatus as defined in claim 31, the information relay module operable so as to provide an operator printed visual indicia representing the inspiration and expiration phases of an individual's breathing.

37. The apparatus as defined in claim 31, wherein the breathing sounds are collected by at least a first microphone and a second microphone;

- the first microphone operable to collect acoustic signal data breathing sounds and airflow sounds resultant from the individual's breathing applying air pressure to a diaphragm of the first microphone; and

45 TRI-MP2/PCT - the second microphone operable to collect acoustic signal data breathing sounds of the individual.

38. The apparatus as defined in claim 37, wherein the acoustic signal data collected by the second microphone are subtracted from the acoustic signal data collected by the first microphone so as to provide an acoustic signal data recording of substantially airflow sounds of the individual.

39. The apparatus as defined in claim 3 1 , the at least one microphone being provided in a structure including one or more opening sufficient to reduce airflow resistance and be substantially devoid of dead space.

40. An apparatus for transforming acoustic signal data breathing sounds into a graphical representation indicative of breathing cycle phases including inspiration phases and expiration phases comprising:

at least one microphone for collecting acoustic signal data resultant from the breathing of an individual during a given time period;

an acoustic signal data digitizing module for receiving and digitizing sounds via a transducing link from the at least one microphone, the audio signal digitizing module operable to produce an acoustic data stream plot representative of wave amplitude versus time;

a module for segmenting a plurality of adjacent audio samples from the acoustic data stream plot into a plurality of segments of a predetermined length of time;

46 TRI-MP2/PCT a module for transforming the acoustic data stream in each of the plurality of segment so as to produce a plurality of frequency spectra wherein each frequency spectrum is representative of one of the plurality of segments;

a module for transforming each frequency spectrum so as to produce a plurality of magnitude bins in each segment;

a module for determining a sum of lower frequency magnitude bins within a predetermined lower frequency range and a sum of higher frequency magnitude bins within a predetermined higher frequency range within a sampling of the plurality segments;

a module for dividing the sum of higher frequency magnitude bins by the sum of lower frequency magnitude bins in the sampling of the plurality of segments so as to produce a mean bands ratio;

a module for determining a sum of lower frequency magnitude bins and a sum of higher frequency magnitude bins within a given segment;

a module for dividing the sum of higher frequency magnitude bins by the sum of lower frequency magnitude within said given segment so as to produce a first bands ratio;

a module for comparing said mean bands ratio to said first bands ratio and determining if said first bands ratio is greater or less than said mean bands ratio by at least a predetermined multiplier so as to determine if said given segment is an inspiration phase or an expiration phase of the breathing cycle; and

47 TRI-MP2/PCT an information rely module in communication with the module for comparing said mean bands ratio to said first bands ratio for providing the transformed data to an operator as indicia representing inspiration and expiration.

41. A computer implemented apparatus for transforming acoustic signal data breathing sounds into a graphical representation indicative of breathing cycle phases including inspiration phases and expiration phases comprising:

at least one microphone for collecting acoustic signal data breathing sounds resultant from the breathing of an individual during a given time period;

an acoustic signal data digitizing module for receiving and digitizing sounds via a transducing link from the at least one microphone, the audio signal digitizing module operable to produce an acoustic data stream plot representative of a wave amplitude versus time;

at least one processor operable for receiving the acoustic data stream plot, the processor configured for:

segmenting a plurality of adjacent audio samples from the acoustic data stream plot into a plurality of segments of a predetermined length of time;

transforming the acoustic data stream in each of the plurality of segments so as to produce a plurality of frequency spectra wherein each frequency spectrum is representative of one of the plurality of segments;

48 TRI-MP2/PCT transforming each frequency spectrum so as to produce a plurality of magnitude bins in each segment;

determining a sum of lower frequency magnitude bins within a predetermined lower frequency range and a sum of higher frequency magnitude bins within a predetermined higher frequency range within a sampling of the plurality segments;

dividing the sum of higher frequency magnitude bins by the sum of lower frequency magnitude bins in the sampling of the plurality of segments so as to produce a mean bands ratio;

determining a sum of lower frequency magnitude bins and a sum of higher frequency magnitude bins within a given segment;

dividing the sum of higher frequency magnitude bins by the sum of lower frequency magnitude bins within said given segment so as to produce a first bands ratio;

comparing said mean bands ratio to said first bands ratio and determining if said first bands ratio is greater or less than said mean bands ratio by at least a predetermined multiplier so as to determine if said given segment is an inspiration phase or an expiration phase of the breathing cycle; and

an information rely module in communication with the at least one processor for providing the transformed data to an operator as indicia representing inspiration and expiration.

49 TRI-MP2/PCT

42. A method for processing acoustic signal data for use in monitoring a breathing cycle of an individual comprising:

generating a data set representative of an acoustic data stream plot of wave amplitude versus time, the data set originating from breathing sounds of an individual;

transforming the acoustic data stream plot to yield at least one relatively higher frequency spectral characteristic and at least one relatively lower frequency spectral characteristic;

determining a proportional value of the relatively higher frequency spectral characteristics to the relatively lower frequency spectral characteristics; and

generating at least first output indicative of an inspirational breathing phase according to a first range of the proportional value and/or at least one second output indicative of an expirational breathing phase according to a second range of the second proportional value.

43. A device for processing acoustic signal data for use in monitoring a breathing cycle of an individual comprising:

means for generating a data set representative of an acoustic data stream plot of wave amplitude versus time, the data set originating from breathing sounds of an individual;

means for transforming the acoustic data stream plot to yield at least one relatively higher frequency spectral characteristic and at least one relatively lower frequency spectral characteristic;

50 TRI-MP2/PCT means for determining a proportional value of the relatively higher frequency spectral characteristic to the relatively lower frequency spectral characteristic; and

means for generating at least first output indicative of an inspirational breathing phase according to a first range of the proportional value and/or at least one second output indicative of an expirational breathing phase according to a second range of the second proportional value.

44. A method for processing acoustic signal data for use in monitoring inspirational and expirational phases of a breathing cycle of an individual comprising:

generating a data set representative of an acoustic data stream plot of wave amplitude versus time, the data set originating from breathing sounds of an individual;

transforming the acoustic data stream plot to yield inspirational spectral data for at least one inspirational phase and expirational spectral data for at least one expirational phase; and characterizing the shape of the inspirational and expirational frequency spectra for tracking breathing activities to identify inspirational and expirational breathing phases in subsequent breathing cycles.

45. A device for processing acoustic signal data for use in monitoring inspirational and expirational phases of a breathing cycle of an individual comprising:

means for generating a data set representative of an acoustic data stream plot of wave amplitude versus time, the data set originating from breathing sounds of an individual;

51 TR1-MP2/PCT means for transforming the acoustic data stream plot to yield inspirational spectral data for at least one inspirational phase and expirational spectral data for at least one expirational phase; and

means for characterizing the shape of the inspirational and expirational frequency spectra for tracking breathing activities to identify inspirational and expirational breathing phases in subsequent breathing cycles.

52 TRI-MP2/PCT