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`
`US 20090105556/X1
`
`(19) United States
`(12) Patent Application Publication (10) Pub. No.: US 2009/0105556 A1
`Fricke et al.
`(43) Pub. Date:
`Apr. 23, 2009
`
`(54)
`
`MEASUREMENT OF PHYSI0l.OGl(.‘.-\L
`SIGNALS
`
`(75)
`
`ltwcntorsz
`
`John Robert Frieke. [.exing,toI1.
`MA {US}: Matthew Corbin
`Wiggins. Concord. MA (US)
`
`Corresportdencc Address:
`()CCIIIUTI RUIILICICK & TSAO, LIP
`10 FAWCETT STREET
`(IAMBRIDGE, MA 02138 (US)
`
`(73)
`
`Assigxicez
`
`Tlax I.L(.‘.. Cantbridgc. MA (US)
`
`(21)
`
`Appl , No .:
`
`l2:’2-10,651
`
`(22)
`
`Filed:
`
`Sep. 29., 2008
`
`Related U.S.Applieatien Data
`
`(60)
`
`Provisional application No. 6t)f995_.723. filed on Sep.
`28. 2007.
`
`Publication Classification
`
`(51)
`
`Int. (:1.
`(2006.01)
`A61}? 5/00
`(2006.01)
`A613 5/I455
`(52) U.S.(Il. ....................................... .. 6lJ01'301:6()01'3l0
`
`(57)
`
`ABSTRACT
`
`A system includes an optical sensor and :1 signal processing
`module. The optical sensor is ctmligtlrt-:d to be positioned on
`an area ofskin ofa patient. The optical sensor includes a light
`source for illuminating a capillary bed in the area of skin and
`at photodetector. The pholodetector is conligtlred to receive an
`optical signal front the CElplll:1I‘_\" bed resulting from the illu-
`mination and to convert the optical signal into an electrical
`signal. the optical signal clmmctefizilig a llucluation in a level
`of blood in the capillary bed. The signal processing inodule is
`configured to process the electric signal using a nonstationary
`freque11-::y estimation ntethod to obtain a processed signal
`related to at least one ofa heart rate and at respi1'atitJ11 rate of
`the patient. Another aspect relates to obtaining a quantity
`related to the blood pressure o i‘ the patient i11 addition to or
`instead of obtaining a processed signal related to at least one
`of the heart rate and the respiration rate of the patient.
`
`100
`
`128
`
`
`
`126
`
`124
`
`001
`
`Apple Inc.
`APL1016
`
`U.S. Patent No. 8,923,941
`
`Apple Inc.
`APL1016
`U.S. Patent No. 8,923,941
`
`001
`
`

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`US 2009f0 105556 A1
`
`Apr. 23, 2009
`
`MEASUREMENT OF PHYSIOIJOGICAI.
`SIGNALS
`
`CROSS-Rlil"liRl-iNCl'i TO Rl-iI.A'l'l-ll.)
`APPl..lCA’l‘lONS
`
`[0001] This application claims priority to U.S. provisional
`application No. 60l995.723. filed Sep. 28. 2007'. entitled
`“Method and Devices for Measurement of Multi-rnodal
`
`Physiological Signals," which is incorporated herein by ref-
`CTCITCC.
`
`STATEMENT REGARDING FEDERALLY
`SPONSORED RESEARC H
`
`TT1e subject matter described in this application was
`[0002]
`partially funded by the Cioveminent of the United States
`under Contract No. W9]ZLK-04~P-0239 awarded by the
`U.S. Department of the Army. The government has certain
`rights in the invention.
`
`FlliI..D Ol-' Tl-IE IN]/l£N'l'I()N
`
`[0003] The invention relates to measurement ofphysiologi-
`cal signals.
`
`l3A(TKGROlJNl)
`
`Physiological signals are important for monitoring a
`[0004]
`subject‘s physical and cognitive state. Often. heart rate
`parameters are measured directly via electrocardiogram
`(ECG) measurements of a heart beat. Respiration rate data
`can be obtained from a respiration chest strap. Physiological
`signals can also be extracted from infrared (IR) photoplcthys-
`mographs (PPG). The signals of interest include heart rate,
`respiration rate, continuous blood pressure, and intrathoracic
`pressure. With respect to blood pressure. there is technology
`related to collecting data at two locations on the body and
`using pulse transit time and other parameters as the basis of
`the pressure estimate.
`
`SUMMARY
`
`In a general aspect. a system includes an optical
`[0005]
`sensor and a signal processing module. The optical sensor is
`configured to be positioned on an area ofskin ofa patient. The
`optical sensor includes a light source for illuminating a cap-
`illary bed in the area of skin and a photodetector. The photo-
`detector is configured to receive an optical signal from the
`capillary bed resulting from t.l1c illumination and to convert
`the optical signal into an electrical signal. the optical signal
`characterizing a fluctuation in a level of blood in the capillary
`bed. The signal processing module is configured to process
`the electric signal ttsinga nonstationary frequency estimation
`method to obtain a processed signal related to at least one of
`a heart rate and a respiration rate of the patient.
`[0006] Embodiments may include one or more of the fol-
`lowing. The system includes an output for providing infor-
`mation determined from the processed signal. The nonsta-
`tionary frequency estimation method includes a Hilbert
`transfonn method or an instantaneous frequency estimation
`method. The processed signal includes at least one ofinstan-
`taneous heart rate, inter—beat interval. heart rate variability.
`high—low heart rate ratios, respiration rate. inter-breath inter-
`val. and respiration rate variability. The lluctttation in l.l1e level
`ofblood in the capillary bed relates to a change in at least one
`
`ofvolume and pressure ofthe thoracic cavity or to a change in
`at least one of volume and pressure ofan organ in the thoracic
`cavity.
`[0007] The system includes an auxiliary sensor configured
`to detect an ambient signal. The auxiliary sensor includes at
`least one o faccelenometer. a pressure sensor. an optical detec-
`tor. a temperature sensor. and a piezoelectric device. The
`signal processing module is configured to remove an effect of
`the ambient signal from the electrical signal. The optical
`signal is a reflectance or a transmittance of the capi llary bed.
`[0008]
`ln another general aspect. a method includes ill1uni-
`nating a capillary bed in an area of skin ofa patient. receiving
`an optical signal from the capillary bed resulting from the
`illumination. converting the optical signal into an electrical
`signal. and processing the electrical signal tising a nonstation-
`ary iiequency estimation method to obtain a processed signal
`related to at least one of a heart rate and a respiration rate of
`the patient. The optical signal characterizes a fluctuation in a
`level of blood in the capillary bed.
`[0009] Embodiments may include one or more of the fol-
`lowing. The method includes outputting information deter-
`mined from the processed signal. Processing the electrical
`signal using the nonstationary frequency estimation method
`includes performing a I-lilhert trartsfornt or processing the
`electrical signal using an instantaneous frequency estimation
`method. Processing the electrical signal using the instanta-
`neotis frequency method includes band pass filtering the elec-
`trical signal. determining an instantaneous frequency of the
`electrical signal. and using the instantaneous frequency to
`obtain the processed signal.
`[0010] The method furl.hcr includes processing the electri-
`cal signal using a model to obtain a blood pressure signal
`related to a blood pressure of the patient. The optical signal
`characterizes a capillary refill time in the capillary bed. Pro-
`cessing the electrical signal includes processing the electrical
`signal in real time.
`[0011]
`In another aspect, a method for monitoring blood
`pressure includes illunlinating a capillary bed in an area of
`skin ofa patient. receiving an optical signal from the capillary
`bed resulting from the illumination. converting the optical
`signal into an electrical signal. a11d processing the electrical
`signal using a model characterizing a relationship ofthe fluc-
`tuation in the level of blood and the blood pressure of the
`patient to obtain a quantity related to the blood pressure of the
`patient. The optical signal cltaractcrizes a lltictuation in a
`level of blood in the capillary bed ofthe patient.
`[0012] Embodiments may include one or more of the fol-
`lowing. The method includes outputting information deter-
`mined based on the quantity related to the blood pressure of
`the patient. The optical signal characterizes a capillary refill
`time. The method further includes engaging a device to
`restrict circulation in the capillary bed of the patient and
`disengaging the device prior to receiving the optical signal
`from the capillary bed. The disengaging of the device occurs
`gradually. The device is an active clamping device.
`[0013] The quantity related to the blood pressure of the
`patient is a quantity related to the continuous blood pressure
`ofthe patient. Applying the model includes applying a model
`including circuit elements or properties of the capillary bed.
`The method further includes calibrating the 111odel on the
`basis of a blood pressure of the patient determined by using a
`blood pressure cuff.
`
`O22
`
`022
`
`

`
`US 2009f0l05556 A1
`
`Apr. 23, 2009
`
`Fmbodiments may include one or more of the fol-
`[0014]
`lowing advantages.
`[0015] A system or method as described above can be used
`for both military and civilian applications. Combat casualty
`care requires close tnonitoring ofvital signs from tl1e moment
`that a ntedic first attends to a wounded soldier in the battle-
`
`lield and thence through the many transfer stages to the point
`of full hospital care. generally removed lrom the combat
`scene. Similar needs are evident in the civilian community
`where critical care is administered by first responders at the
`scene ofaccidents, by emergency room staff, and by intensive
`care unit staff. It is often desirable to obtain ntaxitnttnt infor-
`mation using as little equipment as possible. The system and
`method described herein support this need. They reduce the
`burden of equipment logistics. the burden of extra wires and
`sensors on and around the patient, and the complexity and
`cost of ttsing multiple devices.
`[0016]
`For both military and civil ian applications. a dispos-
`able. wearable device in keeping with the system and t11et.l1od
`described herein can be adapted to stay with a patient and to
`report vital signs througltout the care and transport processes.
`Further. the system can be configured to provide medical
`personnel with real-tirne visibility of vital signs as well as
`recording. ofthis information for playback by attending inedi-
`cal stat ff at a later time. The disposability of the device allows
`it to be fabricated with low cost parts and clinlinatcs the need
`for sanitizatiorr and asset tracking logistics in large scale
`clinical or military uses.
`[0017]
`Such system and methods additionally support
`applications in fitness monitoring. where their ease ofuse and
`robustness make them a compelling alternative to chest strap
`monitors for the rnonitorillg ofcardiac and respiratory param-
`eters during exercise. An car-worn device can also integrate a
`speaker unit for mobile electronic devices sucl1 as mobile
`phones or music players.
`[0018] An advantage of applying a nonstationary fre-
`quency estimation method [e.g.. analysis involving monitor-
`ing the frequency changes of the signal over titne_. such as
`monitoring changes in the instantaneous principal frequency
`over time) is that it is possible to avoid a tradcoff inherent i11
`many stationary estimation methods between frequency reso-
`lution and duration of data signals being analyzed. For
`example. iftlte signal is assumed to be stationary within each
`of a series of data windows. the frequency resolution is gen-
`erally inversely proportional to the duration of the window.
`As the window duration increases. the assumption of a sta-
`tionary signal is increasingly violated andfor nonstationary
`events (e.g.. transients) are more difficult to detect. At least
`sotne nonstationary frequency analysis methods. which may
`be based. without limitation. on a Hilbert transform approach.
`tracking of a rtonstationary model. nonstationary principal
`frequency analysis. or other tirne-freqttency tnethods. miti-
`gate the effects of such a time-freqttency tradeoll‘. Further-
`more. use o fsuch nonstationary teeltniques. as opposed to use
`of time domain peak picking andfor threshold based tech-
`niques. can provide robustness ofalgorithm against artifacts.
`and provide sensitivity to periodicity without being burdened
`by a window that can reduce the time resolution.
`[0019] Other features and advantages are apparent from the
`following description and frotn the appended claims.
`
`l3Rllil*' l)lESCRIP'l‘l()N O1’ DRAWINGS
`
`1’ IG. 1 is a schematic diagram ofa pl1otoplel.l1ys111o-
`[0020]
`graph (Pl’G} sensor system.
`
`FIG. 2 is a graph ofa PPG detector signal taken over
`[0021]
`a 25 second period by an earlobe PPG device.
`[0022]
`FIG. 3 is a flow diagram of signal processing of a
`detector signal from a PPG device to obtain heart rate and
`respiration rate parameters.
`[0023]
`FIG. 4 is a graph ofa result ofband—pass filtering the
`data shown in FIG. 2 between 0.5 Hz and 5.5 I-12 to extract a
`
`cardiac signal.
`[0024]
`FIG. Sis a graph ofa result ofband-pass filtering the
`data shown in FIG. 2 between 0.17 Hz and 0.5 Hz to extract a
`
`respiration signal.
`[0025]
`FIG. 6 is a graph ofan inter-beat interval obtained by
`applying an instantaneous frequency method to the cardiac
`signal shown in FIG. 4.
`[0026]
`FIG. 7 is a graph of a spectral analysis of the inter-
`beat interval data shown in FIG. 6.
`
`FIG. 8 is a graph of the respiration rate obtained by
`[0027]
`applying an instantaneous frequency method to the respira-
`tion signal shown itt FIG. 5.
`[0028]
`FIG. 9 is a diagram ofl’l-‘G measurentents related to
`physiological states used to determine intrathoracic pressure.
`[0029]
`FIG. Ill is a graph of the output ofa matched filter-
`ing process using the PPG detector signal shown in FIG. 2 and
`a pulse pilot signal.
`[0030]
`FIG. ll is a block diagram of a least mean squares
`(LMS) adaptive filter.
`[0031]
`FIG. 12 is a sclrematic diagram of an active clamp-
`ing mechanism ttsed to stimulate capillary refill.
`[0032]
`FIG. 13 is a diagram ofa system model relating a
`PPG signal to blood pressure.
`[0033]
`FIG. 14 is a graph of trends in various physiological
`parameters before and during a stress event.
`[0034]
`1" IG. 15 is a block diagram ofa portable electronics
`unit.
`
`FIG. 16 is a flow diagram of methods to estimate a
`[0035]
`heart rate and a respiration rate.
`[0036]
`FIG. 17 is a flow diagram ofa processing delay in
`the estimation ofa heart rate.
`
`FIG. 18 is a [low diagram of a processing delay in a
`[0037]
`first method for the estimation of a respiration rate.
`[0038]
`l--‘IG. 19 is allow diagram ofa processing delay in a
`second method for the estimation ofa respiration rate.
`[0039]
`FIG. 20 is a flow diagram ofa processing delay in a
`third method for the estirnation of a respiration rate.
`
`l)l'i'l"Al I .1"-D DI ESCRIPTION
`
`[0040] Referring to FIG. 1. examples of an infrared pho-
`topletltysinograph (PPG) device 100 are used to obtain physi-
`ological signals related to one or more of heart rate. respira-
`tion rate. blood pressure. and intrathoracic pressure. Such
`signals may be relevant
`for monitoring a person's state.
`including one or more of the pcrson’s physical state, long-
`ternt health. psychological state. andfor cognitive state. More
`generally. the physiological signals may provide information
`about the activity of the person's sympathetic and parasym-
`pathetic nervous system. The PPG device 100 illustrated in
`FIG. I is attached to an earlobe 102 of a person. for example.
`using a clamping or adhesive approach. However. in other
`embodiments. PPG device 100 is used on other areas of the
`skin ofa person. including but not limited to a portion of a
`forehead. a neck. an arm. a foreamt. a finger. a leg. a back, an
`abdomen. or a stomach. In general. a requirement for the
`positioning of PPG device 100 is that the Pl-‘G sensor be
`located such that it can obtain a measurement via the skin that
`
`023
`
`023
`
`

`
`US 2009f0 105556 A1
`
`Apr. 23, 2009
`
`is related to blood [low or pressure. for example to measure a
`level of blood in a capillary bed 104, for example. a blood
`volume. a rate of blood flow. or a rate of change of blood
`volume. Note also that the approach is not limited to use of a
`single PPG device on an individual. In some embodiments.
`multiple PPG devices are used. for example. on the torso
`andfor at dilferent extremities. and signals obtained at the
`different PPG devices are processed independently or in com-
`bination to determine underlying characteristics of the indi-
`vidual ‘s state.
`
`In some embodiments. such as that shown in FIG. 1.
`[0041]
`an infrared light source 106 illuminates the earlobe 102. The
`blood level in capillary bed 104 affects the amount of light
`108 that is backscattered or reflected by earlobe 102. Light
`108 backscattered by earlobe 102 is received by an optical
`transducer such as a photodetector 110 and converted into a
`detector signal 112. Since the blood How in capillary bed 104
`is controlled by the heart beat ofthe person and thus the blood
`level in the capillary bed varies with time. the backscattercd
`light 108 and hence the detector signal 112 are also tittie-
`varying. In another embodiment. the PPG sensor operates in
`transmission mode and the light transmitted through the cap-
`illary bed is received by the photodetector.
`[0042] The detector signal 112 is sent to a signal processing
`unit 114 which processes the detector signal. which contains
`information about the person’s pulse. to extract desired physi-
`ological data. in various embodiments including one or more
`ofinstantaneous hean rate. inter-beat interval. heart rate vari-
`ability. high-low heart rate ratio. respiration rate. inter-breath
`interval. respiration rate variability. blood pressure, and
`intrathoracic pressure. A single PPG device 100. referred to
`below as an integrated Mnlti—Modal Physiological Sensor
`(IMMPS). is capable of producing multiple (or all) of such
`types of physiological data.
`[0043]
`In some embodiments. the PPG device 100 provides
`real-time visibility of physiological paratneters and vital
`signs. which can be transmitted to other equipment for real-
`time processing or for playback or off-line processing at a
`later time. in some embodiments. the PPG device includes
`user output devices. such as a set of light emitting diodes
`(I..l7.Ds} {e.g.. a red LEI) ] 16. a yellow LED 118. and a green
`LED 120} or an audio device for producing alert sounds.
`which provide on-device status on PPG device 100. As an
`example for use of such output devices. when a selected
`physiological parameter is in a normal range. green LED 120
`is turned on: when the physiological parameter is in a slightly
`abnormal range, yellow LED 118 is turned on; when the
`physiological parameter is in a dangerous range. red LEI") 1 16
`is turned on. In some embodiments. the audio output device is
`used to provide other audio output. such as the output for an
`electronic device such as a mobile phone or a music player. In
`some embodiments. a wireless link 122 to an external moni-
`toring system l24. such as a bedside system or a wearable
`system. provides sensor data to the external system enabling
`a numeric readout 126 of various physiological parameters.
`In some embodiments, the PPG device. or at least some
`wearable portion ofthe device. is disposable. In such dispos-
`able embodimenls, the bedside system can be designed to be
`sterilized and reused: in another etnbodiment. the bedside
`system itself is also disposable. in some embodiments. the
`bedside system includes or comntunicates with a centralized
`monitoring system that monitors PPG devices of multiple
`patients.
`
`the photodetector based
`In some embodiments.
`[0044]
`detector signal is augmented with other signals. for example.
`accelerometer or pressure sensor signals. For example. aux-
`iliary sensors 130 are Oonllected to signal processing Ltnit 114
`via a wired connection 132. In other embodiments. auxiliary
`sensors 130 are connected to signal processing unit 114 via a
`wireless connection. Auxiliary sensors 130, such as te111pera-
`ture sensors. accelerometers. pressure transducers. optical
`detectors. or piezoelectric films or matrices can provide aux-
`iliary signals 132 related to ambient sources ofnoise to signal
`processing unit 114. Signal processing unit 114 incorporates
`auxiliary signals 132 into the signal processing, liir example.
`to increase the signal-to-noise ratio ofthe desired physiologi-
`cal data.
`
`Heart and Respiration Rate Signals
`
`[0045] Referring to FIG. 2, in an embodiment ol‘ the I-‘PU
`device that uses a photodetector signal obtained from at an
`earlobe location. a detector signal 200 obtained from the PPG
`device 100 has a high-frequency pulse signal 202 whose local
`peaks in the time domain have a one-to-one correspondence
`with cardiac beats. Significant low-frequency amplitude vari-
`ability in the detector signal is due in large part a respiration
`signal 204. which modulates the baseline of the pulse signal.
`[0046] The time varying heart and respiration components
`in detector signal 200 can be modeled as
`s(r}=;I_.,t.r]eos [(1)_.,{'r}.r+1pH( T)]+_-I Rf.t]co.-s [m,,t_r+¢R( ?}]+
`NE! D.
`
`i 1 l
`
`where A,,(t} is the amplitude modulation ofpulse signal 202.
`[1],,(t) is the frequency modulation ofpulse signal 202. I]!3(1) is
`the phase modulation of pulse signal 202. . 3(1) is the ampli-
`tude modulation of respiration signal 204. 0;-R[t) is the fre-
`quency modulation of respiration signal 204. $30) is the
`phase modulation of respiration signal 204. and MI) is the
`time varying noise. which includes baseline drift and broad-
`band noise in the overall signal band.
`[0047] Given the measured detector signal 200 (s{l)). signal
`processing is performed to estimate Lhe slowly varying corn-
`ponents of the heart rate U.tH(t) and the respiration rate uJ,.(t).
`It is known that uJ,,(t)-=(um-=1 beat per second 1 Hz for heart
`rate and Lt}R{i)='-°tJ);,U~l 2 breaths per minute»-t).2 Hz for respi-
`ration rate.
`
`[0048] Amplitude, phase. and frequency modulation cause
`spectral spread that broadens the pure tones implied by these
`frequencies. Amplitude and phase modulation and rapid fluc-
`tuations of the frequency modulation are confounding com-
`ponents of detector signal 200. The slowly varying compo-
`nents of mm are the desired components for obtaining heart
`and respiration rate information.
`is com-
`[0049]
`For both heart and respiration rate. w[t).
`posed of three pans: constant frequency too, which is the
`nominal heart or respiration rate: a zero-meat . slowly varying
`lreqttericy component S2, having a time scale ofminutcs; and
`a zero-mean. rapidly varying frequency component Qrhaving
`a time scale ofseconds. In this case. the composite heart rate
`or respiration rate is written as
`
`(o{.'}--(o,+Q,{i‘}+§2,( I}.
`
`ill
`
`The signal ofinterest is the combination of the constant and
`the slowly varying cornponent (for both heart rate and respi-
`ration rate) and is written as
`
`ti)! u‘}=t:J°+fl_{r].
`
`{3}
`
`024
`
`024
`
`

`
`US 2009f0 105556 A1
`
`Apr. 23, 2009
`
`The phase tnodulation noted is Eq. ( l ), 12(1). is assumed to be
`small. since large phase modulation can be represented as
`frequency modulation and this is already captured in S2, or $2,.
`[0050] Applying [Eq. (3) to ta]. (1), a new equation for llifl‘
`measured raw signal 200 is obtained:
`
`.rt.'}"‘-.-igttlcos [(i1,,r(t)t+qt,:,,-{t}]+.-Iyqtrtcos [
`uJRtt}t+1p__‘R{I}]+l\-"III.
`
`M}
`
`where for both heart and respiration rate, small components
`them are defined as
`-pan ,'
`.,,’QJ('rlrt‘1:+¢{f}
`
`(5)
`
`and by construction |¢E(t]|<<l and ¢E(t) is zero mean.
`[005]] Using the Law of Cosines and the fact that lt]iE(l.]
`l-(<1. the following equation for raw signal 200 is obtained:
`
`.rtr}=.-[t_;,ttt1{ cos [tirqttltjn-¢m{t}sin [tit_q{rlr}'}+.‘l'Rl!l{
`cos [(o,,{r]r]—q1<Rttisiu [to,,tr,1r,1'}+.«\r't ti.
`
`{6}
`
`[0052] The formulation in Eq. (6) of PPG detector signal
`200 suggests a number of methods to estimate the desired
`slowly varying heart and respiration rate signals riiH(t) and
`liJR[l).. respectively. Such estimation techniques can include
`instantaneous frequency determittation via analytic signals.
`tnoving averages. band pass filtering. synchronous detection.
`correlation detection, narrowband processes (e.g._. demodu-
`lation). matched filtering, wavelet filtering. short—time fre-
`quency analysis (e.g., short-time fast Fourier transform.
`Wigner-Ville transform). state estimation (e.g.. Kalntan fil-
`tering. unscented filtering). Doppler processing, or a combi-
`nation of the above methods. A number of these techniques
`can be implemented to account for the no nstationary nature of
`the detector signal, which relates to the time variation of the
`frequency modttlation signals. tu(t).
`[0053] Referring to FIG. 3, one example of a procedure for
`obtaining heart rate parameters andfor respiration rate param-
`eters involves receiving the detector signal 200. such as that
`shown in FIG. 2. from a PPG photodetector [IR Plethyst11o-
`graph 300). To emphasize the pulse signal in order to extract
`cardiac parameters from the detector signal. the respiratory
`modulation is removed by band-pass filtering (302) the detec-
`tor signal between approximately 0.5 Hz and approxitnately
`5.5 I12. I3and-pass filtering of the detector signal shown in
`FIG. 2 results in a cardiac signal shown in FIG. 4. which has
`significantly less amplitude variability due to respiratory con-
`tamination. The band-pass filtered signal pulse signal can be
`expressed as
`
`§I’fJ=-fnt!J{ we tniriitrirr-mnsin ts-‘wtr;}+fi't:i.
`
`{Tl
`
`where fi£(t) is the content of the noise. N(t). within the heart
`rate bandwidth. Likewise, referring again to FIG. 3. to extract
`parameters related to respiration from a PPG detector signal.
`the pulse signal is retnoved by band-pass filtering (304) the
`detector signal between approximately 0.1 7 Hz (equivalent to
`10 breaths per minute) and 0.5 Hz (30 breaths per minute].
`Band—pass filtering the detector signal of FIG. 2 produces a
`respiration signal shown in l"'IG. 5. which retains primarily
`low frequency respiration components of the original signal.
`[0054]
`Focusing now on the cardiac signal. one approach to
`detecting heart beats in the cardiac sigial is by threshold-
`based peak picking. which can be used to determine the time
`of specific events such as heart beats. In some implement‘ -
`tions. peak picking can be sensitive to the threshold selected.
`For example. if the threshold is set too low. then false beats
`can be counted. and the inter-beat interval (I131) is determined
`to be shorter than it really is. If the threshold is set too high.
`
`then true beat peaks may be tnissed. For general processing it
`is convenient to select a single threshold. but if the data are
`suificiently variable then selecting a single threshold is not
`possible.
`[0055] Other appro