WO2011003132A1 - Non-invasively measuring physiological process - Google Patents
Non-invasively measuring physiological process Download PDFInfo
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- WO2011003132A1 WO2011003132A1 PCT/AU2010/000853 AU2010000853W WO2011003132A1 WO 2011003132 A1 WO2011003132 A1 WO 2011003132A1 AU 2010000853 W AU2010000853 W AU 2010000853W WO 2011003132 A1 WO2011003132 A1 WO 2011003132A1
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
- A61B5/024—Detecting, measuring or recording pulse rate or heart rate
- A61B5/02411—Detecting, measuring or recording pulse rate or heart rate of foetuses
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/43—Detecting, measuring or recording for evaluating the reproductive systems
- A61B5/4306—Detecting, measuring or recording for evaluating the reproductive systems for evaluating the female reproductive systems, e.g. gynaecological evaluations
- A61B5/4343—Pregnancy and labour monitoring, e.g. for labour onset detection
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/43—Detecting, measuring or recording for evaluating the reproductive systems
- A61B5/4306—Detecting, measuring or recording for evaluating the reproductive systems for evaluating the female reproductive systems, e.g. gynaecological evaluations
- A61B5/4343—Pregnancy and labour monitoring, e.g. for labour onset detection
- A61B5/4362—Assessing foetal parameters
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B2503/00—Evaluating a particular growth phase or type of persons or animals
- A61B2503/40—Animals
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B2562/00—Details of sensors; Constructional details of sensor housings or probes; Accessories for sensors
- A61B2562/02—Details of sensors specially adapted for in-vivo measurements
- A61B2562/0219—Inertial sensors, e.g. accelerometers, gyroscopes, tilt switches
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
- A61B5/316—Modalities, i.e. specific diagnostic methods
- A61B5/318—Heart-related electrical modalities, e.g. electrocardiography [ECG]
- A61B5/344—Foetal cardiography
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B7/00—Instruments for auscultation
Definitions
- the present disclosure relates, generally, to the non-invasive measurement of a physiological process such as, but not limited to, the detection of foetal heart (cardiac) and/or pregnant uterus signals through interposed maternal tissue. More particularly, the disclosure relates to a method of, and equipment for, non-invasively measuring a physiological process which can be used, inter alia, for detecting foetal cardiac activity and/or the presence of a pregnant uterus to allow an operator to determine the pregnancy status of the female, the stage of pregnancy, the number of foetuses present within the pregnancy and the health of the foetuses.
- a physiological process such as, but not limited to, the detection of foetal heart (cardiac) and/or pregnant uterus signals through interposed maternal tissue. More particularly, the disclosure relates to a method of, and equipment for, non-invasively measuring a physiological process which can be used, inter alia, for detecting foetal cardiac activity and/or the presence of a pregnant uterus to allow an operator to determine the pregnancy status of
- the applicants are aware of various methods for determining pregnancy status, the number of foetuses present and the stage of pregnancy within females (animals and humans).
- the methods that are used may be divided into two broad categories; physical detection of the foetus and/or pregnant uterus and laboratory-based methods for detecting chemical and/or hormonal changes within the female that are associated with pregnancy.
- Physical methods include the manual palpation of the foetus and pregnant uterine structures by an experienced operator. In humans this service is typically provided by medical practitioners and in animals by veterinary surgeons. For example, in cattle, the foetus along with changes to the uterine environment associated with pregnancy can be manually detected by per rectum palpation of the uterus and its contents from around 35 days of pregnancy by an experienced operator. Larger animals (such as horses and cattle) are amenable to per rectal manual palpation of the uterine contents and uterine environment and, as such, pregnancy may be detected at an earlier stage than for animals that cannot be submitted to this process (e.g. humans, dogs, cats, sheep, pigs).
- US ultrasound
- Ultrasound-based methods transmit high frequency sound waves towards structures under examination and record reflected sound waves. These reflected waves are processed and usually converted to visual images for assessment by the operator.
- One of the US methods employed is two-dimensional real time US which uses a transducer array to create an image of the structures within the projected (and reflected) sound beam. This method requires skill to direct the transducer to the appropriate site, to exclude interposed air pockets and to interpret signal and images that are obtained.
- RT-Mode US Another US method is RT-Mode US which allows identification of foetal age, the presence of foetal death, multiple foetuses (i.e. litters) and sexing of foetuses.
- High frequency transducers are needed to visualise delicate uterine and foetal structures. These higher frequencies are characterised by poor tissue penetration, necessitating close internal positioning of the probe and highly skilled operators.
- a (Amplitude)-Mode US uses a reflected sound wave to determine the depth of tissue structures below the probe. Again, significant skill is required to move the device into the appropriate position and to interpret the output.
- B (Brightness)-Mode US is similar to A mode ultrasound except the reflected sound wave is converted to light of an intensity that mimics the amplitude of the reflected sound.
- A- and B- Mode US methods have been described in pregnancy diagnosis in animals.
- M Mode US uses a single beam of sound and the reflected signal is used to update a visual presentation of movement of the interfaces between surfaces continually.
- the frequency of transmitted sound waves is typically very high and therefore this method is useful to visualise rhythmic movements (e.g. the heart) and for assessing size of structures.
- M mode is used extensively in human cardiac and foetal cardiac imaging.
- Doppler US measures the change in frequency that occurs when transmitted sound waves are reflected from moving surfaces (or fluids). This change in frequency is converted to an audible signal that the operator may use to identify movement (such as due to the presence of a foetus). The foetal heart and circulatory movement can be detected with this method along with changes to maternal uterine blood flow as blood flow increases to meet foetal and placental demand.
- Doppler US probes must be directed against the structure in question and at an angle that is not perpendicular to the plane of movement. As such, reasonable skill is required to produce a diagnostic signal.
- Doppler US allows identification of multiple foetuses (e.g. the detection of multiparous pregnancies and estimated litter size). Doppler US has not proved reliable in pigs or cattle pregnancy diagnosis being associated with low sensitivity.
- ECG electrocardiogram
- the foetal ECG signal from external leads applied to the mother in late pregnancy in cattle is around 10 ⁇ V and significant electrical noise from the farm environment (e.g. from milking machines, electrical fences, etc.) is often present.
- a study in horses found the variability in signal strength arising from different lead positions and the numerous lead configurations to be the greatest challenge to the use of ECG.
- the study also found great variability in foetal heart rate in horses; in contrast to cattle.
- Other studies have found equine foetal heart rate monitoring using ECG successful but time consuming to obtain.
- Twin foetuses are readily detected using external ECG in horses. Electrode attachment to the skin of the mother is not without risk.
- the abdominal electrode especially is resented by many mares necessitating movement to a more lateral position, away from the ventral midline.
- the maternal ECG of dairy cows may also experience changes associated with pregnancy.
- a standard six-limb ECG identified two significant findings: (1) for lead II, the T-wave is negative for most pregnant cows and positive for non-pregnant cows and (2) pregnant cows generally demonstrate a right axis deviation in the mean electric axis when compared to non-pregnant cows (i.e. no axis deviation).
- Laboratory-based analytical methods of pregnancy diagnosis require the collection of a diagnostic sample obtained from the mother (e.g. blood, urine, milk, faeces). The sample is analysed to determine the presence of or level of a specific hormone or chemical (metabolite) that is correlated to pregnancy status and, for some, to the stage of the pregnancy.
- a diagnostic sample obtained from the mother (e.g. blood, urine, milk, faeces).
- the sample is analysed to determine the presence of or level of a specific hormone or chemical (metabolite) that is correlated to pregnancy status and, for some, to the stage of the pregnancy.
- These methods require significant efficiencies in sample collection, identification, processing and reporting to minimise time lag and identification errors.
- Many are intrusive, requiring invasive sample collection (e.g. blood).
- Many assays require laboratory support and/or prolonged sample processing time and are therefore not able to provide a diagnosis to the operator within a few minutes of collection of the sample.
- a method of non-invasively measuring a physiological process includes:
- pre-processing the signal of interest to enhance the signal of interest and to suppress other received signals that are not of interest.
- the method has particular application in the detection of pregnancy in domestic animals. It will, however, be appreciated that the method is equally applicable in the detection of pregnancy in humans as well as other animals such as pets, wild animals, etc.
- the physiological process to be measured may be the presence of a foetal cardiac signal and embodiments will be described with reference to that application below.
- the method may therefore include determining the presence of foetal cardiac signals (including but not limited to auditory, kinetic, and electrical signals) within naturally radiated signals obtained from the placement of one or more receivers against or near the body of the subject being examined, i.e. the female whose maternal condition is to be determined.
- foetal cardiac signals including but not limited to auditory, kinetic, and electrical signals
- the method may include detecting the presence of one or more cardiac signals by determining if periodic repetitions at a rate consistent with a foetal heart rate (about
- the method may include, once the presence of one or more cardiac signals has been detected, determining if a foetal cardiac signal is present.
- the method may include determining from the receiver data that there is more than one cardiac signal present and, if more than one cardiac signal at different rates is found in the receiver data, confirming pregnancy of the subject.
- the method may include, if only one cardiac signal is detected, determining if the detected signal is maternal or foetal.
- the method may includes measuring the maternal heart rate separately.
- the method may include measuring the maternal heart rate by at least one of (a) applying the at least one receiver to a region where the maternal cardiac signal is known to be strong and foetal cardiac signals are known to be absent or weak and (b) measuring the maternal heart rate by means other than the use of the at least one receiver, such as by using a stethoscope.
- the method may include processing the received signals to determine signal quality.
- the method may include monitoring and evaluating variations in signal quality in real time and feeding data relating to the signal quality back to an operator to allow, if necessary, remedial action to be taken to improve the signal quality.
- the method may include, once the data have been obtained, automating a task of diagnosing the presence of a foetal cardiac signal using at least one predetermined technique.
- These techniques may include: (a) classical statistics, such as analysis of signal amplitude and power distributions; (b) digital signal processing, which include time-domain and frequency-domain methods such as auto- and cross- correlation, (c) spectral and cepstral analysis, (d) separation of components (blind source separation) by means of methods such as independent component analysis or principal component analysis, (e) pattern recognition and data clustering that are used to find a desired signal component in signal noise and clutter, (f) neural networks and kernel methods (such as support vector machines), (g) the use of heuristics - "rules of thumb” which help to interpret the data, such as might be applied by a human data interpreter, or the like.
- the method may include using a number of the techniques in parallel.
- the method may include effecting pre-processing enhancement of interest, in the form of some kind of filtering, prior to applying the at least one technique.
- the method may include effecting pre-processing enhancement of the signal by using a combination of low-pass, band-pass, and high-pass filtering.
- the method may include combining outputs of the applied techniques, using a classifier, to make a final decision.
- the classifier sometimes called a “committee of experts", may use methods such as Bayesian statistics to allocate a weight or importance to the outcome, based upon the signal quality, the known reliability of the method, and a knowledge of prior probabilities of accuracy.
- the method may include further outputting, as part of the decision, data relating to a measure of confidence in the decision which may be of use in the business or agricultural health context in which the diagnosis is taking place.
- the method may include combining historical data with data obtained from the a least one receiver to produce an updated estimate of pregnancy status, number of foetuses, foetal age and predicted time until parturition for a number of subjects being investigated.
- the historical data may include, but is not limited to, female electronic animal identification data, management and production data and previous pregnancy diagnosis data.
- the method may include transferring multi-field data in a format suitable for inclusion with computer software.
- Equipment for non-invasively measuring a physiological process includes: at least one receiver to be placed relative to a body of a subject being examined to detect at least one signal from the body of the subject;
- a discrimination unit for determining if the at least one signal is a signal of interest associated with the physiological process
- a processor for processing the signal of interest to enhance the signal of interest and to suppress other received signals that are not of interest.
- the equipment may include a receiver pack comprising a plurality of receivers operable to detect different types of signals.
- the receiver pack may include at least some of the following types of receivers:
- At least one audio receiver for receiving sound wave information from the subject being examined
- At least one electrical receiver each of which may comprise an electrode, for receiving muscle and nerve electrical activity signals from the subject being examined;
- At least one pressure receiver including an accelerometer, for receiving kinetic information from the subject being examined.
- the processor may be in communication with the receiver pack for processing the received signals, performing computations to enhance the signal of interest and to filter noise and other signals not of interest to provide refined signals.
- the processor may employ algorithms to interpret the refined signals, optionally combine the refined signals with historical data and provide an output in the form of information on the physiological process.
- the physiological status in the preferred application of the equipment is the detection of a pregnancy status of a female domestic animal, the likely number of foetuses present, the estimated age of the pregnancy and the estimated time to parturition.
- the discrimination unit may comprise a pre-processing module for effecting pre-processing of the signal of interest.
- the pre-processing module may use a combination of low-pass, band-pass and high-pass filtering.
- the processor may include an evaluation module for monitoring and evaluating variations in signal quality in real time.
- the equipment may include an enunciator for alerting an operator to the signal quality.
- the processor may be configured to automate a task of diagnosing the presence of a foetal cardiac signal using at least one predetermined technique.
- the processor may be configured to use a number of the techniques in parallel.
- the processor may include a classifier which is operable to combine outputs of the applied techniques to make a final decision about the signal of interest. Further, the processor may be configured to output, as part of the decision, data relating to a measure of confidence in the decision.
- the equipment may include a data storage system for recording and accessing data from multiple animals and events.
- the equipment may include a portable power supply.
- the equipment may include a data input and processing system for combining historical and current data including, but not limited to, female electronic animal identification data, management and production data and previous pregnancy diagnosis data for concurrent processing and output.
- the processor may be operable to combine, analyse and interpret serially obtained foetal cardiac signals from individual females with the currently obtained signal to produce an updated estimate of pregnancy status, number of foetuses, foetal age and predicted time until parturition using all combined information.
- the equipment may include an output system for transferring multifield data in a format suitable for inclusion with computer software.
- Fig. 1 shows a block diagram of an embodiment of equipment for non- invasively measuring a physiological process
- Fig. 2 shows a flow chart of steps used by a component of the equipment of Fig. 1 for carrying out an embodiment of a method of non-invasively measuring a physiological process
- Fig. 3 shows a flow chart of steps used by a component of the equipment of Fig. 1 for carrying out another embodiment of a method of non-invasively measuring a physiological process.
- reference numeral 10 generally designates an embodiment of equipment for non-invasively measuring a physiological process.
- the equipment 10 has particular application in the detection of pregnancy in domestic animals and, more particularly, in animals used in animal husbandry such as cattle, sheep, pigs or horses.
- animal husbandry such as cattle, sheep, pigs or horses.
- the equipment will be described with reference to that application but those skilled in the art will readily appreciate that the equipment, and associated method, could be used in other applications where rapid, cost effective, early detection of pregnancies is desirable.
- the equipment and method can also be used in the detection of pregnancy in humans.
- the equipment 10 is used for recording and processing of passively received foetal cardiac signals.
- a "passively received" signal is one which is naturally radiated from the animal's body as opposed to a signal generated by an actuator such as would occur with ultrasound techniques.
- These naturally radiated cardiac signals include, but are not limited to, audio signals, electrical signals, kinetic signals and physiological signals.
- the equipment 10 includes a receiver pack 12.
- the receiver pack 12 comprises a plurality of receivers or sensors 14.
- the sensors 14 are electrodes able to be placed relative to the animal without any preparatory work being done on the animal's body. Examples of such electrodes are disclosed in the applicant's co-pending International Patent Application No. PCT/AU2009/000873 dated 6 July 2009 and entitled "A system for sensing electrophysiological signals".
- the sensors 14 of the receiver pack 12 are placed against or near the body of a subject being examined, for example, a pregnant cow.
- the sensors 14 are used to capture signals radiated from the body of the animal in question. As indicated above, theses sensors can be used to capture audio, kinetic and electrical signals passively.
- the equipment 10 includes a processor in the form of a data processing unit 16 to which the receiver pack 12 is connected via a cable 18. It will be appreciated that, instead, the receiver pack 12 could communicate wirelessly with the processor 16. Further, the receiver pack 12 and the data processing unit 16 are preferably contained together in a portable unit.
- the processor 16 includes a signal processor 20 which processes signals output by the sensors 14 of the receiver pack 12.
- the processor 16 further includes a microprocessor 22 which controls operation of the signal processor 20 as well as a data storage unit 24 in which data relating to the animals being tested are stored.
- the equipment 10 further includes an output data port 26 and an input data port 28.
- the equipment 10 also includes a power supply 30 so that the equipment 10 is portable.
- the power supply 30 is a battery powered power supply using re-chargeable batteries.
- the equipment 10 is a low-cost device for detection of pregnancies in domestic animals.
- the equipment 10 can be used to provide an indication of the number of foetuses being carried by the animal, the foetal age and the predicted time until parturition. It is also envisaged that the equipment 10 can be used in a rapid manner so that a number of animals can be tested at any one time in rapid succession.
- the sensors 14 are placed on and/or in proximity to the animal's body.
- the sensors 14 may be arranged in an array on the face of the unit. The face of the unit is then placed against the animal's body.
- the sensors 14 detect signals of different types associated with the animal being investigated such as audio, electrical, kinetic and physiological signals.
- the signals detected by the sensors 14 are fed to the signal processor 20 where the detected signals are processed.
- the signal processor 20 includes a pre-processor 20.1 in the form of discrimination unit for determining if at least one signal of interest is present.
- a signal of interest is a signal associated with a heartbeat of a foetus carried by the animal.
- the discrimination unit 20.1 of the signal processor 20 makes use of a combination of low-pass filters, band-pass filters and high-pass filters. In addition, the discrimination unit of the signal processor 20 uses more advanced signal extraction techniques such as blind source separation.
- the steps employed by the signal processor 20 of the equipment 10 are shown in Fig. 2 of the drawings. More particularly, at step 32, the received signals from the sensors 14 of the receiver pack 12 are filtered using analog, continuous time filters to limit the signal to the frequency range of interest, the frequency range being approximately 2Hz-200Hz. At step 34, the filtered signals are amplified as much as possible using an amplifier of the signal processor 20 but taking care to ensure that the maximum signal excursion remains within the range of an analogue to digital converter used.
- the analogue signals are digitised using an analogue to digital converter to obtain digitised sensor data.
- the digitised sensor data are stored in the memory 24 for a recording period of at least several seconds at step 38.
- the signal processor 20 processes the stored sensor data by applying matched filters to enhance the detection of individual heartbeats from the signals detected by the sensors 14 of the receiver pack 12.
- the signal from each sensor 14 will contain a mixture of signals from different sources such as, for example, the maternal heartbeat, a foetal heartbeat, if present, muscular contractions and other noise signals.
- signal enhancement is carried out by the signal processor 20.
- a blind source separation technique is used at step 42 to extract signals belonging to the various sources.
- An example of a blind source signal separation technique used is independent component analysis.
- Each source signal is checked for periodicity using an autocorrelation analysis at step 44.
- the signal is periodic with a rate between about 30 beats per minute (BPM) and 300 BPM, it is classified as a heartbeat signal. It is to be noted that this range is applicable to larger animals such as cows and will be different for smaller animals such as sheep or pigs.
- a decision of "pregnant" is registered at step 46. If only one heartbeat signal is detected and this heartbeat signal is periodic with a rate between about 120BPM and 300BPM, it is likely that a single foetal heartbeat from a healthy foetus has been detected. A retest may then take place with at least one of the sensors 14 closer to the heart of the animal being examined to confirm the pregnancy status. Conversely, if only one heartbeat signal is detected in the range of about 3 OBPM and 120BPM a "non-pregnant" decision is rendered.
- Detected heart rates outside this range may indicate the presence of a foetus of unknown health status and a retest at a future stage is recommended.
- steps 32-38 are the same.
- the incoming digitised signal is assessed by the signal processor 20 for signal quality.
- the signal is subjected to digital filtering and, at step 50, the filtered signal is processed to derive a measure of signal quality.
- the subjects of the method may well be animals, such as cattle, which cannot practically be immobilised or anaesthetised, and which may be kept in an open-air environment which is inhospitable to electronic measurement systems, the application of the sensors 14 is likely to be highly variable, with a consequential variation in signal quality. This variation is measured and evaluated in real time and data relating to signal quality are fed back to an operator, as indicated at 52.
- the equipment 10 includes an enunciator 54 for indicating the signal quality to the operator.
- the enunciator 54 may be an audible and/or visual device.
- the enunciator 54 may emit an audible alarm if the signal quality is below a required threshold or, conversely, an audible signal may be emitted if the signal quality is adequate.
- the enunciator 54 may include a display for displaying a measure of the signal quality.
- ECG electrode sensors 14 have lost contact or are in a high impedance state as a result of poor skin contact. This will result in a distinctive signal, characterized perhaps by extensive saturation or oscillation, and the operator can be informed that electrode contact is poor and the equipment 10 must be adjusted. This can be identified at the level of individual electrode sensors 14.
- a further type of loss of quality might be an ECG signal which is swamped by excessive electromyograph (EMG) signals arising from muscle movement in the animal close to the electrode sensors 14. In this case the operator action might be to wait until the animal settles or manage the animal in such a way as to reduce muscle movement.
- EMG electromyograph
- the quality of the signal has a significant effect on the success of the downstream processing and diagnostics, and is a key parameter which can be used explicitly in the following diagnostic techniques or methods carried out by the signal processor 20 and as referenced at 56 in Fig. 3 of the drawings.
- the diagnostic methods 56 include techniques of classical statistics, such as analysis of signal amplitude and power distributions; techniques of digital signal processing, which include time-domain and frequency-domain methods such as auto- and cross-correlation, spectral and cepstral analysis; separation of components (blind source separation) by means of methods such as independent component analysis or principal component analysis.
- techniques of pattern recognition and data clustering that are used to find a desired signal component in signal noise and clutter and a very large number of neural networks and kernel methods (such as support vector machines) which are able to be used.
- heuristics "rules of thumb" which interpret the data, such as might be applied by a human data interpreter, - assists in adding accuracy to the other methods.
- a simple heuristic is that the maternal heart rate (of an otherwise healthy dam) should fall within a typical range, and the foetal heart rate (of an otherwise healthy foetus) should fall within a typical range, different from that of the dam, and this can help to separate the two heart rate signals.
- the signal Prior to applying the diagnostic method, the signal is pre-processed using digital filtering as shown at step 58.
- This classifier 60 uses methods such as Bayesian statistics to allocate a weight or importance to the outcome, based upon the signal quality, the known reliability of the method and a knowledge of prior probabilities of accuracy.
- the output of the equipment 10 is the decision 46 and a measure of confidence 62 in the decision 46 which may be of use in the business or agricultural health context in which the diagnosis is taking place is also output.
- Data relating to pregnant females are output on the data output line 26.
- the data can be correlated with data input on the input line 28.
- the data input on the input line 28 may relate to historical data in regard to the herd, previous pregnancies etc.
- the microprocessor 22 may process the data output on the output line 26.
- the data output can simply be displayed on a display (not shown) or can be modified for use with computer software and herd management devices.
- equipment 10 is provided which enables rapid, low-cost detection of pregnancy in animals in herds without the need for skilled labour to determine pregnancies.
- little, if any, trauma is imparted to the animals being investigated.
- reproductive efficiency is a major driver of financial performance of livestock enterprises. Assessing individual animal pregnancy status is key information for decision making because management requirements, maintenance costs and income potential are different for pregnant and non pregnant animals. Culling, separation, feeding and other management decisions are influenced by individual animal pregnancy status. These include, but are not limited to, determining dates for drying lactating dairy cows off, for weaning beef calves from their mothers, for culling and sale (all species), and for hastening return to mating for animals not detected as pregnant (all species). The pregnancy status of individual animals offered for sale is also often legally required information. The provision of the equipment 10 facilitates these management decisions.
- EID Electronic individual animal identification
- Systems that can record data electronically, link with existing information, use algorithms to perform management decisions (eg drafting) based upon inputs are increasingly being used.
- the recording of pregnancy status information electronically using the equipment 10 in a manner that can link with EID provides an advantage.
- the simple electronic recording of pregnancy test results with animal EID reduces identification and transcription errors.
- the identification of animals pregnant with more than one foetus is of great value (eg sheep, pigs and cattle). These animals can be marked for preferential treatment and management practices implemented that can optimise the pregnancy.
- reproductive performance of many farm animals is declining. Early and regular pregnancy diagnostic capability allows farmers to identify animals with superior reproductive performance. These animals may be selected to breed replacements and animals with lesser reproductive performance preferentially culled along with their offspring.
- the availability of the equipment 10 alleviates these problems.
- the regular, early, reliable, convenient and accurate diagnosis of pregnancy of individuals using the equipment 10 assists in efficient and profitable individual farm animal management systems being deployed.
- an ability to undertake repeated, safe, pregnancy diagnosis confirmation will be an advantage for many women.
Abstract
Description
Claims
Priority Applications (5)
Application Number | Priority Date | Filing Date | Title |
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NZ597459A NZ597459A (en) | 2009-07-06 | 2010-07-05 | Non-invasively measuring physiological process |
US13/382,877 US8652063B2 (en) | 2009-07-06 | 2010-07-05 | Non-invasively measuring physiological process |
AU2010269114A AU2010269114B2 (en) | 2009-07-06 | 2010-07-05 | Non-invasively measuring physiological process |
BR112012000276A BR112012000276A2 (en) | 2009-07-06 | 2010-07-05 | noninvasive method of measuring a physiological process; and equipment for noninvasive measurement of a physiological process. |
EP10796575.8A EP2451347A4 (en) | 2009-07-06 | 2010-07-05 | Non-invasively measuring physiological process |
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AU2009903169A AU2009903169A0 (en) | 2009-07-06 | Non-invasively measuring physiological process | |
AU2009903169 | 2009-07-06 |
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EP (1) | EP2451347A4 (en) |
AU (1) | AU2010269114B2 (en) |
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Cited By (2)
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EP2668897A1 (en) * | 2011-01-25 | 2013-12-04 | Public University Corporation Nara Medical University | Fetal heart potential signal extraction program, fetal heart potential signal-discriminating apparatus and pregnancy monitoring system using same |
WO2015033244A1 (en) * | 2013-09-09 | 2015-03-12 | Koninklijke Philips N.V. | Fetal heart rate extraction from maternal abdominal ecg recordings |
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EP2668897A1 (en) * | 2011-01-25 | 2013-12-04 | Public University Corporation Nara Medical University | Fetal heart potential signal extraction program, fetal heart potential signal-discriminating apparatus and pregnancy monitoring system using same |
EP2668897A4 (en) * | 2011-01-25 | 2015-04-22 | Public University Corp Nara Medical University | Fetal heart potential signal extraction program, fetal heart potential signal-discriminating apparatus and pregnancy monitoring system using same |
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CN105530857A (en) * | 2013-09-09 | 2016-04-27 | 皇家飞利浦有限公司 | Fetal heart rate extraction from maternal abdominal ECG recordings |
US20160198969A1 (en) * | 2013-09-09 | 2016-07-14 | Koninklijke Philips N.V. | Fetal heart rate extraction from maternal abdominal ecg recordings |
RU2676002C2 (en) * | 2013-09-09 | 2018-12-25 | Конинклейке Филипс Н.В. | Fetal heart rate extraction from maternal abdominal ecg recordings |
US10531801B2 (en) | 2013-09-09 | 2020-01-14 | Koninklijke Philips N.V. | Fetal heart rate extraction from maternal abdominal ECG recordings |
US11337616B2 (en) | 2013-09-09 | 2022-05-24 | Koninklijke Philips N.V. | Fetal heart rate extraction from maternal abdominal ECG recordings |
Also Published As
Publication number | Publication date |
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US8652063B2 (en) | 2014-02-18 |
NZ597459A (en) | 2014-01-31 |
EP2451347A1 (en) | 2012-05-16 |
BR112012000276A2 (en) | 2016-02-16 |
AU2010269114A1 (en) | 2012-02-02 |
US20120108989A1 (en) | 2012-05-03 |
EP2451347A4 (en) | 2013-07-17 |
AU2010269114B2 (en) | 2014-05-08 |
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