the preferred p2m system is a monitoring device with two major subsystems , one to measure signals and the other to process data into meaningful information . fig1 shows a schematic of the system , and fig2 shows a perspective view of the system . first , the piezoelectric film , an electrically active fluoropolymer converts mechanical energy such as movement caused by a heartbeat into voltage measurements capable of supporting time series analysis techniques . second , the voltage is recorded by and analyzed using a microcomputer controlled system , the purpose of which is to discriminate the signal from background noise and display it on a screen or printout . techniques such as preamplifying and preconditioning through the use of high and low - band pass filters reduces noise . the piezoelectric material 1 used is the polymer polyvinylidene fluoride ( pvdf ), which can be shaped into cables , thin film , or thick tiles . pvdf piezoelectric film is environmentally rugged , lightweight , flexible , inherently reliable , sturdy , easily repairable and transportable with excessive assembly or disassembly . since the material is inert , it may be used inside the human body . ultraviolet radiation passes harmlessly through the pvdf film , which may be produced in varying thicknesses . in addition , the piezoelectric film is waterproof , operates between 0 and 145 degrees centigrade , and does not tear under stress . pvdf may convert a temperature reading into an electric output . the pvdf film is incorporated into a fluid - filled vinyl pad , approximately 10 cm by 10 cm in surface area . this is placed on / under / above various locations of the patient . p2m detects cardiac and respiratory motion , and monitors pulse , respiration and apnea episodes 3 . cardiac and respiratory movements are simultaneously recorded by selective filtering of original signal . the piezoelectric element 1 is a pressure — sensing detector acting as a highly sensitive strain gage providing high dynamic range and linearity . analog signals are fed through a band - pass filter into an amplifier (× 200 -× 5000 ) 5 and are visually displayed . analog acoustic signals are converted to digital values using a multi - channel converter 7 at a sampling rate of up to 5 khz . data is transformed to the frequency domain using fast fourier transform ( fft ). the system uses a microcomputer 9 for recording , analysis and presentation of data , which allows for on - line assessment of data and realtime decisions . in its simplest mode of operation pvdf piezoelectric film 1 acts as a piezoelectric strain gage . the voltage output is up to four orders of magnitude higher than that produced by a nonamplified signal from circuitry used with resistive wire . linearity and frequency response are excellent . although similarities to a strain gage exist , current need not be applied since the device is electrically self - generating . unlike the strain gage , the present invention does not produce an electric charge ad infinitum with sustained stress . the slowest frequency the polymer film detects is a thousand seconds for an electrical event to occur , and the highest is one gigahertz ( microwave ). the piezoelectric film is passive and biologically non - hazardous , as opposed to traditional strain gages that require an applied current . pvdf sheets are commercial off - the - shelf ( cots ) products , the type and specifications of which were chosen based on optimum sensitivity range and resilience . each sheet contains seven - foot attached shielded twisted - pair ( for noise rejection ) leads 11 to transmit the charge produced by the sheets . the piezoelectric sheets 1 are placed under a patient &# 39 ; s chest and foot or at similarly remote areas of the body , or may be put on like a wrapped cuff . the change in pressure exerted by the patient &# 39 ; s respiration and heartbeat causes the piezoelectric film to generate voltages , which is carried via nonmagnetic miniature coaxial cable 11 through a radio frequency filter 13 . the signal is then directed to a high input - impedance amplifier 5 and computer system 7 for data processing . a conventional oscilloscope and a chart recorder displays the output . respiration and heart rate 15 are then calculated by the energy spectrum from the time series data . several techniques reduce noise and vibration interferences . active cancellation uses two piezoelectric sensors , one of which is not in contact with the body . the sensor not attached to the body is exposed to environmentally acoustic and vibrational signals , while the sensor attached to the body is exposed to environmental as well as body signals . subtraction of one output from the other output yields the body signal of interest . another preferred technique to reduce noise involves band - pass filtering / band - stop filtering . by identifying the extraneous electronic or acoustic noise and its particular frequencies , band - pass or band - stop filtering eliminates extraneous signals from the overall signal . additionally , signal processing techniques that use a prior knowledge of the expected signals extract the desired information from the piezoelectric signal . spectral techniques help to identify the frequencies and amplitudes of the events of interest and discern them from extraneous noise . cardiac action analysis uses a bandpass frequency limit of 0 . 1 - 4 . 0 hz , and respiration analysis uses a frequency limit from 0 . 01 - 3 . 0 hz . the filtered cardiac and respiration signals are fed to a recording system . body movements are analyzed by bandpass filtering the original signal with frequency limits from 0 . 1 - 20 hz . once the signal produced by the film sensor is converted to voltages , amplified and filtered , it is processed through the p2m instrumentation . the hardware equipment includes , but is not limited to , a 586 processor computer 9 with enhanced ram and disk capacity to handle large amounts of data . a board with a range that includes acoustic frequencies facilitates data acquisition , signal conditioning and signal processing . for system operation , a master program 17 combines the three separate software modules of data acquisition / control , signal processing / analysis , and data display / user interface . the labview ™ “ g ” graphical programming language was used for all three subroutine programs . the analog voltage signal is digitized and analyzed in time and frequency domains . routines developed for signal conditioning and analysis include digital filtering , spectral analysis , auto correlation , and noise — rejection programs . the data is displayed real - time in either monitor or acquisition mode . monitor mode displays the current data and discards old readings as new updates are processed , while acquisition mode saves data for future analysis . the voluminous data must not exceed the disk - storage capacity of the computer in acquisition mode . for protection and ease of transport , the entire p2m system 19 is encased in a metal technical enclosure 21 with casters ( not shown ) and locking glass door ( not shown ), as shown in fig2 . the equipment also includes a medevac stretcher 23 on which the sensor is mounted . this device may be incorporated into a litter to eliminate the need for patient attachment or miniaturized as a portable field device in a purse with a wireless communication setup . significant field and analysis testing was conducted to confirm the workability and accuracy of the p2m system . the piezoelectric film measures mechanical , thermal and acoustic signals . that high sensitivity is necessary to measure vital signals non - intrusively . for pulse rate , the physical beating of the heart is transmitted through the body into the piezo - film sensor pad as mechanical impulses . the respiration is measured by the mechanical impulse transmitted to the sensor based on chest movements . the sensitive piezo - film sensor pad measures all extraneous movement and speech , resulting in a voltage signal output that is superimposed upon the physiological signals . as a result , movement or speech by the subject may cause a reading error . the p2m sensor measures all physical impulses in the measuring environment , including the patient &# 39 ; s physiological signals , nearby human noise and activity signals , noise and vibration from the machinery , and electromagnetic ( em ) noise emitted from the lights and instrumentation . while the output signal includes all of these signals , many are too weak to affect the measurement while others such as em noise corrupt the reading . running the signal through filters and other signal — processing algorithms removes the noise . the conditioned signal is then analyzed through routines , including a fast fourier transform ( fft ) which identifies the primary signal frequencies . for a still , speechless patient , the primary frequency is usually respiration , and the second highest frequency is heart rate . patient positioning and frequency harmonics may complicate the distinction , requiring additional logic to separate and identify the heart and respiration frequency peaks . the logic algorithms must be robust enough to define the respiration and heart peaks for a variety of conditions . to increase resolution , a large number of high sampling rate data points were selected and re - sampled at a lower rate to simplify computation for accurate analysis . the minimum sampling interval was thirty seconds . fig3 shows the results for the twenty respiration / pulse - rate measurements performed with the p2m system . human evaluator measurements were performed simultaneously as a control . p2m accurately measured pulse 25 and respiration 27 under ideal conditions , but patient movement or speech interfered with accurate measurement . heart rate measurement quality was not reduced by the absence of respiration , and p2m matched the control measurement results 29 , 31 with an error of less than beat per minute . fig4 shows the p2m front panel in acquisition mode . the upper graph 33 displays a thirty - second window of time - series measurements of all physiological signals . heartbeat spikes are shown in the upper ( time series ) graph 33 , along with a lower - frequency sinusoidal function which corresponds to the respiration signal . the lower graph 35 shows the same data in the frequency domain . the first and largest spike 37 corresponds to approximately 16 . 4 respirations per minute . the control group 31 measured 17 ± 2 respirations per minute . the large amplitude of the spike indicates that respiration is the largest impulse measured by the sensor pad . the second - largest spike 39 is sixty times per minute , which was identical to the actual heart rate measured by a fingertip - clip heart - rate monitor . the power as measured by the amplitude is less than one - third of that found in the respiration frequency , but the ratio varies based on the physiology and sensor pad positioning of the patient . the smaller spikes 41 in the lower graph represent respiration and heart - rate harmonics , a result of the harmonics not being a perfect sinusoidal function . since the heart rate might fall at exactly the same frequency as a respiration harmonic , it is necessary for logic algorithms to check for harmonics . the heart rate and respiration harmonics may be differentiated by comparing signals taken from different parts of the body . the buttons and menus 43 on the front panel of the interface program enables the control of data acquisition and analysis routines . the thirty - second data records may be saved to file for archiving or additional evaluation . fig5 shows the p2m system in monitor mode . the top graph 45 shows the time - series data , with the characteristic higher - frequency heartbeat spikes 47 superimposed over a lower — frequency respiration wave 49 . the middle graph 51 shows heart rate 53 and respiration 55 as updated every five seconds . as a new five - second data string is acquired , the oldest five seconds of data is discarded , and the heart rate and respiration are re - calculated by analyzing the thirty - second data string with the new data . the upper curve 53 is colored red to signify heart rate , while the lower curve 55 is colored blue to signify respiration . heart rate appears steady in the mid - 50s range , with respiration in the mid - teens . both compare favorably (± 2 ) with human control measurements . the anomaly 57 after 25 updates is attributable to patient movement or an extraneous and errant noise / vibration event . the bottom graph 59 shows an fft of the time - series signal . regular voltage signals of heart beat provide strength signals as voltage levels that are related to blood pressure . times between signals at varied parts of the body or patterns of secondary signals provide information on circulation or blockage or interference with blood flow . in another preferred embodiment , fig6 shows a schematic view of the p2m system with a single passive sensor 61 positioned on a patient 63 . fig7 shows one of the graphical user interfaces ( gui ) of the p2m system . the upper chart 65 shows a 30 - second window of digital voltage data , where the low - frequency oscillations are caused by respiration and the higher - frequency spikes are the result of heartbeat measurements of the patient on the litter . the time - series signal is converted to frequency data via a fourier transform and displayed as a power spectrum , shown in the middle chart 67 . from this data , pulse and respiration can be extracted by examining the power associated with the dominant frequencies 69 . in a preferred method of blood pressure measurement passive measurement of blood pressure ( systolic and diastolic ) may be conducted using pulse wave analyses . measurement and characterization of the pulse - wave velocity ( pwv ), or alternately , the pulse - wave travel time ( pwtt ), inherently requires more than one measurement location . thus , plural sensors are required for measurements in different locations . the sensors may measure pulse - wave characteristics , for example , along the brachial artery , along with other measurements described herein . fig8 shows measurement results of the pulse at two locations along the arm . the temporal separation between the two corresponding peaks 71 , 73 gives the pulse - wave travel time ( pwtt ). this value can be used to correlate systolic and diastolic blood pressure . as such , the calibration must be performed simultaneously for several measurements of pwtt and blood pressure to construct a calibration curve . barschdorff & amp ; erig showed that the relationship between blood pressures ( systolic and diastolic ) are approximately linear with pwv and pwtt . testing and evaluation of the p2m system was performed at tamc in february , 1998 . simultaneous measurements of pulse and respiration were performed with the p2m , an electronic monitor , and by human evaluation . fig9 shows a photograph of the testing performed at tamc . a total of 11 volunteers were monitored following the project &# 39 ; s testing protocol . fig1 displays the results of the testing . the p2m was over 95 % accurate as compared to conventional methods , and the several instances where the p2m was not in agreement with conventional methods proved to be very valuable in subsequent modifications and improvements to the system software . in addition , 12 volunteer nurses performed physiological monitoring of pulse and respiration using the p2m , electronic monitor , and human evaluation . following the monitoring , the nurses completed a survey comparing and ranking the usage of the three methods . testing of the p2m system for pulse and respiration in a high noise and vibration environment was performed at wheeler army air field , on mar . 5 , 1999 . tests were - performed during static display of a medevac helicopter . the main purpose of the test was to characterize the high noise / vibration environment using the p2m , microphones and accelerometers . results showed that through filtering and signal analyses , the p2m was able to discern physiological signals from the high amplitude and frequency noise caused by the helicopter to output accurately pulse and respiration . no conventional methods were performed at this test due to the high - noise environment , which would render those methods useless . fig1 shows the high noise and vibration testing of p2m at wheeler army air field , on mar . 5 , 1999 . next , in response to inquiries made by the flight medics during the mar . 5 , 1999 testing at wheeler , the ability of p2m system to accurately monitor pulse and respiration through layers of clothing and gear was tested . fragmentation protective body armor , military oriented protective posture ( mopp ) gear , and a combination of the two were tested using the p2m system . results showed that the p2m performed with higher fidelity with the additional layers between the subject and the sensor , which is largely due to the increased contact area and efficient transmission of mechanical and acoustic signals through the solid layers . the single - sensor p 2 m configuration that has been demonstrated to accurately measure pulse and respiration is very sensitive to the patient position relative to the main sensor pad . the quality and magnitude of the physiological signals received by the system depends on this positioning . the preferred optimum placement is to situate the sensor directly beneath the center of the patient &# 39 ; s chest . if the sensor is moved from this placement , or if the patient position changes , the integrity of the incoming signal also changes . thus , a preferred configuration uses multiple sensors in a pattern that covers the entire region of the litter on which the patient would lie so that regardless of patient movement and position , there will always be one or more active sensors in optimum measurement placements . in a preferred embodiment , the invention is a passive system using an array of distributed sensors ( or “ multi - sensor ”) capable of accurately and robustly monitoring certain physiological signals of the human body . these signals , in turn , may be processed for determination of vital signs that are currently used by nurses and other caregivers , for example , heart rate , respiration , and systolic / diastolic blood pressure . passive monitoring of such parameters as cardiac output , cardiac function , and internal bleeding are within the scope of this invention . the invention uniquely provides a device that is passive ( completely non - invasive ), unobtrusive , and autonomous ; i . e ., the apparatus in no way interferes either with the patient &# 39 ; s mobility or with other monitoring equipment , and is capable of functioning with a minimum of technical expertise . in addition , the equipment functions reliably in high - noise environments and other situations that render alternative and existing methods ineffective . these environments include , but are not limited to , medical evacuation ( medevac ) by helicopter or ambulance , and operation through military oriented protective posture ( mopp ) gear and body armor . with the development of a reliable multi - sensor monitoring system for such rugged and noisy operation , the application to the hospital icu environment , where noise is substantially lower , is considerably more straightforward . completely non - invasive , passive , pulse , respiration , blood pressure ( and detection of cardiac output , internal bleeding , shock , etc .) measurements using a sensor system that is undetectable to the patient have considerable intrinsic value even in noise - free surroundings . the passive and autonomous operation of such a system is suitable for telemetry and real - time remote monitoring , and the final feature of the invention is a telemetry design feature for distance and remote monitoring . fig1 shows a schematic of the p2m using a passive sensor array and microelectronics incorporated into a medevac litter . a schematic of the inventive technology , incorporated into a medevac litter , is shown in fig1 below . the litter 75 is covered in an array 77 of 32 sensors , each of which can measure acoustic and hydraulic inputs from the patient 63 . each of these signals contains a measure of physiologically generated signal and environmental noise . the environmental noise on each pad will be similar , whereas the physiologically generated signals may be position dependent . this information is used to separate the signal from the noise using proven techniques . position dependent physiological signals are used to determine patient position , heart rate , respiration , blood pressure , pulse strength distribution , and potentially some measure of cardiac output . the invention may be incorporated into a wide range of applications apart from the medevac litter . the passive sensor array may be configured without much change to operate on a hospital bed or an ordinary mattress used at home . of particular note is the area of premature infant care . in this case , the attachment of sensor leads to the infant may often be difficult , causing irritation of sensitive skin and entanglement in leads . the sensor may be incorporated into equipment for use in both civilian and military sectors . the sensor may be incorporated into field equipment , clothes and uniforms . this includes , but is not limited to , cervical collars , body armor , biological and / or chemical hazard protection suits , extraction devices , clothes , cushions on seats and seatbacks . exercise equipment , such as stationary bicycles , treadmills or steppers may benefit by incorporating sensors into the supports . physiological indicators such as heart rate may be detected through handholds as an aid to regulating the exercise regime . other useful applications might include the use of a passive sensor system in a chair or couch used for psychological examinations . scrutiny of the subject &# 39 ; s physiological signs may give indications of emotional disturbance caused by trigger words or events during counseling . the size of each sensor , number of sensors in the array , and configuration of the sensor array may be tailored , without much experimentation , to particular needs and situations . for a mattress , for example , 32 or more sensors in a rectangular array may be required . the preferred passive sensor may use piezo - electric films and ceramics , hydrophones , microphones or pressure transducers . amplification hardware may include signal amplification circuitry and hardware , e . g ., charge amplifier . data acquisition hardware and signal processing hardware ( circuitry ) and software are used in the system . for the interface between sensor and patient either solid , fluidized ( air ) or fluid layer may be used , as for example , gel , water , foam , rubber , plastic , etc . the interface facilitates transmittal of physiological signals . the invention has great medical value for field monitoring , hospital monitoring , transport monitoring , and home / remote monitoring . for example , the invention may have application in every hospital for passive monitoring of patients . the invention being undetectable to the patient , which adds comfort to the monitoring process . while the invention has been described with reference to specific embodiments , modifications and variations of the invention may be constructed without departing from the scope of the invention .
passive physiological monitoring apparatus and method has a sensor for sensing physiological phenomenon . a converter converts sensed data into electrical signals and a computer receives and computes the signals and outputs computed data for real - time interactive display . the sensor is a piezoelectric film of polyvinylidene fluoride . a band - pass filter filters out noise and isolates the signals to reflect data from the body . a pre - amplifier amplifies signals . signals detected include mechanical , thermal and acoustic signatures reflecting cardiac output , cardiac function , internal bleeding , respiratory , pulse , apnea , and temperature . a pad may incorporate the pvdf film and may be fluid - filled . the film converts mechanical energy into analog voltage signals . analog signals are fed through the band - pass filter and the amplifier . a converter converts the analog signals to digital signals . a fourier transform routine is used to transform into the frequency domain . a microcomputer is used for recording , analyzing and displaying data for on - line assessment and for providing realtime response . a radio - frequency filter may be connected to a cable and the film for transferring signals from the film through the cable . the sensor may be an array provided in a medevac litter or other device for measuring acoustic and hydraulic signals from the body of a patient for field monitoring , hospital monitoring , transport monitoring , home , remote monitoring .