Patent Publication Number: US-7715909-B2

Title: SCG point pick process device and method

Description:
CROSS REFERENCE TO RELATED CASES 
   The present application incorporates by reference and claims the benefit of U.S. Provisional Application 60/687,258 filed Jun. 3, 2005 and entitled SCG Point Pick Process and Method. 

   BACKGROUND OF THE INVENTION 
   Seismocardiographic (SCG) devices and methods are known in the art. In general these devices use an accelerometer to monitor the patient&#39;s heart. In use, an accelerometer is placed on the surface of the patient to detect compression waves originating in the patient&#39;s heart. The compression waves received by the accelerometer are digitized and analyzed with a computer. These SCG devices may be used for cardiac monitoring and diagnostic purposes. In some instances the SCG is used as a replacement for electrocardiographic monitoring of heart rate. In the present invention the system is used to find time intervals between mitral valve opening (MO) and mitral valve closure (MC) times, as well as the opening time (AO) and closing times (AC) for the aortic valve. The time intervals may be used to compute classic measures of cardiac performance including the isovolumic contraction time and the left ventricular ejection time (LVET). At the present time such measures are made with echocardiography. 
   SUMMARY OF THE INVENTION 
   The purpose of the point picking process is to determine the aortic and mitral valve timing. A measure for AO, AC and MO, MC timing is sought so that time interval measurements may be made. 
   In the present system, several accelerometers are used, preferably three, in a several locations to accentuate the reception of different characteristics of the cardiac waveform. It is preferred, for example, to use an acceleration sensor on the xyphoid process of the patient on the midline of the sternum as well as another accelerometer sensor at approximately the fourth intercostal space on the rib cage. This latter location places a sensor over the apex of the heart. In addition it is desirable to place a third sensor on the carotid artery on the patient&#39;s neck preferably above the bifurcation point where the common carotid divides into the external carotid and the internal carotid. 
   In operation, the SCG waveforms of the heart will usually be collected along with a conventional electrocardiographic (ECG) tracing. Certain mechanical events are “picked out” based upon a set of rules described in detail below. In one embodiment the ECG is an integral requirement of the point pick process since it provides a fiducial reference to permit averaging of the SCG waveforms. In an alternate embodiment the SCG is evaluated for cardiac events without reference to the ECG. Either the SCG data is used in “w” form or it may be averaged using the carotid evidence of AO or AC as fiducial points for SCG averaging. This “SCG only” embodiment eliminates the need for a simultaneous ECG for SCG interpretation and may be particularly desirable where ECG recoding is difficult for example in a magnetic resonance imaging magnet. 

   
     BRIEF DESCRIPTION OF THE DRAWINGS 
     Throughout the various figures identical reference numeral indicate identical structure, wherein; 
       FIG. 1  is a schematic diagram of the physical system coupled to a patient; 
       FIG. 2  is a data sequence of simultaneously recorded waveforms from a patient in normal sinus rhythm (NSR) presented in several panels where; 
       FIG. 2A  is a surface ECG tracing; 
       FIG. 2B  is an SCG tracing a xyphoid sensor on the rib cage; 
       FIG. 2C  is an SCG tracing from an apical sensor on the rib cage; 
       FIG. 2D  is an SCG tracing from a carotid sensor on the neck over the common carotid at about the bifurcation; 
       FIG. 3  is data from a patient in normal sinus rhythm (NSR) in two panels where; 
       FIG. 3A  is an event analysis presentation for a mechanical cardiac events of a patient&#39;s heart in NSR; 
       FIG. 3B  is a tracing showing two SCG wavelets taken from a patient in NSR; 
       FIG. 4  is data from a carotid sensor on a patient in NSR in two panels where; 
       FIG. 4A  is an event analysis presentation for mechanical cardiac events of a patient&#39;s heart in NSR; 
       FIG. 4B  is single carotid tracing of a patients heart in NSR; 
       FIG. 5  is data from a patient in an atrial paced rhythm (AAI) in several panels where; 
       FIG. 5A  is a surface ECG tracing; 
       FIG. 5B  is an SCG tracing from a xyphoid sensor on the rib cage; 
       FIG. 5C  is an SCG tracing from an apical sensor on the rib cage; 
       FIG. 5D  is an SCG tracing from a carotid sensor on the neck over the common carotid; 
       FIG. 6  is data from a patient in a ventricular paced rhythm (VVI) in several panels where; 
       FIG. 6A  is a surface ECG tracing; 
       FIG. 6B  is an SCG tracing from a xyphoid sensor on the rib cage; 
       FIG. 6C  is an SCG tracing from an apical sensor on the rib cage; 
       FIG. 6D  is an SCG tracing from a carotid sensor on the neck over the common carotid; 
   

   DETAILED DESCRIPTION OF AN ILLUSTRATIVE EMBODIMENT 
   Overview 
   The objective of the method and device is to extract the “time” that certain cardiac events occur during the heart rhythm of a patient. In the heart a single heart contraction pumps blood and the sequence of mechanical events proceeds from mitral valve closure (MC) to aortic valve opening (AO). Next the aortic valve closes (AC) followed by mitral valve opening (MO). This sequence of cardiac valve actuation events results in the ejection of blood in to the aorta and the lungs. The opening and closing of valves give rise to the compression waves interpreted by the invention. These same mechanical events are caused by the contraction of the muscles in the heart which gives rise to an independent electrographic waveform (ECG) measured on the surface of the patient&#39;s body. Knowledge of the time intervals between these mechanical cardiac events and the electrographic counterpart events has substantial diagnostic value and any of several measures of cardiac performance may be computed from the time intervals. 
   Hardware Implementation 
   In the illustrative embodiment of the system, multiple channels of accelerometry are used and in the current design each channel is identical in terms of electrical performance. It is expected that certain optimization may be used to tailor the channels to their respective signals within the scope of the invention. The preferred locations are identified in the description but alternates sites may be equivalent in terms of function. 
   In use the several sensors are placed on the patient  16  to pick up different cardiac characteristics of a simultaneously recorded signals. That is, all the data is time stamped or aligned in time so that the point pick measurement process may move from one waveform to the other. The waveform figures are displayed as panels to show this feature. As shown in  FIG. 1 , it is preferred, for example, to use both an acceleration sensor on the xyphoid process  10  of the patient on the midline of the sternum as well as at approximately the fourth intercostals space on the rib cage corresponding to the apex  12  of the heart. In addition a third sensor  14  should be placed on the carotid artery preferably above the bifurcation point where the common carotid divides. Multiple electrode typified by electrode  18  are placed in a conventional “lead  12 ” pattern on the patient to pick up and record the ECG. 
   The accelerometers are identical and they may be piezoelectric devices with a frequency response for DC to 20,000 HZ generating approximately 1000 mv/G. The high impedance sensors generate signals that are delivered to the interface  20  via shielded cables. Commercially available sensor may weigh as little as 20 grams which facilitates their placement on the body. The signal processing for the accelerometer signals of the three sensors is similar and the signal processing and analog to digital conversion occurs in a companion interface  20 . The invention has been implemented with the commonly available “Lab View” hardware platform manufactured by National Instruments Co. The SCG accelerometer signals are buffered and bandpass amplified with a flat filter having corner frequencies of approximately 0.3 Hz and 170 Hz. After filtration the signals are digitized with an A to D converter with a sampling rate of about 1K sps, and presented to the computer  21  which uses software to analyze the signals from the ECG and the SCG accelerometers. A user selectable interpretation recording is made of between about 3 to 15 seconds of data covering several beats. A moving 3-15 second window of data is recorded and is available for processing. Longer and shorter windows are operable. 
   Experimentation suggests that the system of the invention is quite tolerant of the signal processing methodology. Since implementation is readily carried out with “off the shelf” hardware the hardware implementation is not described in more detail. 
   SCG Point Pick Process 
   In most of the examples and during cardiac testing, the various SCG waveforms of the heart are collected along with a simultaneous conventional ECG tracing. The recordings are all taken simultaneously and the time relationship between the various waveforms or data sets is preserved. The SCG waveform is considered and processed as “wavelets” each wavelet is intended to encompass the time interval of a single heartbeat. Wavelets may be averaged or used individually (raw). A fiducial point for averaging SCG waveforms may be used to expand or contract the wavelet waveform to permit simple averaging of amplitude values. This fiducial point may be taken from the ECG channel where the electrocardiographic “R-wave” can be extracted from the ECG channel and used to scale and align the SCG waveforms. As an alternative the carotid SCG channel may be taken as indicative for certain events such as AO and AC. These mechanical events can be used scale and then average the SCG data. In general the averaging process expands or compresses the wavelets until they exhibit the same R-R interval. The averaging process is best achieved by manipulating the data by scaling the data so that it exhibits the same R-R interval and then making an arithmetic average of contiguous data sets at the same apparent heart rate. This forced rate ensures that mechanical motion events that are averaged at the same “time” in the cardiac cycle. It appears that the best performance is achieved when approximately 3-5 beats of data for each channel are taken and the data in each channel is averaged. 
   SCG Point Pick Process Schema Table 
   This table represents the software process carried out by the computer  21  described in prose rather than a flow chart. This process is used to create the event analysis presentation seen as panel  FIG. 3A  and  FIG. 4A , which can be viewed on a computer display screen. Wavelet or waveform averaging using the simultaneous ECG recording is described in more details in U.S. Pat. Nos. 4,989,611 and 5,159,932. The process described in the patent is similar channel for channel to the present implementation. 
   1. Point Pick Process with Simultaneous ECG 
   A multiple channel ECG is collected from the patient to help with the evaluation of the SCG data. In general a lead “III” ECG waveform is sufficient and in this ECG channel there should be very distinct QRS complexes. Only a short interval of data needs to be collected with the present system. It has been determined that approximately 3 to 15 seconds of data is sufficient to carry out the invention. The electrocardiogram (ECG) is analyzed and conventional algorithms are used to determine the QRS onset as well as the peak of the R-wave. In  FIG. 2A  the magnitude and rise time of the waveform has resulted in the detection and declaration of event  100  and  102  as the “R-wave” in the respective complexes and the companion waveforms of  FIG. 2 . Rhythm analysis is provided to remove abnormal beats and in the instance of patients having a pacemaker, the pacemaker spike is used as the onset of the R-wave an example of this is seen in  FIG. 6A  where events  104  and event  106  represent the declaration of the onset of the “R-wave” in the waveforms of  FIG. 6 . In the ECG channel the system calculates the average standard deviation in medium R to R intervals of the heart to calculate the heart rate. The simultaneously recorded SCG data is evaluated by establishing an analysis window whose size is determined by the P to R interval and the R to R interval. The analysis window is the P to R to R interval of the average heartbeat. This window is applied to the ECG data as well as the simultaneously recorded SCG xyphoid, SCG apex and SCG carotid data. Once the R peaks are aligned a set of wavelets is created for each of the ECG channels. It is usually required to adjust the DC offset for the wavelet and every wavelet is integrated into a set of velocity wavelets. The velocity wavelets are used as a baseline and they are adjusted to remove noise. Next each velocity wavelet is integrated and a set of displacement wavelets are created. The displacement wavelets are baseline adjusted and any time dependant ramping behavior is removed as well. 
     FIG. 3B  shows two overlapping SCG waveforms from the carotid sensor on a patient in NSR. Wavelet  120  and wavelet  122  differ in detail even when aligned to the same “R-wave” as a fiducial reference. It has been found that averaging 3-5 beats greatly reduces the scatter in the event times shown in  FIG. 3A . Although the wavelet disparity seen in  FIG. 3B  can be improved by averaging the beats around the electrographic R-wave another approach is available as well. 
   The distinct inflections seen as  124  and peak  126  seen in  FIG. 4B  correspond to AO and AC mechanical events. These peaks are very distinct in the carotid waveforms presented in  FIG. 4 . In this instance the points may be selected using an “R-wave” like algorithm that looks at rise time dV/dT and Maximum value to declare the AO and AC events. One may use the AO and AC event to carry out averaging in the remaining SCG channels or they may be applied directly to the raw data in the companion waveforms. In this instance the remaining SCG point pick processes process maybe run in essentially real time without waveform averaging. With the SCG wavelets prepared the point picking process is applied. The process described in the patent is similar channel for channel to the present implementation. 
   The point picking process begins with the identification of aortic opening AO and proceeds sequentially to detect the MC, AC and MO events. With reference to the figures the process occurs according to the following rules and procedures. 
   AO Process 
   Using the Average Carotid Acceleration Wavelet 
   
       
       Process  400  on  FIG. 2D  corresponds to: 
     
  
   Identify the largest positive peak within 220 msec of the R peak see reference numeral  402 ;
         Mark this point as AO carotid, see reference numeral  404 ;   If no positive peak is found, start search again at R peak and search ahead for largest negative peak. When found, search back for 1 st  negative knee (concave down), mark this point AO carotid.
 
Using the Average Xyphoid Acceleration Wavelet
       Process  450  on  FIG. 2B  corresponds to:
       Starting at AO carotid time, search back 60 msec for largest positive peak illustrated by arrows  451  and  452  which delimit the short time interval.   Mark this point as AO xyphoid seen at reference numeral  454 .
 
Using the Average Apex Acceleration Wavelet
   
       Process  460  on  FIG. 2C  corresponds to:
       Starting at AO carotid time, search back 60 msec for largest negative peak   Mark this point as AO apex as shown by reference numeral  462 .   
       If _AO xyphoid−AO apex — &lt;=10 msec;   

   Select AO apex as aortic valve opening AO.
     If (AO xyphoid−AO apex)&gt;=0 and _AO xyphoid−AO apex — &gt;10 msec;   

   Select AO xyphoid as pulmonic valve opening PO. 
   Select AO apex as aortic valve opening AO.
     If (AO xyphoid−AO apex)&lt;0 and _AO xyphoid−AO apex — &gt;10 msec;   

   Select AO xyphoid as aortic opening AO. 
   MC Process 
   Using the Average Xyphoid Acceleration Wavelet 
   
       
       Process  420  on  FIG. 2B  corresponds to:
       Start search at AO xyphoid time−10 msec and search back 85 msec for the largest negative peak, see reference numeral  424 .   Continue search back from this negative peak 30 msecs for 1 st  negative knee.   Mark this point MC xyphoid see reference numeral  422 .   If negative knee not found restart search at negative peak and search back for 45 msec to find 1 st  positive peak.   Mark this point MC xyphoid
 
Using the Average Apex Acceleration Wavelet
   
     
       Process  430  on  FIG. 2C  corresponds to:
       Start search at AO apex time−10 msec and search back 100 msec for the largest negative peak, see reference numeral  432 .   Continue search back from this negative peak 30 msecs for 1 st  negative knee.   Mark this point MC apex as indicated by reference numeral  432 .   If negative knee not found restart search at negative peak back for 45 msec to find 1 st  positive peak.   Mark this point MC apex   
     
       If _MC xyphoid−MC apex — &lt;=10 msec; 
     
  
   Select earlier of MC apex or MC xyphoid as mitral valve closure MC.
     If _MC xyphoid−MC apex — &gt;10 msec and (MC xyphoid−MC apex)&gt;0;   

   Select MC xyphoid as tricuspid valve closure TC. 
   Select MC apex as mitral valve closure MC.
     If (MC xyphoid−MC apex)&lt;0;   

   Select MC apex as mitral valve closure MC. 
   AC Process 
   
       
       Process  440  on  FIG. 2D  corresponds to:
 
Using the Average Carotid Acceleration Wavelet
 
       Process  440  on  FIG. 2D  corresponds to:
       Starting at AO carotid time+200 msec, search ahead for 500 msec for largest positive peak see reference numeral  442 .   Mark this point as AC carotid see reference numeral  444 .
 
Using the Average Xyphoid Acceleration Wavelet
   
     
       Process  460  on  FIG. 2B  corresponds to:
       Start search AC carotid time−15 msec and search back 50 msec for the 1st negative peak   Continue search back from this negative peak 20 msecs for 1 st  negative knee.   Mark this point AC xyphoid as shown by reference numeral  462 .   If negative knee not found restart search at negative peak and search back for 20 msec to find 1 st  positive peak.   Mark this point AC xyphoid
 
Using the Average Apex Acceleration Wavelet
   
     
       Process  470  on  FIG. 2C  corresponds to:
       Start search at AC carotid time−15 msec and search back 50 msec for the 1st positive peak,   Continue search back from this positive peak 20 msecs for 1 st  positive knee.   Mark this point AC apex   If positive knee not found restart search at positive peak and search back for 30 msec to find zero crossing.   Mark this point AC apex   
     
       If _AC xyphoid−AC apex — &lt;=10 msec; 
     
  
   Select earlier of AC apex or AC xyphoid as aortic valve closure AC.
     If _AC xyphoid−AC apex — &gt;10 msec and (AC apex−AC xyphoid)&gt;0;   

   Select AC xyphoid as tricuspid valve closure TC. 
   Select AC apex as aortic valve closure AC.
     If _AC xyphoid−AC apex — &gt;10 msec and (AC apex−AC xyphoid)&lt;0;   

   Select AC apex as aortic valve closure AC. 
   MO Process 
   Using the Average Xyphoid Velocity Wavelet 
   
       
       Process  480  on  FIG. 2B  corresponds to:
       Start search at AC carotid time+50 msec and search ahead 150 msec for the largest negative peak,   Go to corresponding time point on the average xyphoid acceleration wavelet and search back 75 msec for the 1 st  positive knee,   Mark this point MO xyphoid as indicated by reference numeral  482 .
 
Using the Average Apex Velocity Wavelet
   
     
       Process  490  on  FIG. 2C  corresponds to:
       Start search at AC carotid time+50 msec and search ahead 150 msec for the largest negative peak see reference numeral  492 ,   Go to corresponding time point on the average apex acceleration wavelet and search back 75 msec for the 1 st  positive knee,   Mark this point MO apex see reference numeral  494 ,   Select the later of MO apex and MO xyphoid as mitral valve opening MO.
 
II. Point Pick Process without ECG
   
     
     
  
   Point Pick process using AO peak identified in the SCG carotid trace for a fiducial point. The process of picking the AO peak in the carotid trace is essentially the same as QRS detector; setting threshold levels for noise and signal, setting refractory times for AO peak recurrence, and determining AO-AO interval. The AO peak will be used as fiducial marker for wave alignment and the wavelet window is equal to 0.35*avg AO-AO interval+AO-AO interval. 
   AO Process 
   Using the Average Xyphoid Acceleration Wavelet 
   
       
       
         
           Starting at AO carotid time, search back 60 msec for largest positive peak. 
           Mark this point as AO xyphoid
 
Using the Average Apex Acceleration Wavelet
 
           Starting at AO carotid time, search back 60 msec for largest negative peak. 
           Mark this point as AO apex 
         
       
       If _AO xyphoid−AO apex — &lt;=10 msec; 
     
  
   Select AO apex as aortic valve opening AO.
     If (AO xyphoid−AO apex)&gt;=0 and _AO xyphoid−AO apex — &gt;10 msec;   

   Select AO xyphoid as pulmonic valve opening PO. 
   Select AO apex as aortic valve opening AO.
     If (AO xyphoid−AO apex)&lt;0 and _AO xyphoid−AO apex — &gt;10 msec;   

   Select AO xyphoid as aortic opening AO. 
   MC Process 
   Using the Average Xyphoid Acceleration Wavelet 
   
       
       
         
           Start search at AO xyphoid time−10 msec and search back 85 msec for the largest negative peak 
           Continue search back from this negative peak 30 msecs for 1 st  negative knee. 
           Mark this point MC xyphoid 
           If negative knee not found restart search at negative peak and search back for 45 msec to find 1 st  positive peak. 
           Mark this point MC xyphoid
 
Using the Average Apex Acceleration Wavelet
 
           Start search at AO apex time−10 msec and search back 100 msec for the largest negative peak 
           Continue search back from this negative peak 30 msecs for 1 st  negative knee. 
           Mark this point MC apex 
           If negative knee not found restart search at negative peak back for 45 msec to find 1 st  positive peak. 
           Mark this point MC apex 
         
       
       If _MC xyphoid−MC apex — &lt;=10 msec; 
     
  
   Select earlier of MC apex or MC xyphoid as mitral valve closure MC.
     If _MC xyphoid−MC apex — &gt;10 msec and (MC xyphoid−MC apex)&gt;0;   

   Select MC xyphoid as tricuspid valve closure TC. 
   Select MC apex as mitral valve closure MC.
     If (MC xyphoid−MC apex)&lt;0;   

   Select MC apex as mitral valve closure MC. 
   AC Process 
   Using the Average Carotid Acceleration Wavelet 
   
       
       
         
           Starting at AO carotid time+200 msec, search ahead for 500 msec for largest positive peak. 
           Mark this point as AC carotid.
 
Using the Average Xyphoid Acceleration Wavelet
 
           Start search AC carotid time−15 msec and search back 50 msec for the 1st negative peak 
           Continue search back from this negative peak 20 msecs for 1 st  negative knee. 
           Mark this point AC xyphoid 
           If negative knee not found restart search at negative peak and search back for 20 msec to find 1 st  positive peak. 
           Mark this point AC xyphoid
 
Using the Average Apex Acceleration Wavelet
 
           Start search at AC carotid time−15 msec and search back 50 msec for the 1st positive peak 
           Continue search back from this positive peak 20 msecs for 1 st  positive knee. 
           Mark this point AC apex 
           If positive knee not found restart search at positive peak and search back for 30 msec to find zero crossing. 
           Mark this point AC apex 
         
       
       If _AC xyphoid−AC apex — &lt;=10 msec; 
     
  
   Select earlier of AC apex or AC xyphoid as aortic valve closure AC.
     If _AC xyphoid−AC apex — &gt;10 msec and (AC apex−AC xyphoid)&gt;0;   

   Select AC xyphoid as tricuspid valve closure TC. 
   Select AC apex as aortic valve closure AC.
     If _AC xyphoid−AC apex — &gt;10 msec and (AC apex−AC xyphoid)&lt;0;   

   Select AC apex as aortic valve closure AC. 
   MO Process 
   Using the Average Xyphoid Velocity Wavelet 
   
       
       
         
           Start search at AC carotid time+50 msec and search ahead 150 msec for the largest negative peak 
           Go to corresponding time point on the average xyphoid acceleration wavelet and search back 75 msec for the 1 st  positive knee 
           Mark this point MO xyphoid
 
Using the Average Apex Velocity Wavelet
 
           Start search at AC carotid time+50 msec and search ahead 150 msec for the largest negative peak 
           Go to corresponding time point on the average apex acceleration wavelet and search back 75 msec for the 1 st  positive knee 
           Mark this point MO apex 
           Select the later of MO apex and MO xyphoid as mitral valve opening MO
 
It should be apparent that many alternative modifications can be made to the invention without departing from the scope of the appended claims.