Mechanical Cardiography using a Geophone Mechanical Cardiography using a Geophone

Randall D. Peters
Physics Department
Mercer University
Macon, Georgia 31207

(Copyright 26 January 2005)

Abstract

It is shown that a commercial geophone of the type used for oil prospecting may be useful for heart diagnostics, when connected to a personal computer through a user-friendly though powerful analog to digital converter with associated processing software.

1  Background

Various studies by the author have shown the importance of synergy in three key elements of an experiment; these are (i) the sensor, (ii) the interface between sensor and computer, and (iii) the analysis software. Poor performance in any one of these three elements seriously degrades one's ability to understand the experiment.

1.1  The personal computer

The inexpensive pc has dramatically improved analysis capabilities in general. Before its existence there were already some very good sensors. Unfortunately, means for coupling these sensors to the computer to yield a user-friendly while still powerful package have been limited. The Dataq company (www.dataq.com) has produced some inexpensive analog to digitial converters, with associated software, that represent a significant improvement in the interface/processor state of the art. The connection of the converter to the computer via the USB port is straightforward. And the Dataq analysis software, which operates on the *.wdq files generated during data acquisition-is the most impressive set of algorithms used by this author. By means of windows icons or hotkeys, one can quickly switch between display of a time record and its associated spectrum. Moreover, the time record can be viewed in detail using the smallest time increment estabished by the sampling rate; or it can be easily compressed to view the complete record. Additional straightforward filtering possibilities include (i) low-pass, (ii) high-pass, and (iii) band-pass operations. These are accomplished by means of the FFT and its inverse.

2  Mechanical Cardiograph Experiment

An unknown commercial geophone (gift from Symmetric Research in Kirkland, WA) was connected to a Dataq DI-700 analog to digital converter. Records at the maximum sampling rate of the converter (488.28 per s) were collected on several human subjects. These were collected with the subject either (i) lying on the floor with the geophone resting vertically on the chest in the vicinity of the heart, or (ii) sitting with the geophone resting in a shirt pocket in the vicinity of the heart.

2.1  Example time record

Figure 1 is an example of a fully-compressed time record in which the subject was prone.
example.gif

Figure 1 Example of a mechanical cardiogram. The heartbeat is evident in the tallest, sharp `pulses' of this compressed record.

An expanded time record is shown in Fig. 2, where various of the higher frequency components registered by the geophone are visible.
example2.gif

Figure 2. Expanded portion of Fig. 1, having the same units on the vertical axis.

2.2  Example spectrum

Shown in Fig. 3 is the spectrum that results from taking a Hanning-windowed 1024 pt FFT on a portion of the time record used to generate figures 1 and 2.
example3.gif

Figure 3. Spectrum associated with record that generated the figures above. Input averaging of 3 was used.

In Fig. 3 there is clear evidence of mode mixing (due to nonlinearity) between the heartbeat at 1.43 Hz and oscillations of the chest cavity responsible for the largest peak in the comb structure at 10.65 Hz (lines marked with the red arrows).

Various lines of the comb structure were found to persist for rather long times, as evidenced by Fig. 4.
comp-sp.gif

Figure 4. Composite of six overlayed spectra, taken at equally-spaced-in-time increments of a record whose total length was 59 s.

For the data of Fig. 4 the same subject was used, except now standing with the geophone in a chest pocket, vertically oriented. The highest peak in this case is at 10.01 Hz, slightly lower than the previous case. This is probably consistent with compression of the chest cavity between the normal force of the floor and gravity when the subject is prone.

2.3  Comparison of two subjects

An example of the usefulness of high-pass filtering is shown in Fig. 5, where records of duration 6.25 s have been shown for each of two male subjects.
subj-comp.gif

Figure 5. Spectra showing the difference between two male subjects. Subject B has a known heart murmur.

In each of the top raw traces, more than eight heartbeats are visible (more clearly for subject A). Frequencies below 30 Hz were removed from the spectrum to generate the high-pass filtered traces shown. They begin and end with zero-amplitude because of the hanning window employed by the FFT algorithm.

It is seen that the filtered data of subject B is significantly more noisy than that of subject A, presumed to be the result of the known (longtime) heart murmur of subject B. Note also in the case of subject A that there are clearly two-events per heartbeat in the higher frequency components of this mechanical cardiograph. It is assumed that these are associated with mitral and tricuspid valve function. In the case of subject B, the murmur is the result of mitral valve prolapse.

3  Valsalva maneuver

Shown in Fig. 6 (left side) is a spectrum taken with subject A during a Valsalva maneuver. A reference spectrum similar to that of fig. 3 is shown for comparison.
val-cmp.gif

Figure 6. Illustration of spectral change during a Valsalva maneuver.

It is common knowledge from phonocardiography that this maneuver introduces high frequency sounds, which are also implied by the hump in the left figure, which peaks in the neighborhood of 44 Hz.

4  Difference from phonocardiography

In phonocardiography (electronic stethoscope) one listens to sounds transmitted through the chest wall. As a seismic unit, the geophone responds to acceleration of the chest. Thus one expects that chest resonance would be more obvious in the geophone data. Mode mixing between the heart/chest oscillators is in turn expected and the trial cases bear this out.

5  Conclusions

These preliminary findings suggest that the methods described could be of value for cardiac diagnostics. As with the historical development of electrocardiography, empiricism based on clinical testing will be necessary to determine any true benefits.

Acknowledgement The author gratefully acknowledges important contributions to this work from Drs. Matt Marone and Mike Russell.


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