Gas station without pumps

2014 June 1

Blood pressure monitor

I thought of a new variant on the pressure sensor lab for the circuits course: a blood pressure monitor.  I happen to have a home blood pressure monitor with a cuff and squeeze bulb that can be detached from the monitor and hooked up to the MPS2053 pressure sensor instead.  With this setup and an instrumentation amp, I can easily record the pressure in the cuff and observe the oscillations in the cuff pressure that are used for oscillometric blood pressure measurement.

Cuff pressure measurements using an MPX2053DP sensor, and instrumentation amp, and a KL25Z microcontroller board running PteroDAQ software.

Cuff pressure measurements using an MPX2053DP sensor, and instrumentation amp, and a KL25Z microcontroller board running PteroDAQ software.

The fluctuations can be observed by removing a baseline (fitting an exponential decay to the dropping pressure, for example, and the subtracting it out) or by using some sort of digital filter. I tried using a 0.3Hz–6Hz bandpass filter (4th order Bessel filter, applied using scipy.signal.filtfilt):

Oscillations corresponding to the pulse are very visible when the slow pressure decay is filtered out.  I've zoomed in on just the time of the dropping pressure, marked with lines on the previous plot.

Oscillations corresponding to the pulse are very visible when the slow pressure decay is filtered out. I’ve zoomed in on just the time of the dropping pressure, marked with lines on the previous plot.

The pulse is very easy to see (about 40.4bpm in this sample—low even for me), but figuring out the systolic and diastolic pressure from the fluctuations is a bit messy:

The oscillometric method of measuring blood pressure with an automated cuff yields valid estimates of mean pressure but questionable estimates of systolic and diastolic pressures. Existing algorithms are sensitive to differences in pulse pressure and artery stiffness. Some are closely guarded trade secrets. Accurate extraction of systolic and diastolic pressures from the envelope of cuff pressure oscillations remains an open problem in biomedical engineering.  
[Charles F Babbs, Oscillometric measurement of systolic and diastolic blood pressures validated in a physiologic mathematical model, BioMedical Engineering OnLine 2012, 11:56 doi:10.1186/1475-925X-11-56 http://www.biomedical-engineering-online.com/content/11/1/56]

One shortcut is to find the maximum amplitude of the envelope of the oscillations, and look at the pressures at fractions of the amplitude:

However, it has been shown that the pressure, Pm, at which the oscillations have the maximum amplitude, Am, is the mean arterial pressure (MAP). Empirical and theoretical work has shown that the systolic and diastolic pressures, Ps and Pd respectively, occur when the amplitudes of oscillation, As and Ad respectively, are a certain fraction of Am:

  • Ps is the pressure above Pm at which As/Am = 0.55
  • Pd is the pressure below Pm at which Ad/Am = 0.85

[Dr. Neil Townsend, Medical Electronics, Michaelmas Term, 2001, http://makezine.com/go/obpm]

I’m too lazy right now to try to come up with a good envelope follower and find the times for 55% and 85% of peak. The peak seems to be around 48.3s in this plot with magnitude of 0.336kPa and a predicted MAP of 16.28kPa (122mm Hg).  I based the MAP on low-pass filtering the signal to remove the fluctuations and make a good smooth curve for finding the systolic and diastolic pressure, once times on the envelope are picked.  Again, a 4th order Bessel filter applied with filtfilt looks good:

Low-pass filtering removes the fluctuations, so that picking two time points can give clean pressure readings for the systolic and diastolic pressure.

Low-pass filtering removes the fluctuations, so that picking two time points can give clean pressure readings for the systolic and diastolic pressure.

From the standpoint of the course, the filtering to get a good signal is probably too difficult, but students could record the cuff pressure and observe the fluctuations. They might even be able to do some crude RC filtering, though this is really an application that calls out for digital filtering.

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1 Comment »

  1. […] 60Hz noise.  I used scipy.signal.iirfilter and scipy.signal.filtfilt, pretty much as I did for looking at oscillometric blood pressure measurements.  The 60Hz noise was larger in the lab than at home (a lot more stuff plugged in), but […]

    Pingback by EKG lab not quite done | Gas station without pumps — 2014 June 3 @ 21:14 | Reply


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