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Storing Data Points in Embedded Systems Efficiently and Reliably

kas.lewis

I am looking for an efficient way to store data points in an embedded system. More precisely, as part of the Sudden Impact Challenge, there is a possible need to sample the heart rhythm and store that data for analysis. The simplest method I can think of would be to make a very large 2D array to put those samples in but doing this sampling at 500Sa/s (12 bit ADC) would consume any available memory after just a few samples.

 

If there are any suggestions or proven techniques I would be grateful to hear them.

 

Thanks

Kas

  • 0

    HI Kas,

     

    I would set up some limits to cut down the amount of data you need.

    Say setup a range of normal heart rate and then use a binary of 0 = within range and 1 if it exceeds range.

    You can do the same with under value.

    If you have different levels of impact detection, you can use a simple binary scale, possibly log scale, and just report changes.

     

    I have found that anything you can do to reduce storage and transmission information, the more responsive you system will be to events of interest.  Ie, when you exceed your normal limits.

     

    DAB

  • 0 in reply to DAB

    Hello DAB,

     

    Thank you for the information. I was however looking to store or at least use the full heartbeat (the complete PQRST complex) to look for abnormalities that may lead to a heart attack or other heart related issues during strenuous activity. For just the heart rate would only need the time between R peaks but I am hoping to accomplish a bit more in this project if possible.

     

    Thanks

    Kas

  • 0 in reply to kas.lewis
    FeatureDescriptionPathologyDuration
    P waveThe p-wave represents depolarization of the atria. Atrial depolarization spreads from the SA node towards the AV node, and from the right atrium to the left atrium.The p-wave is typically upright in most leads except for aVR; an unusual p-wave axis (inverted in other leads) can indicate an ectopic atrial pacemaker. If the p wave is of unusually long duration, it may represent atrial enlargement. Typically a large right atrium gives a tall, peaked p-wave while a large left atrium gives a two-humped bifid p-wave.<80 ms
    PR intervalThe PR interval is measured from the beginning of the P wave to the beginning of the QRS complex. This interval reflects the time the electrical impulse takes to travel from the sinus node through the AV node.A PR interval shorter than 120 ms suggests that the electrical impulse is bypassing the AV node, as in Wolf-Parkinson-White syndrome. A PR interval consistently longer than 200 ms diagnoses first degree atrioventricular block. The PR segment (the portion of the tracing after the p-wave and before the QRS complex) is typically completely flat, but may be depressed in pericarditis.120 to 200 ms
    QRS complexThe QRS complex represents the rapid depolarization of the right and left ventricles. The ventricles have a large muscle mass compared to the atria, so the QRS complex usually has a much larger amplitude than the P-wave.If the QRS complex is wide (longer than 120 ms) it suggests disruption of the heart's conduction system, such as in LBBB, RBBB, or ventricular rhythms such as ventricular tachycardia. Metabolic issues such as severe hyperkalemia, or TCA overdose can also widen the QRS complex. An unusually tall QRS complex may represent left ventricular hypertrophy while a very low-amplitude QRS complex may represent a pericardial effusion or infiltrative myocardial disease.80 to 100 ms
    J-pointThe J-point is the point at which the QRS complex finishes and the ST segment begins.The J point may be elevated as a normal variant. The appearance of a separate J wave or Osborn wave at the J point is pathognomonic of hypothermia or hypercalcemia.[12]
    ST segmentThe ST segment connects the QRS complex and the T wave; it represents the period when the ventricles are depolarized.It is usually isoelectric, but may be depressed or elevated with myocardial infarction or ischemia. ST depression can also be caused by LVH or digoxin. ST elevation can also be caused by pericarditis, Brugada syndrome, or can be a normal variant (J-point elevation).
    T waveThe T wave represents the repolarization of the ventricles. It is generally upright in all leads except aVR and lead V1.Inverted T waves can be a sign of myocardial ischemia, LVH, high intracranial pressure, or metabolic abnormalities. Peaked T waves can be a sign of hyperkalemia or very early myocardial infarction.160 ms
    Corrected QT intervalThe QT interval is measured from the beginning of the QRS complex to the end of the T wave. Acceptable ranges vary with heart rate, so it must be corrected by dividing by the square root of the RR interval.A prolonged QTc interval is a risk factor for ventricular tachyarrhythmias and sudden death. Long QT can arise as a genetic syndrome, or as a side effect of certain medications. An unusually short QTc can be seen in severe hypercalcemia.<440 ms
    U waveThe U wave is hypothesized to be caused by the repolarization of the interventricular septum. It normally has a low amplitude, and even more often is completely absent.If the U wave is very prominent, suspect hypokalemia, hypercalcemia or hyperthyroidism.[13]

     

    Based on the table above, try to test and store any nodes outside the indicated ranges. Add information to show which beat it occurred and timestamps and you may have less data, but only important ones. Be careful too much analysis may not be good for monitoring...

    P>80ns/PR not 120-200ms/etc.

     

    Clem

  • 0

    Hi Kas,

     

    One option could be to store 1-in-100 full waveforms. For example, if the heart is beating at 100bpm, then perhaps just one fully captured beat (at the 500 samples/sec you mention) could be sufficient to identify anomalies within a minute. For the rest of the time, just basic information such as pulse rate could be captured. This would reduce the storage and data transmission requirements to 1/100th.

    Another option could be to store deep data (e.g. on a multi-GB microSD card), but only serve up data once per (say) minute, and allow the remote system or operator to selectively download more data as needed, dynamically.

    There are probably smart compression schemes too but could be complicated math and need a lot of local processing.

    Hard to say what scheme is best without knowing from a medical expert I guess! For example perhaps 1 minute may be too long, but a medical expert may think 10 seconds is fine.

     

    But Clem's idea of local processing is smart. Nowadays there is maybe enough low-cost (and low power) computing resources to do this.