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6 Applications and Methods in Biosignal Processing

RR_AVERAGE2.

RR_LOW_LIMIT = 0.92 ⋅RR_AVERAGE2

RR_HIGH_LIMIT = 1.16 ⋅RR_AVERAGE2

RR_MISSED_LIMIT = 1.66 ⋅RR_AVERAGE2 .

If no QRS complex within 166 % of the previous. Heart rate RR_AVERAGE2

the largest local maximum between the previously thresholds set so far is

chosen as the QRS complex.

If all heart rates of the last RR intervals between the thresholds RR_LOW_LIMIT

and RR_HIGH_LIMIT, the heart rate is considered to be regular, and the average

value AVERAGE_1 is equal to the average value AVERAGE_2. In this case, there is

a normal sinus rhythm.

4.

Detection of T-wave: If the time between the R peaks should be less than 360 ms

the time between the "R" spikes in an ECG must be greater than the 200 ms re-

covery time of the cardiac cells which corresponds to a heart rate greater than

167/min, it is investigated whether the maximum slope of the QRS complex found

is is smaller than half of the average slopes of the QRS complexes found so far. If

not, the "new" QRS complex found will be indentified as false and is interpreted

as a T-wave. (cf. Figure 3.16).

There are several implementations of this algorithm in Matlab, but they have often

been modified and simplified. A complete program also with backward search ac-

cording to the method published by Pan and Tompkins [58] was written in Matlab by

Hooman Sedghamiz, for example [72].¹² An application example of this programme

for determining QRS complexes is shown Figure 6.29. There, both the output signal

of the window integrator and the ECG signal after bandpass filtering are shown. The

adaptive thresholding and signal and noise level estimation procedures are also evid-

ent.

6.3.1.3 Determination of heart rate and its variability

Heart rate variabilityheart rate variability (HRV) describes the variation of the time

interval between successive heartbeats, i.e. the heart rate HFn with the definition:

HFn =

1

RRn

with

RRn = Rn −Rn−1

Rn : location of n-th R-pinch .

(6.25)

12 It can be found in ResearchGate at https://www.researchgate.net/publication/313673153/_Matlab_

Implementation_of_Pan_Tomp-kins_ECG_QRS_detector