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Digital Signal Processing Methods for the Evaluation of Blood Volume Pulse (BVP) Waveform Changes due to Exercise

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Digital Signal Processing Methods for the Evaluation of Blood Volume Pulse (BVP) Waveform Changes due to Exercise

 Chao Li,  Jing Zhai  and Armando Barreto

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I. Introduction

Finger photoplethysmography (PPG) is a non-invasive monitoring technique, which does not require costly equipment or specialized personnel. Traditionally, the Blood Volume Pulse (BVP) has been used to determine the heart rate [1]. However a more detailed analysis of photoplethysmographic BVP variations may indicate circulatory changes that take place in an individual due to exercise. Further research has shown that the changes in the single BVP signal through an exercise session (before exercise, immediately after exercise, and after a recovery period) can be measured, characterized, and quantified through signal processing methods [2].

 

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II. Data Gathering Protocol

The recording procedure used consisted of three measurements: A, B and C, through a total time of about 18 minutes. Ten healthy volunteers with ages between 22 and 40 participated in the recordings.

Each subject was requested to sit comfortably, resting the right arm on a table. At this point, the first photoplethysomgraphic Blood Volume Pulse record was obtained from the tip of the right index finger (Stage “A”, “Before exercise”). After recording for about 30 to 60 seconds, the subject was asked to begin performing continuous lifting of a 6.6-pound dumbbell with the left arm. At the end of 1-minute intervals, the subject was asked to switch the arm used to lift the dumbbell. This process lasted for 8 minutes. Then a second BVP measurement was taken (Stage “B”, “Immediately after exercise”). After this, the subject was asked to rest, allowing for his or her cardiovascular system to recover, for 8 more minutes. After the recovery period, one last BVP measurement was taken from the right index finger (Stage “C” or “After recovery”).

 Data Gathering Protocol:

 

 

The following three figures show the BVP waveforms recorded from one of the subjects (S3) at stages A, B and C, respectively. As we can see, in stages A and C, the dicrotic notch is very pronounced, while in stage B the Dicrotic Notch is less obvious, because of the changes in the cardiovascular system caused by the exercise. This is probably due to a combined effect of the increased cardiac output and decreased peripheral resistance associated with exercise [4]. Our objective is to find methods to derive a single numerical parameter from the BVP signal, which will reflect those cardiovascular changes.

    

                        FIG1.  BVP waveform from Subject S3 at stage A

    

                         FIG2. BVP waveform from Subject S3 at stage B  

    

                         FIG3. BVP waveform from Subject S3 at stage C 

 

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III. Data processing methods

Three approaches were tested to quantify the changes introduced in the photoplethysmographic Blood Volume Pulse waveform by exercise. 

1. Average Beat Histogram Analysis

Preliminary observation of the records obtained for the study indicated that the dicrotic notch tends to be less pronounced in the measurement taken right after the exercise (Stage B). This led us to implement a signal processing scheme that separates individual beats in the signal, aligns them according to their maxima and computes a normalized histogram for each of them. In this histogram the full amplitude range of each beat is divided into 100 bins and the number of values within each amplitude bin is found. Before the exercise session (A) and after the recovery period (C), the presence of dicrotic notch results in a large number of samples detected in the range R1: (40% - 70%) of the total amplitude of the beats, which tends to predominate over R2: (70% - 100%). On the other hand, immediately after the exercise session the Dicrotic Notch is normally less pronounced. So the ratio of the histogram accumulation for range R1 and the histogram accumulation for R2 was selected as the single index to summarize the changes in the histogram [3]. The following table indicates the ratios found for the ten subjects at the 3 different stages of the procedure, normalized to the value found in stage A:

               

A

B

C

S1

1.00

0.7294

0.9132

S2

1.00  

0.3839

0.9089

S3

1.00 

0.2013

1.0873

S4

1.00  

0.5365

1.0215

S5

1.00 

0.7838

0.7962

S6

1.00

0.8422

0.8879

S7

1.00 

0.4042

0.5712

S8

1.00 

0.9264

0.9182

 S9

1.00  

1.1282

1.3340

S10

1.00 

0.5276

0.8639

              Table I.  Histogram method results 

     

             FIG 4     Histogram method results

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  2. BVP Harmonic Composition Changes

The presence of the Dicrotic Notch in the BVP waveform is represented in the frequency domain as a significant component corresponding to the second harmonic of the fundamental BVP frequency. This second harmonic component is normally very significant in comparison with the fundamental for stages A and C (i.e., at rest or after recovery). In contrast, the second harmonic contribution is small at stage B (right after the exercise session), since the Dicrotic Notch is less well defined. To detect these changes we propose the determination of the ratio Pf2/Pf1, where Pf2 is the amplitude of the second harmonic and Pf1 is the amplitude of fundamental in the averaged periodogram of the BVP segment recorded at each stage of the procedure. The values of this ratio, normalized to the ratio measured in stage A are shown in Table II and Figure 3.              

               

A

B

C

S1

1.00

1.2965

0.9408

S2

1.00  

1.1722

0.8228

S3

1.00 

1.6172

0.9418

S4

1.00  

1.0162

1.0092

S5

1.00 

0.6991

0.8178

S6

1.00

0.9147

1.6994

S7

1.00 

1.4692

1.3159

S8

1.00 

1.1322

1.4105

 S9

1.00  

1.9591

1.7746

S10

1.00 

1.3119

0.7448

                Table II   Harmonic method result 

 

     

              FIG  5    Harmonic method results

 

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3. Dicrotic Notch depth method:

The algorithm for this approach isolates each individual BVP beat and identifies the local minimum and local maximum associated with the presence of the Dicrotic Notch. The difference between these two levels is used as the estimation of the Dicrotic Notch depth for a particular beat. The ratio of the Dicrotic Notch depth to the total amplitude of each beat is found and an average of this ratio is calculated for all the beats in the BVP segment under study. Table III and Figure 4 show the results for the 10 subjects studied, at the 3 stages of the protocol, normalized to make stage A for every subject 1.0:     

              

A

B

C

S1

1.00

0

0.0984

S2

1.00  

0.0550

0.4990

S3

1.00 

0.0084

2.3933

S4

1.00  

0.0351

1.0879

S5

1.00 

0.0905

0.2032

S6

1.00

0.0263

0.0088

S7

1.00 

1.00

1.00

S8

1.00 

1.00

1.00

 S9

1.00  

0.0056

0.5506

S10

1.00 

0.4069

1.1176

           Table III   Dicotic notch depth method results      

     

           FIG 6    Dicrotic notch depth method results

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 IV. Discussion

Tables I – III and Figures 4- 6 show that there is significant variability in the BVP responses recorded from different individuals through the exercise protocol used in this study. Figure 5 shows that the evolution of the harmonic ratio measure was particularly different for different individuals. It is important to assess if these differences are primarily due to the methods used to evaluate the changes in BVP waveforms or whether they arise because the waveforms themselves varied in different ways through the 3 recorded stages (A, B and C) for different individuals. By visual inspection of the waveforms recorded, we realized that for eight of the ten experimental subjects the waveforms at the different stages showed the anticipated changes very clearly. However, the waveforms from two of our subjects (S8 and S9) showed much less pronounced changes.

In order to compare the efficiency of each one of the signal processing approaches used in the study to represent the changes in the BVP waveform induced by exercise, we will focus on the records obtained from the eight subjects for whom BVP waveform changes were clear, i.e. we will exclude from consideration the results from subjects S8 and S9. Looking at this subset of the data we appreciate that the Histogram method (Table I and Figure 4) provides results that are consistent with our expectations.  For this method the lessening of the Dicrotic Notch observed immediately after exercise (stage B), is represented by a reduction of the numerical index derived through the methods, with respect to the values obtained at stages A and C.  For the Histogram method this pattern is only disrupted for subjects S8, which has a lower value for stage C than for stage B and for S9 whose value for stage A is lower than for stage B. These are, however, two subjects with non-representative BVP waveforms.  

For the Dicrotic Notch Depth method, it encountered some problems when the waveform shows no notch in the downward slope, but just a lessoning of the slope. In such cases, the dicrotic notch depth is zero, which is the case for S7 and S8. The indexes for S7 and S8 for the three stages are all zero.

 For the harmonic ratio method, it indicate a lack of consistency of this measure, even within the set of eight subjects whose BVP waveforms appeared typical according to visual inspection.

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V. Conclusion

Photoplethysmographic BVP records obtained from 10 healthy volunteers confirm that the BVP waveforms change as the subject performs exercise. In our study eight of the 10 subjects studied displayed clear BVP waveform changes of the type that we had originally expected. In the remaining 2 subjects the BVP changes were subtler. The Histogram method was successful in consistently representing the BVP changes of the eight subjects whose data was typical. The results from the Harmonic Ratio method were the least consistent of the three methods considered. Overall, the Histogram seems to be the most promising for the intended application, due to the consistency of the results obtained and its relatively low computational cost.

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Reference:

[1] Lee A. L., Tahmoush A. J., and Jennings J. R., “An LED  transistor photoplethysmograph”, IEEE Transactions  on Biomedical Engineering, May 1995, pp. 248-250.

[2] Heimer M. and Barreto A., “Evaluation of physical exercise using photoplethysmography”. Proc. X Annual Conf. IEEE Engineering in Medicine and Biology Society, November 1988, pp. 1617-1618.

[3] Barreto A., Heimer M., and Garcia M., “Characterization of Photoplehtysmographic Blood Volume Pulse Waveforms for Exercise Evalution,” Proceedings 14th Southern Biomedical Engineering Conference, Shreveport, Louisiana, April, 1995, pp. 220-223.

[4] McArdle W., Katch F., and Katch V., Exercise Physiology: Energy, Nutrition and Human Performance. Lea & Febiger, Philadelphia, 1985.