**6.1 Waveform of the FBG sensor signal**

In this section, the blood pressure is calculated from the waveform of the FBG sensor signal. As shown in Section 3, the FBG sensor signal is measured representing the pressure of the blood flow that causes a change in the diameter of the blood vessel. Pulsation is a distortion that causes an arterial distortion on the skin surface. Therefore, information on blood pressure is considered to be present in the FBG sensor signal from which a distortion is measured.

A signal measured with a general photoelectric pulse wave sensor is a volume pulse wave signal indicating the volume of blood. A signal obtained by second derivative of the volume pulse wave signal is an acceleration plethysmogram. The basic shape of acceleration plethysmogram includes five peaks [18]. The A-wave to the E-wave are called initial systolic positive wave, initial contraction negative wave, mid-systole re-elevation wave, post-contraction descent wave, and expansion initial positive wave, respectively. Therefore, an acceleration pulse wave contains information on systole and diastole of the heart. The first derivative signal of the

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*Vital Sign Measurement Using FBG Sensor for New Wearable Sensor Development*

**6.2 Calculation method of blood pressure from the FBG sensor signal**

When blood pressure was calculated from FBG sensor signal, PLS regression analysis, which is a widely known multivariate analysis among others, was used. The PLS regression analysis can construct calibration curves from the explanatory and objective variables. At this time, it is a feature to construct a calibration curve on the premise that an explanatory variable and an objective variable contain errors. The explanatory variable is the FBG sensor signal waveform, and the objective variable is the blood pressure measured simultaneously by the electronic sphygmomanometer. The FBG sensor signal is processed through the following steps [19].

1.The FBG sensor signal is processed with a band pass filter of 0.5–5 Hz.

3.The signal is divided for each detected peak.

rate fluctuations caused by respiratory sinus arrhythmia.

**6.3 Experimental result of calculating the blood pressure**

4.The divided signals are averaged.

2.The 'A' peak ('A' wave) is detected from the signal waveform of the band pass

5.At the vertical axis of the averaged signal, the first point (peak of 'A' wave) is normalized to "1", and the lowest point (peak of 'B' wave) is set to "0".

6.The horizontal axis of all FBG sensor signal waveforms processed up to the 5th term is cut out in the shortest time, and the length of the horizontal axis is unified.

The step 1 of the signal processing a range for covering a signal with a pulse rate of 30–300 times/min. In step 4 of the signal processing, considering that the measurement time of the electronic sphygmomanometer is ~30 s, the average is calculated for the pulse wave signals measured within that time. The step 5 of signal processing is to cancel the vertical axis fluctuations caused by pressure while installing the FBG sensor in humans. The step 6 of signal processing is to cancel the pulse

The FBG sensor signal processed through the aforementioned signal processing steps is used as an explanatory variable, the blood pressure value of the electronic sphygmomanometer measured simultaneously is used as a target variable, and a calibration curve is constructed by PLS regression analysis. The newly measured FBG sensor signal is substituted into this calibration curve to calculate the blood pressure.

This experiment was performed on three subjects. A schematic of the experimental blood pressure measurement is shown in **Figure 9** [19]. The posture of the subject was supine, and the FBG sensor was installed at the pulsation point of the radial artery of the right wrist. The reference blood pressure value (objective

FBG sensor is similar to the acceleration pulse wave in shape [13]. Since an FBG sensor signal indicates the displacement of the Bragg wavelength due to strain, time change of the volume pulse wave is measured. Therefore, the first derivative signal of the FBG sensor is similar to the second derivative signal of the volume pulse wave signal. Furthermore, since the first derivative waveform of an FBG sensor signal includes information on the systole and diastole of the heart, the blood pressure can

*DOI: http://dx.doi.org/10.5772/intechopen.84186*

be calculated from this waveform.

filter.

*Vital Sign Measurement Using FBG Sensor for New Wearable Sensor Development DOI: http://dx.doi.org/10.5772/intechopen.84186*

FBG sensor is similar to the acceleration pulse wave in shape [13]. Since an FBG sensor signal indicates the displacement of the Bragg wavelength due to strain, time change of the volume pulse wave is measured. Therefore, the first derivative signal of the FBG sensor is similar to the second derivative signal of the volume pulse wave signal. Furthermore, since the first derivative waveform of an FBG sensor signal includes information on the systole and diastole of the heart, the blood pressure can be calculated from this waveform.
