**5. Vital sign calculation from peak in FBG sensor signal**

#### **5.1 Calculation of pulse rate**

Since the FBG sensor corresponds to heartbeat vibration, the vital sign can be calculated from the FBG sensor signal. In this section, the pulse rate is calculated from the FBG sensor signal. An FBG sensor was installed perpendicular to the direction of blood flow in the radial artery at the left wrist of the subject. In order to measure the reference pulse rate, an electronic sphygmomanometer was installed at the upper arm of the subject. The measurements using the FBG sensor and the electronic blood pressure were performed at the same time. The peak interval (PPI) of the FBG sensor signal was measured, and the pulse rate per min was calculated from Eq. (2).

$$\text{PR}\_{\text{cal}}\{\text{times}/\text{minutes}\} = \text{PPI}/\text{60} \tag{2}$$

**49**

**Figure 7.**

*Results of the PPI from the temperature data logger and the FBG sensor.*

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

the subjects A, B, and C were observed to be 0.67, 0.87, and 0.56, respectively, while the respective measurement accuracies were 2.1, 2.6, and 1.9 bpm. These results indicate that the pulse rate could be measured from the FBG sensor signal with high accuracy. Thus, it is evident that the pulse rate can be calculated if the peak of the

The pulse rate was calculated from the FBG sensor signal in Section 5.1. This section describes the measurement and calculation of respiration rate. When a person breathes, a physiological phenomenon called respiratory dynamic arrhythmia occurs, whereby the pulse rate rises during inspiration and decreases during expiration. In other words, the PPI decreases during inspiration, and increases during expiration. Therefore, when breathing is repeated, the PPI cycles up and down, and thus, the period of a breath cycle can be deduced from a PPI cycle. The respiratory

*RRcal* = *PPIcyc*/60 (3)

Experiments on breathing rate were conducted with three subjects. To measure the reference respiratory rate, a medical face mask attached with a temperature data logger (Ishikura Shoten Co., Ltd., SK-L200 THII) was used. The purpose of the face mask was to prevent the breath from leaking out. Breath temperature is known to be higher than the atmospheric temperature. At the time of inspiration, the temperature of the atmosphere is measured with a data logger. On the contrary, as the breath temperature was measured at exhalation, the value was relatively higher. Thus, a constant periodic temperature change was measured every time the subject breathes. One cycle of this temperature change was used as reference respiration time, and the reference respiratory rate was calculated from Eq. (3). The FBG sensor signal was measured under the same conditions as those for the experiment on pulse rate presented in Section 5.1. The subjects were in sitting posture at the time of measurement. The results of the temperature data logger and PPI from the FBG sensor signal are shown in **Figure 7**. It is evident that both curves are very similar to each other. In addition, it could be confirmed that the cycle varies depending on the number of breaths. The respiratory rates calculated from the temperature data logger and the FBG sensor signal are plotted against one another in **Figure 8** for the three

where, *RRcal* is calculated respiration rate, and *PPIcyc* is the cycle of PPI.

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

FBG sensor signal is detected accurately.

**5.2 Calculation of respiratory rate**

rate per min is calculated from Eq. (3),

where, *PRcal* is calculated pulse rate, and *PPI* is the peak interval. Three subjects were measured in supine position, and the measurement conditions were the same as those for the experiment on heartbeat discussed in Section 4.

A scatter diagram between the reference pulse rate and the pulse rate calculated from the FBG sensor signal is shown in **Figure 6**. The correlation coefficients for

**Figure 6.** *Result of calculated pulse rate from FBG sensor signal.*

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

the subjects A, B, and C were observed to be 0.67, 0.87, and 0.56, respectively, while the respective measurement accuracies were 2.1, 2.6, and 1.9 bpm. These results indicate that the pulse rate could be measured from the FBG sensor signal with high accuracy. Thus, it is evident that the pulse rate can be calculated if the peak of the FBG sensor signal is detected accurately.

#### **5.2 Calculation of respiratory rate**

*Fiber Optic Sensing - Principle, Measurement and Applications*

**5. Vital sign calculation from peak in FBG sensor signal**

that in turn is related to the heartbeat.

**5.1 Calculation of pulse rate**

The result of the RRI and PPI of the subject is shown in **Figure 5**, where the horizontal axis is the measurement time, and the vertical axes are the time intervals of PPI and RRI [17]. The heart rates of subject was ~51 times per min. It is evident that the RRI and PPI plots are almost identical for the subject. In other words, the FBG sensor signal corresponds to the heartbeat vibration as it represents the variation in the diameter of the arterial blood vessel caused by the flow rate (or pressure)

Since the FBG sensor corresponds to heartbeat vibration, the vital sign can be calculated from the FBG sensor signal. In this section, the pulse rate is calculated from the FBG sensor signal. An FBG sensor was installed perpendicular to the direction of blood flow in the radial artery at the left wrist of the subject. In order to measure the reference pulse rate, an electronic sphygmomanometer was installed at the upper arm of the subject. The measurements using the FBG sensor and the electronic blood pressure were performed at the same time. The peak interval (PPI) of the FBG sensor

signal was measured, and the pulse rate per min was calculated from Eq. (2).

as those for the experiment on heartbeat discussed in Section 4.

*PRcal*(*times*/*minutes*) = *PPI*/60 (2)

where, *PRcal* is calculated pulse rate, and *PPI* is the peak interval. Three subjects were measured in supine position, and the measurement conditions were the same

A scatter diagram between the reference pulse rate and the pulse rate calculated from the FBG sensor signal is shown in **Figure 6**. The correlation coefficients for

**48**

**Figure 6.**

*Result of calculated pulse rate from FBG sensor signal.*

The pulse rate was calculated from the FBG sensor signal in Section 5.1. This section describes the measurement and calculation of respiration rate. When a person breathes, a physiological phenomenon called respiratory dynamic arrhythmia occurs, whereby the pulse rate rises during inspiration and decreases during expiration. In other words, the PPI decreases during inspiration, and increases during expiration. Therefore, when breathing is repeated, the PPI cycles up and down, and thus, the period of a breath cycle can be deduced from a PPI cycle. The respiratory rate per min is calculated from Eq. (3),

$$RR\_{cal} = PPI\_{cyc} / \text{\textdegree O} \tag{3}$$

where, *RRcal* is calculated respiration rate, and *PPIcyc* is the cycle of PPI.

Experiments on breathing rate were conducted with three subjects. To measure the reference respiratory rate, a medical face mask attached with a temperature data logger (Ishikura Shoten Co., Ltd., SK-L200 THII) was used. The purpose of the face mask was to prevent the breath from leaking out. Breath temperature is known to be higher than the atmospheric temperature. At the time of inspiration, the temperature of the atmosphere is measured with a data logger. On the contrary, as the breath temperature was measured at exhalation, the value was relatively higher. Thus, a constant periodic temperature change was measured every time the subject breathes. One cycle of this temperature change was used as reference respiration time, and the reference respiratory rate was calculated from Eq. (3). The FBG sensor signal was measured under the same conditions as those for the experiment on pulse rate presented in Section 5.1. The subjects were in sitting posture at the time of measurement.

The results of the temperature data logger and PPI from the FBG sensor signal are shown in **Figure 7**. It is evident that both curves are very similar to each other. In addition, it could be confirmed that the cycle varies depending on the number of breaths. The respiratory rates calculated from the temperature data logger and the FBG sensor signal are plotted against one another in **Figure 8** for the three

**Figure 7.** *Results of the PPI from the temperature data logger and the FBG sensor.*

**Figure 8.** *Result of calculating respiratory rate.*

subjects. The measurement accuracies observed for the three subjects were 0.4, 0.6, and 0.4 per min, which were considered to be reasonably good. The high measurement accuracy was observed even for different respiration rates of the same subject and for different subjects. The change in pulse rate (change in PPI interval) due to respiratory dynamic arrhythmia was very small; however, since the sampling rate of the FBG sensor was 10 kHz, it is considered that the calculated respiratory rate was accurate. This measurement method can calculate a respiratory rate in the range of 6–10 bpm; therefore, it is suitable for measurement of slow breathing (~12 bpm or less). It is evident from the above results that the high accuracy of measurement of respiratory rate is attributable to the high sampling rate.
