Verification of embedding conditions for FBG sensor into textile product for the development of wearable healthcare sensor.

BACKGROUND: To develop wearable healthcare sensors that use fiber Bragg grating (FBG) sensors, a stretch textile product with an embedded FBG sensor is required. OBJECTIVE: The FBG sensor, which is an optical fiber, was embedded into a textile product following a wavy pattern by using a warp knitting machine. METHODS: When an optical fiber is embedded in a textile product, the effect of the cycle length of wavy pattern and the number of cycles on the optical loss is verified. The shorter the cycle length of the wavy pattern of the optical fiber, and more increase in the number of cycles, the longer the textile product in which the optical fiber is embedded can expand and contract. However, when the cycle length of the wave pattern is 30 mm (shortest), large in optical loss, the pulse wave signal cannot be measured. If the cycle length of the wavy pattern is 50 mm or more, small in optical loss, the pulse wave signal is measured. RESULTS: Compared with a straight pattern embedding FBG sensor, the amplitude value of the pulse wave signal measured with a cycle length of 50 mm is large, therefore the sensor sensitivity in this state is greater. This result is consistent with the measurement sensitivity depending on the angle of installation with respect to the direction of the artery. CONCLUSION: With a cycle length of wavy pattern of 50 mm and 4 cycles, a stretch textile product with an embedded FBG sensor can be fabricated. Pulse wave signals are measured with this textile product, and the development of wearable healthcare sensors is expected.

Measurement of Pulse Wave Signals and Blood Pressure by a Plastic Optical Fiber FBG Sensor.

Fiber Bragg grating (FBG) sensors fabricated in silica optical fiber (Silica-FBG) have been used to measure the strain of human arteries as pulse wave signals. A variety of vital signs including blood pressure can be derived from these signals. However, silica optical fiber presents a safety risk because it is easily fractured. In this research, an FBG sensor fabricated in plastic optical fiber (POF-FBG) was employed to resolve this problem. Pulse wave signals were measured by POF-FBG and silica-FBG sensors for four subjects. After signal processing, a calibration curve was constructed by partial least squares regression, then blood pressure was calculated from the calibration curve. As a result, the POF-FBG sensor could measure the pulse wave signals with an signal to noise (SN) ratio at least eight times higher than the silica-FBG sensor. Further, the measured signals were substantially similar to those of an acceleration plethysmograph (APG). Blood pressure is measured with low error, but the POF-FBG APG correlation is distributed from 0.54 to 0.72, which is not as high as desired. Based on these results, pulse wave signals should be measured under a wide range of reference blood pressures to confirm the reliability of blood pressure measurement uses POF-FBG sensors.

Wireless, Portable Fiber Bragg Grating Interrogation System Employing Optical Edge Filter.

A small-size, high-precision fiber Bragg grating interrogator was developed for continuous plethysmograph monitoring. The interrogator employs optical edge filters, which were integrated with a broad-band light source and photodetector to demodulate the Bragg wavelength shift. An amplifier circuit was designed to effectively amplify the plethysmograph signal, obtained as a small vibration of optical power on the large offset. The standard deviation of the measured Bragg wavelength was about 0.1 pm. The developed edge filter module and amplifier circuit were encased with a single-board computer and communicated with a laptop computer via Wi-Fi. As a result, the plethysmograph was clearly obtained remotely, indicating the possibility of continuous vital sign measurement.

Verification of Non-Invasive Blood Glucose Measurement Method Based on Pulse Wave Signal Detected by FBG Sensor System.

This paper describes and verifies a non-invasive blood glucose measurement method using a fiber Bragg grating (FBG) sensor system. The FBG sensor is installed on the radial artery, and the strain (pulse wave) that is propagated from the heartbeat is measured. The measured pulse wave signal was used as a collection of feature vectors for multivariate analysis aiming to determine the blood glucose level. The time axis of the pulse wave signal was normalized by two signal processing methods: the shortest-time-cut process and 1-s-normalization process. The measurement accuracy of the calculated blood glucose level was compared with the accuracy of these signal processing methods. It was impossible to calculate a blood glucose level exceeding 200 mg/dL in the calibration curve that was constructed by the shortest-time-cut process. In the 1-s-normalization process, the measurement accuracy of the blood glucose level was improved, and a blood glucose level exceeding 200 mg/dL could be calculated. By verifying the loading vector of each calibration curve to calculate the blood glucose level with a high measurement accuracy, we found the gradient of the peak of the pulse wave at the acceleration plethysmogram greatly affected.

Influence of Individual Differences on the Calculation Method for FBG-Type Blood Pressure Sensors.

In this paper, we propose a blood pressure calculation and associated measurement method that by using a fiber Bragg grating (FBG) sensor. There are several points at which the pulse can be measured on the surface of the human body, and when a FBG sensor located at any of these points, the pulse wave signal can be measured. The measured waveform is similar to the acceleration pulse wave. The pulse wave signal changes depending on several factors, including whether or not the individual is healthy and/or elderly. The measured pulse wave signal can be used to calculate the blood pressure using a calibration curve, which is constructed by a partial least squares (PLS) regression analysis using a reference blood pressure and the pulse wave signal. In this paper, we focus on the influence of individual differences from calculated blood pressure based on each calibration curve. In our study, the calculated blood pressure from both the individual and overall calibration curves were compared, and our results show that the calculated blood pressure based on the overall calibration curve had a lower measurement accuracy than that based on an individual calibration curve. We also found that the influence of the individual differences on the calculated blood pressure when using the FBG sensor method were very low. Therefore, the FBG sensor method that we developed for measuring the blood pressure was found to be suitable for use by many people.