Clothing-based respiratory monitoring can provide real-time non-invasive respiratory monitoring services for subjects, and can be used as a reference for daily health observation. In this study, an optical fiber sensing Section woven into plain fabric is produced by a hand-weaving machine, and the produced sensing fabric is then made into a respiratory monitoring garment. This paper explored the luminescence and coupling principle of notched optical fiber through theoretical analysis and simulation, and demonstrated the feasibility of making it into respiratory sensing fabric. We used this structure to make a fabric and then sew the fabric with the yoke to make a smart garment. In testing, we obtained the static respiratory waveform and the respiratory rate (R-R) during daily common movements, which were also compared with two types of commercial sensors. The results showed that the smart garment based on optical fiber sensing fabric maintains good consistency with the monitoring waveform of commercial sensors and good R-R obtained in static motion (error not more than 2 rpm). Monitoring tests showed that the garment has high monitoring accuracy and motion monitoring stability. Moreover, it was also very comfortable and can be used as daily respiratory monitoring equipment.

A waveguide Bragg grating (WBG) provides a flexible way for measurement, and it could even be used to measure body temperature like e-skin. We designed and compared three structures of WBG with the grating period, etching depth, and duty cycle. The two-sided WBG was fabricated. An experimental platform based on photonic integrated interrogator was set up and the experiment on the two-sided WBG was performed. Results show that the two-sided WBG can be used to measure temperature changes over the range of 35–42 °C, with a temperature measurement error of 0.1 °C. This approach has the potential to facilitate application of such a silicon-on-insulator (SOI) WBG photonic sensor to wearable technology and realize the measurement of human temperature.

A compact and label-free biosensor based on coreless-fiber-coupled microcavity is proposed and experimentally demonstrated for bovine serum albumin (BSA) detection. The microcavity is fabricated in a coreless fiber by on-line fiber cutting-welding micromachining. Experimental results show that the BSA samples with different concentration and refractive index ranging from 1.3344 to 1.3349 are clearly discriminated by spectral characteristics of the coreless-fiber-coupled microcavity, with a sensitivity of 1.602 nm/(mg/ml). The device presents superiorities such as miniature size, standardized production control, reliable quality, and cost effective, which makes it a good candidate for the detection of low-concentration micro-samples analytes in the fields of life sciences, biological engineering, and biopharmaceutical industry.

Heart disease is the leading cause of death for men and women globally. The residual network (ResNet) evolution of electrocardiogram (ECG) technology has contributed to our understanding of cardiac physiology. We propose an artificial intelligence-enabled ECG algorithm based on an improved ResNet for a wearable ECG. The system hardware consists of a wearable ECG with conductive fabric electrodes, a wireless ECG acquisition module, a mobile terminal App, and a cloud diagnostic platform. The algorithm adopted in this study is based on an improved ResNet for the rapid classification of different types of arrhythmia. First, we visualize ECG data and convert one-dimensional ECG signals into two-dimensional images using Gramian angular fields. Then, we improve the ResNet-50 network model, add multistage shortcut branches to the network, and optimize the residual block. The ReLu activation function is replaced by a scaled exponential linear units (SELUs) activation function to improve the expression ability of the model. Finally, the images are input into the improved ResNet network for classification. The average recognition rate of this classification algorithm against seven types of arrhythmia signals (atrial fibrillation, atrial premature beat, ventricular premature beat, normal beat, ventricular tachycardia, atrial tachycardia, and sinus bradycardia) is 98.3%.

It is significant to monitor respiration conveniently and in real time for people suffering from respiratory diseases. Polymer optical fibers (POFs) have the advantages of flexibility and light weight, which is highly desirable for wearable respiratory monitoring. However, in most current applications, the POFs are stitched on the textile substrates in the form of macro-bending. This method is complex to fix the bending with certain curvatures and uncomfortable compared with the POF sensors woven into the textile. In this paper, a respiratory fabric sensor based on the side luminescence and photosensitivity mechanism of POF is proposed and demonstrated. The 750µm-diameter POFs were woven into a fabric as warp and laser marking was performed at their designed positions to make them release or couple light. The spacing change between the POFs caused by the respiratory movement accordingly makes the light intensity change in the photosensitive fiber. We chose four fabric widths (10cm, 8cm, 6cm and 4cm) and four fabric weaves (plain weave, honeycomb weave, 1/3 right twill weave and 8/3 warp satin weave) to implement the full-factor experiment for exploring the measurement effect of the respiratory fabric sensor. The result is that the fabric with width of 4cm and weave of 8/3 warp satin is optimal. The calm and deep respiratory tests of the human chest and abdomen in sitting and standing posture were carried out and the test performance of the fabric sensor is almost comparable to that of the medical monitor. The proposed respiratory fabric sensor is comfortable, easily woven and high in precision, which is expected to realize industrialized scale production.