A new publication from Opto-Electronic Sciences; DOI 10.29026/oes.2024.240009 , discusses a smart photonic wristband for pulse wave monitoring.
Pulse waves are a prominent component of physiological signaling and involve abundant health information. Real-time monitoring of pulse signals and effective medical analysis can not only monitor and diagnosis fundamental diseases, but also play an active role in various fields, including multi-location monitoring to aid in traditional Chinese medicine diagnosis, and gesture recognition. Currently, various types of electronic wearable sensors are used to acquire the pulse signal, including piezoelectric, resistance, and capacitance. However, poor electromagnetic compatibility of some electrical medical sensors can lead to data distortion and medical misdiagnosis, which restrict the practical applications of electronic sensors to some extent. Optical fiber sensors provide a promising alternative to electronic sensors due to their resistance to drift, inherent electric safety, and electromagnetic interference immunity.
FSSs are a type of optical fiber sensor based on the multimode interference effect and have been developed rapidly in the past few years due to advantages such as high sensitivity, high precision, and fast response. Herein, the details of the pulse waveform can be distinguished to estimate the pulse rate more accurately. However, silica optical fiber may cause damage to the body in some specific sensing scenarios, such as wearable devices, due to some disadvantages of the sensors based on silica optical fiber, such as low flexibility and fragmentation ability. Polymer optical fibers (POFs) are made of polymer materials with the advantages of low-cost, high flexibility, strain limits, fracture toughness, and a low Young's modulus. Therefore, the sensor based on POF is one promising solution for pulse signal monitoring, which can be attempted as a suitable alternative to traditional methods and fulfill the requirements of further clinical trials.
To address the above problems, the research group of Dr. Rui Min from Beijing Normal University collaborated with Prof. Heng Wang from Shenyang University of Aeronautics and Astronautics, Prof. Qingming Chen from Sun Yat-sen University, Prof. Arnaldo Leal Junior from the Federal University of Espírito Santo(Brazil), Prof. Santosh Kumar from the Koneru Lakshmaiah Education Foundation (India), and Prof. Carlos Marques from the University of Aveiro(Portugal) propose a speckle pattern analysis based POF sensor integrated with a wristband for pulse signal monitoring as a smart photonic wristband, as shown in Fig. 1. POFs with different core diameters and various image-processing algorithms were designed to optimize the sensor. Compared to other existing works, the smart photonic wristband present here has improved sensitivity, accuracy, and portability and the collected pulse signal contained detailed medical information, as illustrated in Fig. 2. Performance tests were performed on the POF used in a smart photonic wristband. At a bending angle of 45 degrees (forming a loop for sensing), about 60% of the light could pass through the POF. This ensures that the light signal is sensitive enough under bending to meet the sensing requirements. The linear working range of POF is 0-45 N under applied pressure. A high linearity (R² = 0.989) was demonstrated within this range, which helps to avoid distortion in pulse wave signal detection. In addition, the test results indicated that the signal-to-noise ratio of the smart photonic wristband monitoring was 34.96 dB, and a measurement delay of 369.9 ms between the measurement and the reference ECG signal, respectively, with a measurement error of only 3.7%.
Figure 3 illustrates the experimental results of some applications of the smart photonic wristband. The smart wristband can perform pulse palpation measurements similar to those made by well-trained practitioners of traditional Chinese medicine, including the identification of pulse indicators such as the pulse positions of CunKou. The proposed sensor offers an approach to visual diagnosis that integrates both Eastern and Western medical practices, advancing the standardization and objectification of traditional pulse diagnostic techniques. Smart photonic wristbands could also capture subtle changes in pulse waveforms before and after exercise, and the potential for high sensitivity and stability of smart wristbands in executing users in different exercise states was demonstrated in exercise testing experiments. Furthermore, the AI algorithm has achieved the recognition of different gestures with 95% accuracy, which plays a vital role in screening potential patients with related diseases. Eventually, the team has also developed a cloud system to monitor the user's pulse and exercise information and the data is interconnected using Wi-Fi to the cloud, facilitating advances in healthcare cloud IoT technology. In the future, the smart photonic wristband will be deployed in specific medical settings that demand resistance to electromagnetic interference, such as Magnetic Resonance Imaging (MRI) systems, CT systems, and diagnostic ultrasound systems. The smart photonic wristband reported in this article has high potential for applications in the field of Internet of Things, wearable physiological signal health monitoring.
Keywords: smart healthcare / specklegram / pulse monitoring / gesture recognition / artificial intelligence / wearable sensor
