A multinational team of researchers have developed a speckle pattern analysis based polymer optical fibre (POF) sensor, integrated with a wristband, to enhance monitoring of pulse waves – vital indicators of physiological health, holding substantial information that can aid in diagnosing various medical conditions.
Compared to previous pulse signal monitoring wristbands, the new smart photonic wristband demonstrated improved sensitivity, accuracy, and portability. The pulse wave information collected by the wristband also contained more detailed medical information.
Advancing pulse wave monitoring with POF
Current methods for monitoring pulse waves often rely on electronic wearable sensors, such as piezoelectric and capacitive devices. However, these can suffer from poor electromagnetic compatibility, leading to data distortion and potential misdiagnosis.
To address these existing issues, the research group proposed a speckle pattern analysis-based POF sensor, integrated with a wristband for pulse wave monitoring in a more robust, smart photonic wristband. The wristband uses different core diameters and various image-processing algorithms, which are designed to optimise the sensor.
The research, published in Opto-Electronic Science, reveals the success the researchers had in tackling existing limitations. It stated: “The results indicated that the smart photonic wristband had a high signal-to-noise ratio and low latency, with the measurement error controlled at approximately 3.7%”
Testing indicated that even at a bending angle of 45 degrees, approximately 60% of light transmission through the POF was maintained, ensuring sensitivity for effective monitoring. The wristband exhibited a high linearity (within a pressure range of 0-45N, minimising distortion in pulse detection.
Going beyond with AI and mixed medicine experience
The wristbands employ a sophisticated AI algorithm that boasts a 95% accuracy rate in recognising different gestures. This capability is instrumental in screening potential patients for related health conditions. The development of a cloud system also allows wearers to monitor their pulse and exercise data seamlessly via Wi-Fi, advancing the field of healthcare cloud IoT technology.
Beyond pulse monitoring, the smart wristband is capable of performing traditional pulse palpation techniques similar to those used in Chinese medicine, such as identifying pulse positions at CunKou. It is viewed that the integration of Eastern and Western medical practices enhances the standardisation and objectivity of traditional diagnostics.
The team envisions deploying the smart photonic wristband in medical environments where resistance to electromagnetic interference is crucial, such as MRI scanning, CT systems, and diagnostic ultrasounds. Additionally, the team also touted the wristband for applications in the field of Internet of Things.
Future work will continue to focus on the Cunkou diagnostic method, refining the quantitative analysis of pulse waves among various patients and healthy people.
