Abstract

Real-time acquisition of human pulse signals in daily life is clinically important for cardiovascular disease monitoring and diagnosis. Here, we propose a smart photonic wristband for pulse signal monitoring based on speckle pattern analysis with a polymer optical fiber (POF) integrated into a sports wristband.

Several different speckle pattern processing algorithms and POFs with different core diameters were evaluated. 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%. This optimized pulse signal could be used for further medical diagnosis and was capable of objectively monitoring subtle pulse signal changes, such as the pulse waveform at different positions of Cunkou and pulse waveforms before and after exercise.

With the assistance of artificial intelligence (AI), functions such as gesture recognition have been realized through the established prediction model by processing pulse signals, in which the recognition accuracy reaches 95%. Our AI-assisted smart photonic wristband has potential applications for clinical treatment of cardiovascular diseases and home monitoring, paving the way for medical Internet of Things-enabled smart systems.