Distributed fiber gratings exhibit outstanding capabilities in achieving a wide spectral response through the superimposition of gratings with different periods in the fiber core. This significantly broadens the design flexibility and potential applications of fiber gratings. However, as photons pass through gratings with varying periods in sequence, which not only inevitably existing signal crosstalk but also poses challenges for integrating. In this study, a three-dimensional (3D) four-channel filter is proposed and realized in fiber-compatible materials using femtosecond laser writing. The filter consists of a 3D beam splitter and four parallel different-period Bragg waveguide gratings (WGs). By designing grating periods in each path, parallel filtering and reflection at multiple designed wavelengths are achieved compactly with 50 nm spectrum spacing within 1450–1600 nm wavelengths. The four-channel filter entire measures 15.5 mm × 1 mm × 1 mm (the highest integration of distributed fiber gratings reported so far). Our technique will augment the laser fabrication technology for 3D integrated photonic devices and serve as a powerful and generalized solution for highly integrated in-situ measurement and multi-parameter decoupled sensing.

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.