Author Correction: Optimal signal quality index for remote photoplethysmogram sensing
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Optimal signal quality index for remote photoplethysmogram sensing
Remote photoplethysmography (rPPG) enables non-invasive monitoring of circulatory signals using mobile devices, a crucial advancement in biosensing. Despite its potential, ensuring signal quality amidst noise and artifacts remains a significant challenge, particularly in healthcare applications. Addressing this, our study focuses on a singular signal quality index (SQI) for rPPG, aimed at simplifying high-quality video capture for heart rate detection and cardiac assessment. We introduce a practical threshold for this SQI, specifically the signal-to-noise ratio index (NSQI), optimized for straightforward implementation on portable devices for real-time video analysis. Employing (NSQI < 0.293) as our threshold, our methodology successfully identifies high-quality cardiac information in video frames, effectively mitigating the influence of noise and artifacts. Validated on publicly available datasets with advanced machine learning algorithms and leave-one-out cross-validation, our approach significantly reduces computational complexity. This innovation not only enhances efficiency in health monitoring applications but also offers a pragmatic solution for remote biosensing. Our findings constitute a notable advancement in rPPG signal quality assessment, marking a critical step forward in the development of remote cardiac monitoring technologies with extensive healthcare implications.
Recent advances in solid-liquid triboelectric nanogenerators for self-powered chemical and biological sensing
Solid-liquid triboelectric nanogenerators (SL-TENGs) exhibit significant potential in energy harvesting and sensing. This review explores SL-TENG development, focusing on chemical sensing and biosensing applications. Initially, the working mechanisms of various SL-TENG modes are described. Subsequently, an analysis of surface modifications of contact surfaces and liquids to functionalize chemical sensing and biosensing is explored, including their impact on surface properties and the corresponding effect on device performance related to sensing applications.
A tip-tilt-piston electrothermal micromirror array with integrated position sensors
A tip-tilt-piston 3 × 3 electrothermal micromirror array (MMA) integrated with temperature field-based position sensors is designed and fabricated in this work. The size of the individual octagonal mirror plates is as large as 1.6 mm × 1.6 mm. Thermal isolation structures are embedded to reduce the thermal coupling among the micromirror units. Results show that each micromirror unit has a piston scan range of 218 μm and a tip-tilt optical scan angle of 21° at only 5 Vdc. The micromirrors also exhibit good dynamic performance with a rise time of 51.2 ms and a fall time of 53.6 ms. Moreover, the on-chip position sensors are proven to be capable for covering the full-range movement of the mirror plate, with the measured sensitivities of 1.5 mV/μm and 8.8 mV/° in piston sensing and tip-tilt sensing, respectively. Furthermore, the thermal crosstalk in an operating MMA has been experimentally studied. The measured results are promising thanks to the embedded thermal isolation structures.
Sensing-actuating integrated asymmetric multilayer hydrogel muscle for soft robotics
Achieving autonomously responding to external stimuli and providing real-time feedback on their motion state are key challenges in soft robotics. Herein, we propose an asymmetric three-layer hydrogel muscle with integrated sensing and actuating performances. The actuating layer, made of p(NIPAm-HEMA), features an open pore structure, enabling it to achieve 58% volume shrinkage in just 8 s. The customizable heater allows for efficient programmable deformation of the actuating layer. A strain-responsive hydrogel layer, with a linear response of up to 50% strain, is designed to sense the deformation process. Leveraging these actuating and sensing capabilities, we develop an integrated hydrogel muscle that can recognize lifted objects with various weights or grasped objects of different sizes. Furthermore, we demonstrate a self-crawling robot to showcase the application potential of the hydrogel muscle for soft robots working in aquatic environments. This robot, featuring a modular distributed sensing and actuating layer, can autonomously move forward under closed-loop control based on self-detected resistance signals. The strategy of modular distributed stimuli-responsive sensing and actuating materials offers unprecedented capabilities for creating smart and multifunctional soft robotics.
Hollow fiber-based strain sensors with desirable modulus and sensitivity at effective deformation for dexterous electroelastomer cylindrical actuator
The electroelastomer cylindrical actuators, a typical representation of soft actuators, have recently aroused increasing interest owing to their advantages in flexibility, deformability, and spatial utilization rate. Proprioception is crucial for controlling and monitoring the shape and position of these actuators. However, most existing flexible sensors have a modulus mismatch with the actuation unit, hindering the free movement of these actuators. Herein, a low-modulus strain sensor based on laser-induced cellular graphitic flakes (CGF) onto the surface of hollow TPU fibers (HTF) is present. Through the electrostatic self-assembly technology, the flexible sensor features a unique hybrid sensing unit including soft HTF as substrate and rigid CGF as conductive path. As a result, the sensor simultaneously possesses desirable modulus (~0.155 MPa), a gauge factor of 220.3 (25% < ε < 50%), fast response/recovery behaviors (31/62 ms), and a low detection limit (0.1% strain). Integrating the sensor onto the electroelastomer cylindrical actuators enables precise measurement of deformation modes, directions, and quantity. As proof-of-concept demonstrations, a prototype soft robot with high-precision perception is successfully designed, achieving real-time detection of its deformations during the crawling process. Thus, the proposed scheme sheds new light on the development of intelligent soft robots.
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