Quality-Aware Signal Processing Mechanism of PPG Signal for Long-Term Heart Rate Monitoring.

Photoplethysmography (PPG) is widely utilized in wearable healthcare devices due to its convenient measurement capabilities. However, the unrestricted behavior of users often introduces artifacts into the PPG signal. As a result, signal processing and quality assessment play a crucial role in ensuring that the information contained in the signal can be effectively acquired and analyzed. Traditionally, researchers have discussed signal quality and processing algorithms separately, with individual algorithms developed to address specific artifacts. In this paper, we propose a quality-aware signal processing mechanism that evaluates incoming PPG signals using the signal quality index (SQI) and selects the appropriate processing method based on the SQI. Unlike conventional processing approaches, our proposed mechanism recommends processing algorithms based on the quality of each signal, offering an alternative option for designing signal processing flows. Furthermore, our mechanism achieves a favorable trade-off between accuracy and energy consumption, which are the key considerations in long-term heart rate monitoring.

Unraveling the Structural Statistics and Its Relationship with Mechanical Properties in Metallic Glasses.

Metallic glasses exhibit excellent properties such as ultrahigh strength and excellent wear and corrosion resistance, but there is limited understanding on the relationship between their atomic structure and mechanical properties as a function of their structural state. In this paper, we bridge the processing-structure-property gap by utilizing molecular dynamics simulation for a model binary metallic glass, namely Ni80P20. The structural statistics including the fraction of Voronoi index, the distribution of Voronoi volume, and medium-range ordering are calculated to explain the observed changes in mechanical behavior and strain localization upon relaxation and rejuvenation. Our findings demonstrate that the evolution of mechanical properties can be linked to the atomic structure change in terms of short- and medium-range ordering. With the help of structural statistics, the mechanical properties are determined based on simple Voronoi analysis.

Multiscale Manufacturing of Amorphous Alloys by a Facile Electrodeposition Approach and Their Property Dependence on the Local Atomic Order.

Metallic glasses are a unique class of materials combining ultrahigh strength together with plastic-like processing ability. However, the currently used melt quenching route to obtain amorphous alloys has a high cost basis in terms of manufacturing and expensive constituent elements often necessary to achieve the glassy state, thus hindering widespread adoption. In contrast, multimaterial electrodeposition offers a low-cost and versatile alternative to obtain amorphous alloys. Here, we demonstrate multiscale manufacturing of a model binary amorphous system by a facile and scalable pulsed electrodeposition approach. The structural and mechanical characteristics of electrodeposited Ni-P metallic glasses are investigated by a combination of experiments and molecular dynamics simulations. The property dependence on slight change in alloy chemistry is explained by the fraction of short-range-order clusters and geometrically unfavorable motifs. Bicapped square antiprism polyhedra clusters with two-atom connections result in more homogeneous deformation for Ni90P10 metallic glass, whereas a relatively higher fraction of three-atom connections in Ni85P15 metallic glass leads to higher strength, albeit localized and relatively brittle failure. The practicality of our approach is likely to stimulate the use of amorphous alloys in simple chemistries for multiscale use with systematic property optimization for specific applications.