Intramuscular EMG classifier for detecting myopathy and neuropathy

This article presents an automatic diagnostic system to classify intramuscular electromyography (iEMG) signals, thereby detecting neuromuscular disorders. To this end, we tailored the center symmetric local binary pattern (CSLBP) to analyze one-dimensional ($1$-D) signals. In this approach, the $1$-D CSLBP feature extracted from a decimated iEMG signal is fed to a combination of classifiers, which in turn assigns a set of labels to the signal, and ultimately the signal category is determined by the Boyer-Moore majority voting (BMMV) algorithm. The proposed framework was investigated with a benchmark iEMG dataset that contains signals recorded from three different muscles: biceps brachii (BB), deltoideus (DE), and vastus medialis (VM). In a repeated $10$-fold cross-validation, CSLBP-Combined-Classifiers-BMMV (CSLBP-CC-BMMV) achieved an average classification accuracy of $92.80$%, $94.25$%, and $93.71$% for the iEMG signals recorded from BB, DE, and VM muscle, respectively. Interestingly, the performance of CSLBP-CC-BMMV surpassed the other published approaches and ensemble learning methods that are akin to our scheme in terms of classification accuracy and computational time.     

2D Zinc Oxide – Synthesis,Methodologies, Reaction Mechanism,and Applications

Zinc oxide (ZnO) is a thermally stable n-type semiconducting material. ZnO 2D nanosheets have mainly gained substantial attention due to their unique properties, such as direct bandgap and strong excitonic binding energy at room temperature. These are widely utilized in piezotronics, energy storage, photodetectors, light-emitting diodes, solar cells, gas sensors, and photocatalysis. Notably, the chemical properties and performances of ZnO nanosheets largely depend on the nano-structuring that can be regulated and controlled through modulating synthetic strategies. Two synthetic approaches, top–down and bottom–up, are mainly employed for preparing ZnO 2D nanomaterials. However, owing to better results in producing defect-free nanostructures, homogenous chemical composition, etc., the bottom–up approach is extensively used compared to the top–down method for preparing ZnO 2D nanosheets. This review presents a comprehensive study on designing and developing 2D ZnO nanomaterials, followed by accenting its potential applications. To begin with, various synthetic strategies and attributes of ZnO 2D nanosheets are discussed, followed by focusing on methodologies and reaction mechanisms. Then, their deliberation toward batteries, supercapacitors, electronics/optoelectronics, photocatalysis, sensing, and piezoelectronic platforms are further discussed. Finally, the challenges and future opportunities are featured based on its current development.