Flexible pressure sensors have gained considerable attention for their potential applications in wearable electronics and human−machine interfacing. However, two major bottlenecks in their widespread usage (i) achieving high sensitivity over a wide working pressure range and (ii) constituent material platform for manufacturability and environmental safety still limits its utility. Herein, we suggest a low-cost hierarchical construction strategy, which enhances the sensitivity of a paper-based piezoresistive pressure sensor over a wide working range. This strategy uses a special multilayered cellulose paper structure composed of alternate layers of plain and corrugated paper sheets, coated with 2D tin-monosulfide (SnS). This design of the paper pressure sensor allows it to achieve high sensitivity up to 14.8 kPa−1 and a broad working range of 0−120 kPa with good durability and repeatability. Further, to confirm practical applicability, we utilized an array of these multilayered flexible pressure sensors for monitoring human activity and developing a biodegradable and foldable keypad. The proposed paper-based green electronic platform can potentially be used in a variety of applications including healthcare and human−machine interfacing.
Low-cost automated histopathology microscopy systems usually suffer from optical imperfections, producing images that are slightly Out of Focus (OoF). In this work, a guided filter (GF) based image preprocessing is proposed for compensating focal errors and its efficacy is demonstrated on images of healthy and malaria infected red blood cells (h-RBCs and i-RBCs), and PAP smears. Since contrast enhancement has been widely used as an image preprocessing step for the analysis of histopathology images, a systematic comparison is made with six such prominently used methods, namely Contrast Limited Adaptive Histogram Equalization (CLAHE), RIQMC-based optimal histogram matching (ROHIM), modified L 0 , Morphological Varying(MV)-Bitonic filter, unsharp mask filter and joint bilateral filter. The images enhanced using GF approach lead to better segmentation accuracy (upto 50% improvement over native images) and visual quality compared to other approaches, without any change in the color tones. Thus, the proposed GF approach is a viable solution for rectifying the OoF microscopy images without the loss of the valuable diagnostic information presented by the color tone.
Microscopic observation of biological specimen smears is the mainstay of diagnostic pathology, as defined by the Digital Pathology Association. Though automated systems for this are commercially available, their bulky size and high cost renders them unusable for remote areas. The research community is investing much effort towards building equivalent but portable, low‐cost systems. An overview of such research is presented here, including a comparative analysis of recent reports. This paper also reviews recently reported systems for automated staining and smear formation, including microfluidic devices; and optical and computational automated microscopy systems including smartphone‐based devices. Image pre‐processing and analysis methods for automated diagnosis are also briefly discussed. It concludes with a set of foreseeable research directions that could lead to affordable, integrated and accurate whole slide imaging systems.
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