RESUMEN

Clinical fetal monitoring devices can only be operated by medical professionals and are overly costly, prone to detrimental false positives, and emit radiation. Thus, highly accurate, easily accessible, simplified, and cost-effective fetal monitoring devices have gained an enormous interest in obstetrics. In this study, a cost-effective and user-friendly wearable home fetal movement and distress detection device is developed and assessed for early-stage design progression by facilitating continuous, comfortable, and non-invasive monitoring of the fetus during the final trimester. The functionality of the developed prototype is mainly based on a microcontroller, a single accelerometer, and a specialized fetal phonocardiography (fPCG) acquisition board with a low-cost microphone. The developed system is capable of identifying fetal movement and monitors fetal heart rhythm owing to its considerable sensitivity. Further, the device includes a Global System for Mobile Communication (GSM)-based alert system for instant distress notifications to the mother, proxy, and emergency services. By incorporating digital signal processing, the system achieves zero false negatives in detecting fetal movements, which was validated against an open-source database. The acquired results clearly substantiated the efficacy of the fPCG acquisition board and alarm system, ensuring the prompt identification of fetal distress.

RESUMEN

Circular leaf spot (CLS) disease poses a significant threat to persimmon cultivation, leading to substantial harvest reductions. Existing visual and destructive inspection methods suffer from subjectivity, limited accuracy, and considerable time consumption. This study presents an automated pre-identification method of the disease through a deep learning (DL) based pipeline integrated with optical coherence tomography (OCT), thereby addressing the highlighted issues with the existing methods. The investigation yielded promising outcomes by employing transfer learning with pre-trained DL models, specifically DenseNet-121 and VGG-16. The DenseNet-121 model excels in differentiating among three stages of CLS disease (healthy (H), apparently healthy (or healthy-infected (HI)), and infected (I)). The model achieved precision values of 0.7823 for class-H, 0.9005 for class-HI, and 0.7027 for class-I, supported by recall values of 0.8953 for class-HI and 0.8387 for class-I. Moreover, the performance of CLS detection was enhanced by a supplemental quality inspection model utilizing VGG-16, which attained an accuracy of 98.99% in discriminating between low-detail and high-detail images. Moreover, this study employed a combination of LAMP and A-scan for the dataset labeling process, significantly enhancing the accuracy of the models. Overall, this study underscores the potential of DL techniques integrated with OCT to enhance disease identification processes in agricultural settings, particularly in persimmon cultivation, by offering efficient and objective pre-identification of CLS and enabling early intervention and management strategies.

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RESUMEN

Speckle patterns are a generic feature in coherent imaging techniques like optical coherence tomography (OCT). Although speckles are granular like noise texture, which degrades the image, they carry information that can be benefited by processing and thereby furnishing crucial information of sample structures, which can serve to provide significant important structural details of samples in in vivo longitudinal pre-clinical monitoring and assessments. Since the motions of tissue molecules are indicated through speckle patterns, speckle variance OCT (SV-OCT) can be well-utilized for quantitative assessments of speckle variance (SV) in biological tissues. SV-OCT has been acknowledged as a promising method for mapping microvasculature in transverse-directional blood vessels with high resolution in micrometers in both the transverse and depth directions. The fundamental scope of this article reviews the state-of-the-art and clinical benefits of SV-OCT to assess biological tissues for pre-clinical applications. In particular, focus on precise quantifications of in vivo vascular response, therapy assessments, and real-time temporal vascular effects of SV-OCT are primarily emphasized. Finally, SV-OCT-incorporating pre-clinical techniques with high potential are presented for future biomedical applications.