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87 articles for “bio signal processing”
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Efficient AES for Biometric Image Signal Processing
Abstract: Abstract: Several computation schemes and architectural designs have been suggested during the last three decades for efficient hardware implementation of biometric applications. The biometric application of advanced encryption standard (AES) algorithm in high texture image signal processing. The proposed AES very large-scale Integration (VLSI) architecture has 16 % and 15 % less dynamic power consumption and LUT utilization then available best design available AES architecture in the presented literature survey. …
Published in Current Trends in Signal Processing · Vol. 9, Issue 1, 2019 · pp. 7–9 Read article
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A Comparison on Driver Fatigue/Drowsiness Detection Methods
Abstract: The rapid improvements in the automobile industry have made our vehicles more powerful, easier to drive and control, safer, more energy efficient, and more environmentally friendly. The accidents caused today by cars are mainly due to the driver fatigue. Driving for a long period of time causes excessive fatigue and tiredness which makes the driver sleepy or loose awareness. The rapid increase in the number of accidents seems to be …
Published in Journal of Automobile Engineering and Applications · Vol. 4, Issue 1, 2017 · pp. 29–33 Read article
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Analysis of Signal Processing Algorithms for Bio-Medical Applications
Abstract: Epilepsy is a burdensome brain disorder, in which heavy seizures will happen again and again. Sudden explosion of electrical activity during the seizures will create a blackout for patients and it will break the body equilibrium, so patients may fall down. Epilepsy affects a large population around the globe. It may begin at any age and last for generations. It can be controlled by the surgical removal of the brain …
Published in Current Trends in Signal Processing · Vol. 12, Issue 3, 2022 · pp. 24–27 Read article
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Signal Drift Compensation in Polymer-Based Wearable Biosensors Using Data Processing Techniques
Abstract: Polymer-based wearable biosensors have emerged as promising platforms for continuous physiological monitoring due to their mechanical flexibility, low operating voltage, and compatibility with soft biological interfaces. However, their long-term deployment remains challenging because of signal drift caused by polymer ageing, hydration–dehydration cycles, ionic trapping, and environmental variations. These effects introduce baseline fluctuations and sensitivity degradation, which compromise the reliability and interpretability of physiological measurements. This study proposes a data-processing–driven framework …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 197–207 Read article
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Genesis of English Language with its Cybernetics Origin
Abstract: AbstractThis paper is looking into the genesis of the English language with its Cybernetics origins and hence looking into the possibilities of developing new techniques to be used in speech processing applications. As we all know, English is the third-most-spoken language in the world by a number of native speakers, which is used to create the present world, which is also a West Germanic language that was first spoken early …
Published in Current Trends in Signal Processing · Vol. 10, Issue 1, 2020 · pp. 19–28 Read article
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Edge Computing Assisted Polymer Composite Biosensors for real time medical Analytics
Abstract: The fast development of healthcare technologies has generated the increased need of real-time, correct, and effective medical monitoring systems. Polymer composite biosensors have come out as a viable solution since they are flexible, biocompatible and highly sensitive in detecting physiological and biochemical signals. Nevertheless, traditional cloud-based data processing systems bring about latency, bandwidth issues, and privacy risks, and thus are not suitable to use in time-sensitive medical services. In order …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Gene Expression Profiling in Autism Spectrum Disorder: A Microarray Analysis Using Gse42133
Abstract: Autism Spectrum Disorder (ASD) is a diverse neurodevelopmental disorder characterized by difficulties in social interaction, communication impairments, and restricted or repetitive patterns of behavior. Despite its increasing prevalence, the underlying molecular mechanisms remain poorly understood. Advances in transcriptomics offer opportunities to investigate the gene expression changes that may contribute to ASD pathophysiology. In this study, the microarray dataset GSE42133 was analyzed, which comprises gene expression profiles from peripheral blood samples …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 13, Issue 1, 2026 · pp. 37–48 Read article
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Olfactory Intelligence in Bio-Hybrid UAVs: Integrating Living Lepidoptera Sensors for High-Precision Environmental Monitoring
Abstract: Autonomous aerial systems still face major challenges when attempting to locate airborne volatile organic compounds because many conventional gas sensors react slowly and cannot reliably follow turbulent chemical plumes. To address this limitation, a bio-hybrid sensing approach was explored using the antenna of the silkworm moth, Bombyx mori, as a natural chemical detector. The antenna was connected to an Electroantennogram (EAG) system that converts biological nerve signals into digital signals …
Published in International Journal of Electrical and Communication Engineering Technology · Vol. 4, Issue 2, 2026 Read article
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Adaptive Drift Correction in Polymer-Based Wearable Biosensors via Data-Driven Signal Modeling
Abstract: Polymer-based wearable biosensors have emerged as a promising technology for continuous health monitoring due to their mechanical flexibility, biocompatibility, and suitability for long-term physiological interfacing. However, prolonged exposure to biofluids, environmental variability, and mechanical deformation introduces signal drift, which significantly degrades measurement accuracy and limits clinical reliability. This paper presents a data-driven methodology for compensating signal drift in polymer-based wearable biosensors using adaptive signal processing and machine learning techniques. The …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 131–139 Read article
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Fractal-Entropy Guided Adaptive Signal Reconstruction for Non-Stationary Biomedical and Communication Systems
Abstract: This paper presents a novel Fractal-Entropy Guided Adaptive Signal Reconstruction (FEG- ASR) framework designed for accurate processing of non-stationary signals in biomedical and communication systems. The proposed approach integrates fractal dimension analysis with entropy- based feature evaluation to capture the intrinsic complexity and irregularity of time-varying signals. By dynamically adapting reconstruction parameters based on fractal-entropy measures, the method effectively separates noise from meaningful signal components while preserving critical information. The …
Published in Current Trends in Signal Processing · Vol. 16, Issue 1, 2026 · pp. 22–33 Read article
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Cognitive Polymer Composite Systems for Autonomous Biomedical Response
Abstract: Cognitive polymer composite systems: A novel form of intelligent biomaterials with the capability to sense, process and respond to real time physiological stimuli on their own. The present paper offers a comprehensive platform to integrate stimulus responsive polymers with intrinsic sensing networks and learning based decision models to offer adaptable bio-medical solutions. Mathematical formulations are available that are used to model stimulus response behavior, sensor signal processing and cognition decision …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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The Rise of Fractional Calculus: Novel Applications in Engineering and Biological Systems
Abstract: Fractional calculus (FC) is an advanced mathematical framework that generalizes the classical concepts of differentiation and integration to non-integer, or fractional, orders. This extension of traditional calculus allows for the modeling of complex dynamic systems that exhibit behavior not easily captured by integer-order differential equations. Over the last few decades, fractional calculus has seen a rapid rise in popularity, particularly in applied mathematics, engineering, and biological sciences, due to its …
Published in Recent Trends in Mathematics · Vol. 1, Issue 2, 2024 · pp. 7–11 Read article
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Nanoyeast Supported on Silica Gel for The Continuous Flow Bioethanol Production
Abstract: Nanomaterials outperform their bulk counterparts. Yet, production of nanomaterials, especially, nanoyeast is a challenge and is an upcoming field. Yeast is a fungal strain that consumes carbohydrates (glucose, sucrose, molasses and the like) and produces bioethanol, a potential transportation fuel. Impregnation methods are well known in catalysis to yield nanomaterials via better dispersion. An attempt has been made to modulate the size of yeast to increase the efficiency of carbohydrate …
Published in International Journal of Advance in Molecular Engineering · Vol. 2, Issue 1, 2024 · pp. 1–7 Read article
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Advancements in AI-Driven Sound Spectrogram Analysis: From Deep Learning to Quantum and Neuromorphic Processing
Abstract: The rapid advancement of artificial intelligence (AI) has significantly reshaped the field of audio signal processing, with sound spectrogram analysis emerging as a central research focus. Spectrograms provide a rich time–frequency representation of audio signals, making them particularly suitable for data-driven learning approaches. This paper presents an in-depth and original review of modern AI-based techniques applied to spectrogram analysis, highlighting their growing impact across critical application areas such as healthcare …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 13, Issue 1, 2026 · pp. 01–06 Read article
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Music on Mind and Body: A Simultaneous EEG and EMG Study to Quantify Emotions from Hindustani Classical Music
Abstract: With the advent of various techniques to assess the bioelectric signals on the surface of the body, it has become possible to develop various human-computer interface systems. In this study, for the first-time a cross- correlation based data is reported for two-different types of bio-signals viz. EEG (Electroencephalography) and EMG (Electromyography). Whereas EEG refers to the neuro-electric impulses generated in the brain recorded in the form of electric potentials, EMG …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 9, Issue 2, 2019 · pp. 27–38 Read article
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Biopolymer Degradation and Structure–Property Relationships in Ageing: A Polymer Science Perspective
Abstract: Ageing, as viewed from the polymer sciences perspective, is perceived as the gradual modification of the structure-property-function interrelationship of biopolymers such as proteins, polysaccharides, nucleic acids and their molecular aggregates. Such changes include structural organization, mechanical behavior, physicochemical stability and functional effectiveness. Ageing is an inevitable multifactorial polymeric process. Due to the growing aging population globally, more age-associated complications emerge, which are correlated with the molecular degeneration of biopolymeric complexes. …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 479–489 Read article
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Role of Solid-State Materials in Development of devices for Internet of Medical Things
Abstract: The Internet of Medical Things (IoMT) represents a transformative paradigm in healthcare delivery, integrating connected medical devices, sensors, and wearable technologies to enable real-time patient monitoring and personalized treatment. Solid-state materials form the foundational infrastructure of IoMT systems, encompassing semiconductors, energy storage materials, sensing materials, and flexible electronics. This article explores the critical role of advanced solid-state materials in enabling miniaturization, energy efficiency, biocompatibility, and enhanced sensing capabilities essential for …
Published in International Journal of Solid State Innovations & Research · Vol. 3, Issue 2, 2025 · pp. 11–18 Read article
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Graphene–Perovskite Hybrid Opto-Electronic Modulators for Ultra-Low Power Optical Communication
Abstract: This paper proposes a novel self-adaptive neuromorphic opto-electronic transceiver architecture designed to enhance the intelligence, adaptability, and efficiency of next-generation optical communication networks. The proposed system integrates neuromorphic computing principles with photonic signal processing to enable real-time learning, dynamic resource allocation, and autonomous compensation of channel impairments such as dispersion, nonlinearities, and noise. Unlike conventional transceivers, the developed model employs spiking neural networks embedded within opto-electronic circuits to mimic biological …
Published in Trends in Opto-electro & Optical Communication · Vol. 16, Issue 1, 2026 · pp. 41–52 Read article
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From Noise to Insight: An Academic Study of Electrical Signal Processing
Abstract: Electrical signal processing is very important for turning raw, often noisy data into useful and actionable information. This article gives a simple and easy-to-understand summary of the basic ideas and methods used in electrical signal processing, such as filtering, signal representation, modulation, and spectrum analysis. The focus is on how to effectively eliminate noise and interference to improve the quality and dependability of signals. The conversation connects ideas from theory …
Published in Current Trends in Signal Processing · Vol. 16, Issue 1, 2026 · pp. 10–21 Read article
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Nutrient Sensing and Microbiota Crosstalk: Driving Determinants Shaping Metabolic Stability and Adaptive Physiology for Animal Health
Abstract: Nutrient sensing is a fundamental cellular process that enables animals to adapt to fluctuating dietary inputs while maintaining metabolic homeostasis and health. Recent advances reveal that the gut microbiota functions as an active metabolic partner, producing bioactive metabolites that directly influence host nutrient-sensing pathways and downstream cellular responses. This review synthesizes current knowledge on the integration of key signalling networks, including adenosine monophosphate activated protein kinase (AMPK), mechanistic target of …
Published in International Journal of Molecular Biotechnological Research · Vol. 4, Issue 2, 2026 Read article