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24 articles for “Biomedical Signal Processing”
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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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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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An Ultra-Low Latency Embedded sEMG-Based Intelligent Control System for Wireless Assistive Wheelchair Navigation Using ESP- NOW Protocol
Abstract: This research provides an ultra-low-latency intelligent control framework for wireless assistive wheelchair movement through single-channel surface electromyography (sEMG) and the ESP-NOW communication technology. The framework presented incorporates sEMG acquisition, simple real-time signal processing, determinable decision logic, and wireless communication for controlling the devices using inexpensive ESP32/ESP8266 microcontrollers. It also allows a system to function as an effective interface between a person and a machine suffering from severe motor disability. The …
Published in Recent Trends in Sensor Research & Technology · Vol. 13, Issue 3, 2026 Read article
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Investigations On Use of Poly(3,4-Ethylenedioxythiophene): Poly (Styrene Sulfonic Acid) (PEDOT: PSS) Conductive Polymers for Design of Improved EEG Based Brain Computer Interface for Seizure Control and Analysis
Abstract: This research explores the application of Poly(3,4-ethylenedioxythiophene):poly(styrene sulfonic acid) (PEDOT:PSS) conductive polymers in the design of an enhanced Electroencephalography (EEG)-based Brain-Computer Interface (BCI) for seizure control and analysis. PEDOT: PSS, known for its high conductivity, flexibility, and biocompatibility, is employed to improve the efficiency and sensitivity of EEG electrodes, addressing challenges such as signal noise, skin-electrode impedance, and user comfort. The study evaluates the material’s properties, including its electrical conductivity, …
Published in Journal of Polymer & Composites · Vol. 13, Issue 3, 2025 · pp. 223–241 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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Biomedical Image Processing: Retinal Blood Vessel Segmentation using Graph Cut Technique
Abstract: Retinal image, which is used in determining different diseases in the eye of a human being, is an important feature in the field of ophthalmology. Similarly, optic disc detection is also an important feature as it locates diseases and defects. In Image processing of fundus, image vessel extraction is the key feature used in doing so. Here, we are presenting the Graph Cut method which helps in extracting blood vessels …
Published in Current Trends in Signal Processing · Vol. 5, Issue 1, 2015 · pp. 17–20 Read article
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Synergistic Integration of MEMS and Spintronics for Precision Data Analytics in Cheminformatics
Abstract: The transformational potential of merging spintronics and Micro-Electromechanical Systems (MEMS) technologies in cheminformatics is investigated in this work. Recent advancements in MEMS, particularly through the use of microbeam sensors and accelerometers, enhance the precision of data collection and processing, especially in biomedical applications such as drug delivery systems and chemical sensing. The synchronization of oscillations in MEMS devices leads to improved reliability and data accuracy, enabling the development of sophisticated …
Published in International Journal of Cheminformatics · Vol. 2, Issue 1, 2024 · pp. 20–26 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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Real-Time Edge Detection Camera Module Using Discrete Taylor Transform and Heat Equation (PDE): An Applied Mathematical Approach
Abstract: In modern digital signal processing, the capability for denoising and smoothing in real time is very important in scientific, engineering, and industrial applications. This paper presents an efficient hybrid framework that merges two mathematically sound methods, namely, DTT and PDE defined as the Heat Equation, to robustly denoise a signal with minimal distortion. The model addresses one of the most challenging tasks in signal restoration, which maintains the fidelity of …
Published in Current Trends in Signal Processing · Vol. 16, Issue 2, 2026 · pp. 9–14 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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Multi-Parameter Biomedical Sensor-Based Mental State Classification Using EEG And Deep Learning Techniques
Abstract: With mental health concerns becoming increasingly widespread, there is a strong need for systems that can monitor conditions like stress, anxiety, and fatigue in a continuous and non- invasive manner. This research proposes a novel multi-parameter biomedical sensing framework for mental state classification by integrating electroencephalography (EEG) signals with physiological parameters, including body temperature acquired using LM35 sensors, heart rate from pulse sensors, and blood oxygen saturation (SpO₂) measurements. The …
Published in Current Trends in Signal Processing · Vol. 16, Issue 2, 2026 · pp. 1–8 Read article
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Analysis of impact of Meditation on Cognitive Workload using EEG Signals
Abstract: AbstractMental activities can be indicated by the Cognitive workload which are useful in applications like Biomedical, Human Machine Interaction and Task analysis. The mental effort applied on the Working memory at a certain given time is commonly known as Cognitive load. The EEG Signals of Cognitive Workload can be studied and classified. The features such as Entropy, Energy, Power, etc. can be extracted from the EEG signals and processed using …
Published in Current Trends in Signal Processing · Vol. 10, Issue 1, 2020 · pp. 29–39 Read article
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Key of Certification to Scheme Cattle Food
Abstract: The present article is the scripture of animal husbandry to achieve scope via nanotechnology. Biological progress is important in farming; if achieved has been introduced in terms of new animal breeds and new production techniques. Basis of role has been developed from nutrition regime and type of feed and additives used, so forth has been interplays of animal production technology. Modern methods of animal production have assisted from bioengineering, genetic …
Published in Research and Reviews : Journal of Veterinary Science and Technology · Vol. 10, Issue 2, 2021 · pp. 18–24 Read article
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An Improved Power Line Interference Reduction Approach Based on Combination of Mirror Extension and IIR filtering Through a Data Driven Mechanism
Abstract: Electrocardiogram (ECG) is a clinical sign monitoring measurement of the cardiac abnormalities. Like other biomedical signals, the ECG signal is also contaminated by various kinds of noise and artifacts such as power line interference, base line wandering, muscle artifacts and electrode artifacts. The present paper proposes a scheme for power line interference (PLI) reduction from ECG signal. It makes use of the concept of mirror method, empirical mode decomposition (EMD) …
Published in Current Trends in Signal Processing · Vol. 7, Issue 2, 2017 · pp. 13–21 Read article
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Scaling of Machine Learning Techniques in Medical Imagining and Biomedical Applications Concerning Healthcare
Abstract: Machine learning refers to a field within computer science enabling computers to learn without explicit programming. Stemming from artificial intelligence's study of pattern recognition and computational learning theory, machine learning develops algorithms capable of learning from vast datasets and making predictions. Its applications span diverse computing tasks like email filtering, network intrusion detection, optical character recognition, and computer vision, where conventional algorithm design proves challenging. Notably, in computer vision, a …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 1, 2024 · pp. 41–44 Read article
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Harnessing the Bioactive Potential of Calotropis gigantea and Calotropis procera
Abstract: The medicinal plants of the Apocynaceae family Calotropis gigantea and Calotropis procera have gained more and more interest as source of bioactive molecules for biomedical applications like cancer therapy. They have various pharmacological activities, which are believed to be linked to various phytochemical constituents such as cardenolides, cardiac glycosides, flavonoids, triterpenoids, steroids, phenolic compounds, alkaloids, and proteins in their latex. The recent molecular and cellular studies show that extracts and …
Published in International Journal of Molecular Biotechnological Research · Vol. 4, Issue 2, 2026 Read article
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Non-Invasive Glucose Monitoring Device Using Max30102 Sensor
Abstract: Diabetes mellitus is a chronic metabolic disorder affecting millions globally, requiring continuous blood glucose monitoring to prevent complications such as cardiovascular disease, kidney failure, neuropathy, and retinopathy. Conventional invasive finger- prick techniques result in pain, skin irritation, and an increased risk of infection, which lowers patient compliance, particularly in young patients and the elderly. This paper presents a non-invasive glucose monitoring prototype using the MAX30102 optical biosensor interfaced with the …
Published in Journal of Instrumentation Technology & Innovations · Vol. 16, Issue 1, 2026 · pp. 36–44 Read article
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EXPLORING BODY TO BODY COMMUNICATION USING HEALTH MONITOR APPLICATION
Abstract: The paper presents a Advanced technology of communication method called as body to body communication in biomedical field. Human body is used as a medium of transmission of data. The use of this technology in medical monitoring systems eliminates the complexity of existing technologies that involves cables wires for transmission of data. The proposed model provides a secure and simple communication system that consists of wearable devices to measure heart …
Published in Journal of Communication Engineering & Systems · Vol. 8, Issue 1, 2018 · pp. 52–58 Read article
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Advancement and Limitations of Raman Spectroscopy: A Review
Abstract: The present review provided an overview of advances and limitations in Raman spectroscopy— a powerful analytical tool widely used across scientific disciplines. Instrumental advances, including the development of lasers, detectors, and optics, have increased the scope of Raman spectroscopy. These advances have expanded its applications in fields such as information science and biology. The integration of Raman spectroscopy with additional technologies such as microscopy and artificial intelligence further expands analytical …
Published in Research and Reviews: A Journal of Pharmaceutical Science · Vol. 15, Issue 2, 2024 · pp. 85–97 Read article
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AI-integrated Responsive Polymer Composites for Controlled Drug Delivery
Abstract: In the current biomedical engineering, it has been established that the development of smart drug delivery systems has become a paramount of relevance especially in ensuring precise, controlled and targeted therapeutic effects. This paper proposes a responsive polymer composite architecture with built-in AI, which is used to deliver drugs in a controlled manner and involves the development of advanced material design and predictive modeling based on data. Biocompatible materials and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article