25 papers · ranked by Valyu relevance
Amin Gasmi
Feelings and emotions are significant determinants of the behavior of an individual. Human emotions can be established and recognized through several approaches, such as facial images, gesture, neuroimaging methods, and psychological signals [1]. The human body produces many physiological signals. These physiological…
Radek Martinek, Martina Ladrova, Michaela Sidikova, Rene Jaros + 4 more
'Khosrow Behbehani' 'Radana Kahankova' 'Aleksandra Kawala-Sterniuk' 'Paweł Pławiak'] Analysis of biomedical signals is a very challenging task involving implementation of various advanced signal processing methods. This area is rapidly developing. This paper is a Part III paper, where the most popular and efficient…
Ignacio Sanchez-Gendriz
Ecoacoustics is a research field that has attracted attention of researchers from areas as diverse as ecology, biology, engineering, and human sciences, to cite a few. Ecoacoustics studies the sounds that emanates from the environments, by gaining insights of landscape dynamics from acoustic patterns and…
Lukas P. A. Arts, Egon. L. van den Broek
The spectral analysis of signals is currently either dominated by the speed-accuracy trade-off or ignores a signal’s often non-stationary character. Here we introduce an open-source algorithm to calculate the fast continuous wavelet transform (fCWT). The parallel environment of fCWT separates scale-independent and…
Sulaiman Aburakhia, Abdallah Shami, George K. Karagiannidis
—Recent advancements in sensing, measurement, and computing technologies have significantly expanded the potential for signal-based applications, leveraging the synergy between signal processing and Machine Learning (ML) to improve both performance and reliability. This fusion represents a critical point in the…
Radan Ganchev
The widespread use of automated voice assistants along with other recent technological developments have increased the demand for applications that process audio signals and human voice in particular. Voice recognition tasks are typically performed using artificial intelligence and machine learning models. Even though…
Sergey Edward Lyshevski, Richard Buckley, Christopher Feuerstein, Pedro Silva Girão
'Pedro Silva Girão'] This paper investigates evaluation methodologies and machine reasoning schemes to analyze dynamic electromagnetic spectrum. We research practical and scalable classification of radio frequency signals across high frequency, very high frequency, ultra high frequency and super high frequency bands.…
Zulfidin Khodzhaev
| Introduction | | 1 | | --- | --- | --- | | 1 | Spectrogram of finger snapping with 44100 Hz sam | | | pling rate | | 3 | | 1.1 Frequency of the signal per time. | 3 | | | 1.2 Power Spectral Density | 3 | | | 1.3 Spectrogram | 3 | | | 2 | Spectrogram of finger snapping with 96000 Hz sam | | | pling rate | | 3 | | 3 |…
Omkar Deshpande, Kharanshu Solanki, Sree Pujitha Suribhatla, Sanya Zaveri + 1 more
'Sanya Zaveri' 'Luv Ghodasara'] Since the evolution of digital computers, the storage of data has always been in terms of discrete bits that can store values of either 1 or 0. Hence, all computer programs (such as MATLAB), convert any input continuous signal into a discrete dataset. Applying this to oscillating…
Andrew J Harvie, Surendra K Yadav, John C de Mello
We report a sensitive, fixed-wavelength, lock-in-based optical detector built from a light-emitting diode, two colour filters, a photodetector, a small number of discrete analogue components, and a low-cost microcontroller development board. We describe the construction, operating principle, use and performance of the…
Radek Martinek, Martina Ladrova, Michaela Sidikova, Rene Jaros + 4 more
'Khosrow Behbehani' 'Radana Kahankova' 'Aleksandra Kawala-Sterniuk' 'Paweł Pławiak'] Advanced signal processing methods are one of the fastest developing scientific and technical areas of biomedical engineering with increasing usage in current clinical practice. This paper presents an extensive literature review of the…
Chen Ming, Stephanie Haro, Andrea Megela Simmons, James A. Simmons
Computational models of animal biosonar seek to identify critical aspects of echo processing responsible for the superior, real-time performance of echolocating bats and dolphins in target tracking and clutter rejection. The Spectrogram Correlation and Transformation (SCAT) model replicates aspects of biosonar imaging…
Michael X Cohen
The number of simultaneously recorded electrodes in neuroscience is steadily increasing, providing new opportunities for understanding brain function, but also new challenges for appropriately dealing with the increase in dimensionality. Multivariate source-separation analysis methods have been particularly effective…
Hamid Behjat, Carl-Fredrik Westin, Iman Aganj
Conventionally, as a preprocessing step, functional MRI (fMRI) data are spatially smoothed before further analysis, be it for activation mapping on task-based fMRI or functional connectivity analysis on resting-state fMRI data. When images are smoothed volumetrically, however, isotropic Gaussian kernels are generally…
Samuel Akwei-Sekyere, Silvia Comani
The distortion of biomedical signals by powerline noise from recording biomedical devices has the potential to reduce the quality and convolute the interpretations of the data. Usually, powerline noise in biomedical recordings are extinguished via band-stop filters. However, due to the instability of biomedical…
Ting-Hua Yi, Hong-Nan Li, Xiao-Yan Zhao
In structural vibration tests, one of the main factors which disturb the reliability and accuracy of the results are the noise signals encountered. To overcome this deficiency, this paper presents a discrete wavelet transform (DWT) approach to denoise the measured signals. The denoising performance of DWT is discussed…
Authors not listed
The global drive towards net-zero has accelerated the adoption of carbon fibre reinforced polymers (CFRP) for lightweight structures in various sectors such as aerospace, automotive, energy and biomedical. Mechanical machining of CFRP is often necessary to meet dimensional or assembly-related requirements. However…
Chunhui Hao, Yuan Li
Existing speech recognition systems are only for mainstream audio types; there is little research on language types; the system is subject to relatively large restrictions; and the recognition rate is not high. Therefore, how to use an efficient classifier to make a speech recognition system with a high recognition…
Authors not listed
Acoustic measurements of batteries are known to be correlated to their state-of-charge, creating opportunities for state estimation that do not rely on electrical signals. State estimators are typically parametric models fitted from data, often from the broad toolbox of machine learning. Such models can be easily…
Griffin Chure, Jonas Cremer
High-Performance Liquid Chromatography (HPLC) and Gas Chromatography are analytical techniques which allow for the quantitative characterization of the chemical components of mixtures . Technological advancements in sample preparation and mechanical automation have allowed HPLC to become a high-throughput tool which…
Michael X Cohen
Large-scale synchronous neural activity produces electrical fields that can be measured by electrodes outside the head, and volume conduction ensures that neural sources can be measured by many electrodes. However, most data analyses in M/EEG research are univariate, meaning each electrode is considered as a separate…
Madeleine Leger, Jiangfeng Guo, Bryce MacMillan, Hatem Titi + 3 more
We present a new methodology for real-time observation of mechanochemical transformations, based on a magnetic resonance method in which T1-T2 relaxation time correlation maps are used to track the formation of the popular metal-organic framework (MOF) materials Zn-MOF-74 and ZIF-8. This two-dimensional (2D) relaxation…
Authors not listed
Proton nuclear magnetic resonance (1H NMR) spectroscopy offers rapid quantification of saturated (SFA), monounsaturated (MUFA), and polyunsaturated (PUFA) fatty acids in oils. While high-field NMR has been widely applied, its high operational costs limit accessibility. In contrast, benchtop NMR provides a more…
Authors not listed
Nuclear magnetic resonance spectroscopy (NMR) is one of the most potent analytical chemistry methods, providing a unique insight into molecular structures. Its non-invasiveness makes it a perfect tool for monitoring chemical reactions and determining their products and kinetics. Typically, the reactions are monitored…
Authors not listed
Nuclear magnetic resonance spectroscopy (NMR) plays a key role for the analysis of a plethora of molecules, including natural products and drug-like organic molecules. For such cases 1H NMR spectra have proven imperative because of their high sensitivity. However, these spectra are complicated by complex multiplet…