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Background: Computationally efficient spike recognition methods are required for real-time analysis of extracellular neural recordings. The enteric nervous system (ENS) is important to human health but less well-understood with few appropriate spike recognition algorithms due to large waveform variability.
New Method: Here we present a method based on dynamic time warping (DTW) with high tolerance to variability in time and magnitude. Adaptive temporal gridding for "fastDTW" in similarity calculation significantly reduces the computational cost. The automated threshold selection allows for real-time classification for extracellular recordings.
Results: Our method is first evaluated on synthesized data at different noise levels, improving both classification accuracy and computational complexity over the conventional cross-correlation based template-matching method (CCTM) and PCA+k-means clustering without time warping. Our method is then applied to analyze the mouse enteric neural recording with mechanical and chemical stimuli. Successful classification of biphasic and monophasic spikes is achieved even when the spike variability is larger than millisecond in width and millivolt in magnitude.
Comparison With Existing Method(s): In comparison with conventional template matching and clustering methods, the fastDTW method is computationally efficient with high tolerance to waveform variability.
Conclusions: We have developed an adaptive fastDTW algorithm for real-time spike classification of ENS recording with large waveform variability against colony motility, ambient changes and cellular heterogeneity.
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http://dx.doi.org/10.1016/j.jneumeth.2015.12.006 | DOI Listing |
Heliyon
December 2024
North China University of Water Resources and Electric Power, Zhengzhou, Henan, 450011, PR China.
In the domain of stock price prediction, the intricate interdependencies within multivariate time series data present significant challenges for accurate forecasting. This paper introduces a groundbreaking hybrid preprocessing technique to tackle this issue. By leveraging the Empirical Wavelet Transform (EWT), we adeptly extract both low-frequency and high-frequency components from the time series.
View Article and Find Full Text PDFPhys Rev Lett
December 2024
Institute of Natural Sciences, School of Mathematical Sciences, MOE-LSC, Shanghai Jiao Tong University, Shanghai 200240, P. R. China.
We present a novel new way-called Schrödingerization-to simulate general (quantum and nonquantum) systems of linear ordinary and partial differential equations (PDEs) via quantum simulation. We introduce a new transform, referred to as the warped phase transformation, where any linear-including nonautonamous-system of ordinary or partial differential equation can be recast into a system of Schrödinger's equations, in real time, in a straightforward way. This approach is not only applicable to PDEs for classical problems but is also useful for quantum problems, including the preparation of quantum ground states and Gibbs thermal states, the simulation of quantum states in random media in the semiclassical limit, simulation of Schrödinger's equation in a bounded domain with artificial boundary conditions, and other non-Hermitian physics.
View Article and Find Full Text PDFFront Public Health
December 2024
Department of Architectural Engineering, Dankook University, Yongin-si, Gyeonggi-do, Republic of Korea.
This study presents a novel approach to quantitatively assess the impact of flooring materials on walkability using Inertial Measurement Unit (IMU) sensors and Dynamic Time Warping (DTW) algorithm. Four common pavement materials (wood, asphalt, concrete block, and cement) were evaluated across five age groups (20-30, 30-40, 40-50, 50-60, and over 60 years) with 80 participants walking 1,200 m on each surface. IMU sensors attached to the lumbar region recorded acceleration and gyroscope data, which were then analyzed using DTW to quantify gait stability.
View Article and Find Full Text PDFJ Biomech
December 2024
Intelligent Systems for Medicine Laboratory, The University of Western Australia, Perth, Western Australia, Australia.
A search in Scopus within "Article title, Abstract, Keywords" unveils 2,444 documents focused on the biomechanics of Abdominal Aortic Aneurysm (AAA), mostly on AAA wall stress. Only 24 documents investigated AAA kinematics, an important topic that could potentially offer significant insights into the biomechanics of AAA. In this paper, we present an image-based approach for patient-specific, in vivo, and non-invasive AAA kinematic analysis using patient's time-resolved 3D computed tomography angiography (4D-CTA) images, with an objective to measure wall displacement and strain during the cardiac cycle.
View Article and Find Full Text PDFWater Res X
January 2025
AIaqua S.r.l., Via Volta 13/A, Bolzano, Italy.
The continuous increase of water distribution networks (WDNs) in size and complexity poses significant management challenges, including a high risk of failures. Due to the intrinsic interconnected feature of water flow, including losses, this study proposes a methodology based on graph correlation and multilayer network analysis for leak detection and localization in WDNs with multiple components (infrastructure, control devices, hydraulic sensors). The detection process involves correlating monitored data to create a temporal graph and classify vertices.
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