- 测量理论 - 测量数据的数学处理 - 测量不确定性最小化 - 数据评估和建模中的统计方法 - 作为跨学科活动的测量 - 教育中的测量科学 - 医学成像方法、图像处理 - 生物信号测量、处理和分析 - 基于模型生物测量 -​​ 生物测量中的神经网络 - 生物医学中的遥测 - 纳米医学中的测量 - 基本物理量的测量 - 磁场和电场测量 - 几何和机械量的测量 - 光学测量方法 - 电磁兼容性 - 材料科学中的测量

Measurement Science Review covers the following topics: measurement theory, mathematical processing of measurement data, minimization of measurement uncertainty, statistical methods in data evaluation and modeling, interdisciplinary measurement activities, measurement science in education, medical imaging methods and image processing, measurement, processing, and analysis of biological signals, model-based biometrics, neural networks in biometrics, telemetry in biomedicine, measurement in nanomedicine, measurement of fundamental physical quantities, measurement of magnetic and electric fields, measurement of geometric and mechanical quantities, optical measurement methods, electromagnetic compatibility, and measurement in materials science.

测量科学评论（Measurement Science Review）涵盖以下主题：测量理论、测量数据的数学处理、测量不确定性的最小化、数据评估和建模中的统计方法、跨学科的测量活动、教育中的测量科学、医学成像方法与图像处理、生物信号的测量、处理与分析、基于模型的生物测量、生物测量中的神经网络、医学中的遥测、纳米医学中的测量、基本物理量的测量、磁场和电场的测量、几何和机械量的测量、光学测量方法、电磁兼容性以及材料科学中的测量。

Measurement Science Review

Effectiveness of the Wavelet Transform on the Surface EMG to Understand the Muscle Fatigue During Walk Muscle fatigue is the decline in ability of a muscle to create force. Electromyography (EMG) is a medical technique for measuring muscle response to nervous stimulation. During a sustained muscle contraction, the power spectrum of the EMG shifts towards lower frequencies. These effects are due to muscle fatigue. Muscle fatigue is often a result of unhealthy work practice. In this research, the effectiveness of the wavelet transform applied to the surface EMG (SEMG) signal as a means of understanding muscle fatigue during walk is presented. Power spectrum and bispectrum analysis on the EMG signal getting from right rectus femoris muscle is executed utilizing various wavelet functions (WFs). It is possible to recognize muscle fatigue appreciably with the proper choice of the WF. The outcome proves that the most momentous changes in the EMG power spectrum are symbolized by WF Daubechies45. Moreover, this research has compared bispectrum properties to the other WFs. To determine muscle fatigue during gait, Daubechies45 is used in this research to analyze the SEMG signal.

M. Hussain

Md. Mamun

Effectiveness of the Wavelet Transform on the Surface EMG to Understand the Muscle Fatigue During Walk

小波变换在步行过程中表面肌电信号分析中对肌肉疲劳理解的有效性

Abstract For years, researchers have been studying computer vision, i.e. the ability of artificial intelligence (AI) systems to perceive and interpret visual data like humans. This study is gaining increasing attention as researchers aim to develop tools that automate visual tasks and replicate human visual awareness. However, the interpretation of images is very complex due to the vast amount of multi-resolution information they contain, making the development of AI technologies for visual recognition particularly challenging. This article provides an overview of digital image processing, highlighting the main concepts and introducing key algorithms. These methods are designed to capture, process, and interpret digital images and enable the extraction of important data from real-world environments. We conduct rigorous image processing tests and compare AI-driven recognition systems with human analysis. The results show that computer vision technology significantly outperforms human observation in terms of accuracy and consistency. These results highlight the potential of computer vision to revolutionize various industries by automating complex visual tasks and offer promising future applications in areas such as healthcare, security, and manufacturing. The paper provides valuable insights into current advances in digital image processing and the role of AI in improving visual recognition capabilities, paving the way for further innovation in this area.

V Bharathi

N A Natraj

S Gopinath

R Kiruthikaa

Advanced Computer Vision Techniques for Accurate Measurement in Unmanned Mobile Robots

无人移动机器人精确测量的先进计算机视觉技术

Abstract Modern communication networks require improved signal quality and spectrum efficiency. Modern wireless communication relies heavily on the multiple input multiple output (MIMO) technology to improve spectrum efficiency and achieve faster data rates. However, the performance of MIMO systems is significantly hampered by non-linear distortions in power amplifiers (PA), especially under dynamic operating conditions. Traditional methods to reduce these distortions often lack the adaptability required for effective optimization. The proposed dynamic nonlinear distortion adaptive optimization analysis (DNDAOA) therefore introduces an adaptive approach that dynamically adjusts the pre-distortion signals using real-time feedback mechanisms. DNDAOA effectively reduces non-linear distortions and thus improves the performance of MIMO systems. Simulation results show that DNDAOA significantly increases spectrum efficiency, reduces error rates, and improves signal quality. This method is widely used in areas such as wireless telecommunications, internet of things (IoT), autonomous vehicles, and smart infrastructure, driving advances in connectivity, reliability, and data integrity.

R Jayarani

N Narmadhai

Enhancing Wireless Communication Efficiency Using Dynamic Nonlinear Distortion Adaptive Optimization Analysis

利用动态非线性失真自适应优化分析提升无线通信效率

Abstract The identification of diseases caused by changes in ion concentration is quite difficult and yet plays a decisive role in the success of clinical care, diagnosis and treatment. The clinically proven approach to diagnosing electrolyte concentration imbalance is blood tests. There is a need to provide a non-invasive diagnostic method that is not of a temporary nature. Bio-signals such as the electrocardiogram (ECG) can be used to meet this demand and become diagnostic tools that facilitate home monitoring of electrolyte concentration on a permanent basis. This study investigates the feasibility and efficiency of methods based on machine learning (ML) and ECG recordings in monitoring critical levels of existing potassium and calcium concentration. Morphological, frequency and frequency-time domain features were extracted to automatically estimate calcium and potassium levels. Furthermore, the potential of estimates based on modeling approaches will be demonstrated to gain insights into relevant clinical findings and improve the performance of monitoring approaches. Using the hold-out validation method, the best results in terms of mean square error ( MSE ) and R for estimating the calcium value are 0.7157 and 0.57347, using fuzzy inference systems (FIS). Here, R represents the proportion of the variance in the calcium value that is explained by the model.

Sebahattin Babur

Sanam Moghaddamnia

Mehmet Recep Bozkurt

Estimation of Blood Calcium and Potassium Values from ECG Records

从心电图记录估算血钙和血钾值

Abstract The microchannel plate (MCP) is an electron multiplier with millions of micro through-holes that must withstand strong vibrations and enormous shocks in spaceborne detectors. To ensure the reliability and robustness of the MCP in space applications, we proposed an equivalent mechanical model of the MCP to investigate its mechanical properties, since the direct creation of the finite element model using the finite element method (FEM) is not feasible. Then, we developed a test system to verify the effectiveness of the equivalent mechanical model. The results show that the error of harmonic response analysis and the test result is less than 10 %, which is acceptable. Finally, we conducted parametric studies of the MCPs and obtained the equivalent mechanical model of the MCPs with different geometric parameters. This study will help researchers to optimize the MCP for aerospace-grade detectors.

Shengdan Zhang

Yonglin Bai

Weiwei Cao

Junjun Qin

Jiarui Gao

Le Chang

Beihong Liu

Zexun Hu

Zhujun Chu

Xiaoqing Cong

Yongwei Dong

Zhigang Wang

Equivalent Mechanical Model of a Microchannel Plate

微通道板的等效力学模型

Abstract The aim of this study is to determine the metric stability of the one-month handgrip test (HGT) in order to define the contractile characteristics of the biological variation of maximal isometric strength ( F max ) and maximal isometric rate of force development ( RFD max ) of the handgrip in two different testing regimes (classic and impulse). The study was conducted with a total of 16 participants (11 men and 5 women). Testing was performed using an isometric handgrip probe with a standardized test protocol and equipment sports medical solutions (SMS). The results of F max showed a low relative standard error of the mean ( RS = 1.33 %), a high value of inter-class correlation ( ICC = 0.996), and no statistically significant change in trend ( p &gt; 0.05) during the testing period. Therefore, can conclude that the HGT procedure in classic mode can be used as a stable parameter in a human subject sample. However, the RFD max results showed a low RS (2.13 %) and a high ICC value (0.996), but a statistically significant change of trend ( p &lt; 0.05) during the measurement period. The regression constant ( RCO ) trend was 42.629 N/s, which can be attributed to learning or to the adaptive effects of the test procedure, which triggered similar adaptation processes as the training. In general, it can be concluded that the handgrip can be used to sensitively measure the effects of different long-term health improvements, or the effects of different medical/health exercises, rehabilitation programs, effects of medication applications, or dietary supplements for F max . However, further research should be conducted for the RFD max considering the metric stability parameters.

Nevena Vukadinović

Marko Šmrkić

Života Stefanović

Vladimir Ilić

David Nikolić

Igor Zlatović

Milivoj Dopsaj

Metric Stability of One Month Handgrip Maximal and Explosive Isometric Strength Measured by Classic and Impulse Contractions

经典和脉冲收缩测量一个月握力最大和爆发等长力量的指标稳定性

Abbreviation	Meas. Sci. Rev.
Journal Impact	1.03
Quartiles(Global)	INSTRUMENTS & INSTRUMENTATION(Q4)

ISSN	1335-8871
h-index	32

Publication Information	Publisher: Slovak Academy of Sciences - Inst. Measurement Science，Publishing cycle: Bimonthly，Journal Type: journal，Open Access Journals: Yes
Basic data	Year of publication: 2008，Proportion of original research papers: 97.30%，Self Citation Rate:20.00%， Gold OA Rate: 100.00%
Journal Fees	$Details
Average review cycle	网友分享经验：平均4.0个月
Average recruitment ratio	网友分享经验：容易

Measurement Science Review

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Effectiveness of the Wavelet Transform on the Surface EMG to Understand the Muscle Fatigue During Walk

Advanced Computer Vision Techniques for Accurate Measurement in Unmanned Mobile Robots

Enhancing Wireless Communication Efficiency Using Dynamic Nonlinear Distortion Adaptive Optimization Analysis

Estimation of Blood Calcium and Potassium Values from ECG Records

Equivalent Mechanical Model of a Microchannel Plate

Advanced Computer Vision Techniques for Accurate Measurement in Unmanned Mobile Robots

Enhancing Wireless Communication Efficiency Using Dynamic Nonlinear Distortion Adaptive Optimization Analysis

Estimation of Blood Calcium and Potassium Values from ECG Records

Equivalent Mechanical Model of a Microchannel Plate

Metric Stability of One Month Handgrip Maximal and Explosive Isometric Strength Measured by Classic and Impulse Contractions