MEASUREMENT SCIENCE REVIEW            Volume 22      

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No. 1

No. 2 No. 3 No. 4 No. 5 No. 6  

       Measurement of Physical Quantities

    Pages

 
1-10

Piotr Kuwałek, Grzegorz Wiczynski:

Problem of Total Harmonic Distortion Measurement Performed by Smart Energy Meters

Abstract: 

Currently, electricity is treated as commodity that should be delivered from a distributor to a consumer with a certain quality. The power quality is defined by the set of measures with specific limit values. One of the basic measures is the Total Harmonic Distortion (THD), which allows to assess the level of the voltage distortion. The measurement of THD ratio should be carried out in accordance with the normative specification. It is assumed that this requirement is met by class A power quality analyzers. Currently, measures are taken to monitor power quality in a large number of measurement points with the use of smart energy meters that are part of the Advanced Metering Infrastructure (AMI). The paper presents the problem of THD ratio measurement by AMI meters if voltage fluctuations occur. In such situation, inconsistency in measurement results of AMI meters and class A power quality analyzers occurs. The problem is presented on the basis of laboratory study results in which disturbances in power grid are recreated.

 

11-16

Henryk Banach:

A Measurement Method of Determining the Power Supply Parameters for the Optimal Operation of a Synchronous Motor

Abstract: 

The article presents a measurement method for determining the power supply parameters for the optimal operation of a synchronous motor, i.e. operation with minimal losses in the entire load range. The measurement strategy is based on the search for the minimum sum of the power supplied to the excitation circuit and the stator circuit for the assumed load torque values. The process of searching for the minimum sum of power can be significantly shortened and simplified by using a network parameter meter. The research confirmed the usefulness of the proposed method for determining the optimal operation parameters of a synchronous motor. The tested motor was a machine with a cylindrical rotor, but the developed method will also be applicable to synchronous machines with salient pole rotors.

 

17-31

Man-lu Liu, Rui Lin, Jian-wen Huo, Li-guo Tan, Qing Ling, Eugene Yuryevich Zybin:

Design of Distributed Fusion Predictor and Filter without Feedback for Nonlinear System with Correlated Noises and Random Parameter Matrices

Abstract: 

This work presents distributed predictor and filter without feedback for nonlinear stochastic uncertain system with correlated noises. Firstly, for the problem that the process noise and measurement noise are correlated, the two-step prediction theorem based on projection theorem is used to replace the one-step prediction theorem, and the two-step prediction value of a single sensor is obtained. Secondly, the two-step prediction value of each sensor state is used as the measurement information to modify the distributed fusion predictor to obtain the distributed fusion prediction value. Then, according to the projection theorem, the prediction value of distributed fusion is used as measurement information to modify the filtering value of distributed fusion. Finally, the Cubature Kalman filter (CKF) algorithm is used to implement the algorithm proposed in this paper. By comparison with existing methods, the algorithm proposed in this paper solves the problem that existing methods cannot handle state estimation and prediction problems for nonlinear multi-sensor stochastic uncertain systems with correlated noises.

 

32-43

Zhong Mei, Yurii Kuts, Orest Kochan, Iuliia Lysenko, Oleksandr Levchenko, Halyna Vlakh-Vyhrynovska:

Using Signal Phase in Computerized Systems of Non-destructive Testing

Abstract: 

Phase methods of measuring physical quantities and phase measuring equipment are widely used in various fields of science and technology. The article proposes a signal processing methodology based on a combination of the discrete Hilbert transform (DHT) and deterministic, as well as statistical methods of phase measurement. This methodology makes it possible to more fully use the information resource of the measuring signal phase in a wide range of the signal-to-noise ratio. It can be used both in computerized measurement and testing systems, as well as in the processing of measurement data. The benefits of the DHT are considered. The possibility of using statistics of directional data for phase measurements is shown. Circular statistics, such as the mean ring value, circular variance and the resulting vector length, were proposed for use in the phase measurements. Some examples of the use of this methodology in measurements and non-destructive testing are given.

 

44-49

Eduard A. I. Aidu, Vladimir G. Trunov:

Vectorcardiographic Ventricular Gradient with Constituents, and Myocardial Action Potential Parameter Distribution

Abstract: 

Theoretical grounds of integral vectors of ventricular depolarization and repolarization and their sum, i.e., the spatial ventricular gradient, have been studied. A systematic description and biophysical interpretation of these parameters are presented based on the distribution of cardiomyocyte action potential parameters in the inhomogeneous bidomain model of the myocardium. Recent medical studies have shown high efficiency and predictive value of the ventricular gradient, its constituents and related parameters, such as the angle between the constituents, the acceleration of repolarization, etc. Simple examples for a myocardial strip clarify the relationship between the action potential parameters and the resulting ventricular gradient. An explanation with graphic illustration is given for the very informative decartogram of repolarization acceleration. The results obtained here are useful in the modeling of vectorcardiograms for various pathological conditions of the heart ventricles and for various characteristics of the cardiomyocyte action potential, which determine its shape.

 

50-57

Pavol Omaník, Katarína Kozlíková, Natália Daumová, Veronika Schmidtová, Igor Béder:

The Role of Anthropologic Measurements in Pectus Carinatum Brace Treatment Evaluation

Abstract: 

Objectives: Brace treatment in children with pectus carinatum has become the method of choice during the last decade. The authors evaluate the role of anthropometric measurements in diagnostic and treatment processes.

Methods: A prospective study, analysing a compressive brace treatment for pectus carinatum, performed between January 2018 and September 2020.  Demographic data, anthropometric dimensions and indexes of the chest, data connected to an orthosis usage, as well as ongoing treatment outcomes were analysed.

Results: Forty-seven consecutive patients aged between 10 to 18 years with pectus carinatum were prescribed a compressive brace. Thirty-nine of them (83 %) reached clinically positive results while wearing the orthosis for 6 ± 3 months. An improvement in the sagittal chest diameter was 0.5 cm – 2.8 cm (mean 1.0 cm ± 0.5 cm) and an improvement of the Thoracic Index was 0.8 % – 25.1 % (6.4 % ± 4.%) by using the brace on average for (6 ± 2) hours a day.

Conclusion: Clinical anthropometric measurements can evaluate the dimensions of chest wall and treatment progress in patients with pectus carinatum precisely and thus replace the need for more complex examinations requiring X-rays.

 

 

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No. 2  

    

58-64

Liping Tian, Lingbin Shen, Yanhua Xue, Lin Chen, Lili Li, Ping Chen, Jinshou Tian, Wei Zhao:

Theoretical and Experimental Research on Spatial Performances of the Long-slit Streak Tube

Abstract:  

The streak tubes are widely used in National Ignition Facility (NIF), Inertial Confinement Fusion (ICF), and streak tube imaging lidar (STIL) as radiation or imaging detectors. The spatial resolution and effective photocathode area of the streak tube are strongly dependent on its operating and geometry parameters (electron optical structure and applied voltage). Studies about this dependence do not cover the full range of the parameters. In this paper, 3-D models are developed in Computer Simulation Technology Particle Studio (CST-PS) to comprehensively calculate the spatial resolution for various parameters. Monte Carlo Sampling method (M-C method) and spatial modulation transfer function method (SMTF) are employed in our simulation. Simulated results of the optimized spatial resolution are validated by the experimental data. Finally, the radii of the photocathode (Rc) and phosphor screen (Rs) are optimized. Geometry parameters of Rc=60 mm and Rs=80 mm are proposed to optimize the streak tube performances. Simulation and experimental results show that the spatial resolution and effective photocathode area of this streak tube are expected to reach 16 lp/mm and 30 mm-length while the voltage between cathode and grid (Ucg) is 150 V.

 

65-72

Abbas Fadhil Abbas, Adawiya Ali Hamzah:

Studying the Thermal Influence on the Vibration of Rotating Blades

Abstract:  

Computing the vibrating characteristics of any machine or structure is a necessary process that should be performed by the mechanical engineers that work in engineering design field to avoid the collapse under different kinds of applied loads. One of these kinds of structures are the rotating blades, whereas this part is considered as an essential element in many rotating systems that are used in different fields of engineering, e.g., turbomachinery, turbofan, helicopters, etc. One of the biggest disadvantages that is realized in rotating blades is failure due to vibrations and unbalance. It is possible that vibrations significantly reduce the performance of rotating blades compared to standard design conditions. If these rotating blades continue to operate under these circumstances for sufficient time, then the status of these systems will be unstable. Finally, this will lead to collapse of the rotating blades. In this work, a new code was created from scratch, based on the finite element method, to determine the vibrational characteristics of the rotating blades, taking into consideration the effect of rotating speed and temperatures. The compound influence of thermal gradients and rotating speed on the vibrational response (frequencies) for different configurations of blade was studied deeply.

 

73-79

Chunzhi Wang, Hongzhe Jiao, Lukyan Anatychuk, Nataliya Pasyechnikova , Volodymyr Naumenko, Oleg Zadorozhnyy, Lyudmyla Vikhor, Roman Kobylianskyi, Roman Fedoriv, Orest Kochan:

Development of a Temperature and Heat Flux Measurement System Based on Microcontroller and its Application in Ophthalmology

Abstract:  

The paper describes the design and technical parameters of a medical thermoelectric device developed for diagnosing and monitoring the ophthalmic diseases. The main elements of the device are a specially designed thermoelectric heat flux sensor and a thermocouple temperature sensor connected to a data acquisition unit. The sensor is a thermoelectric micro-module that converts the heat flux into an electric voltage, which is recorded by the measuring channel of the data acquisition unit. The device allows high-precision measurements of both heat flux and temperature from the ocular surface. The paper contains examples of clinical piloting of the device.

 

80-83

Peter Andris, Tomáš Dermek, Daniel Gogola, Jiří Přibil, Ivan Frollo:

Analysis of NMR Signal for Static Magnetic Field Standard

Abstract: 

This article describes the analysis of the NMR (Nuclear Magnetic Resonance) stabilizer signal. Magnetic field of the standard is created using an electromagnet. Sufficiently high stability of the magnetic field is achieved with the help of a stabilizer with an NMR probe. The NMR phenomenon makes possible very accurate measurements of the static magnetic field, but the resulting stability depends also on supporting electronics. An analysis has been done and tolerances of the measured quantities have been estimated. The calculated tolerances indicate the needed features of the material. First the probe excites the FID (Free Induction Decay) signal in the water sample and acquires the signal answer. It is Fourier transformed and its spectrum is investigated. The actual magnetic field corresponds to the strongest frequency sample. It is utilized for the magnetic field strength correction and stabilization of it. The article brings many equations for such calculation.

 

84-91

Yong-Sik Kim, Nicholas G. Dagalakis, Jeremy Marvel, Geraldine Cheok:

Design and Testing of Wireless Motion Gauges for Two Collaborative Robot Arms

Abstract: 

Most existing robot performance evaluation methods focus on single robotic arms performing independent motion tasks. In this paper, a motion gauge is proposed to evaluate the symmetrical coordinated-motion performance between two robotic arms. For this evaluation, the proposed device monitors the relative distance between the two robotic arms in real-time, which is used to evaluate the coordinated-motion errors with respect to accuracy, and repeatability between the two arms. The proposed metrology device is composed of two linear displacement sensors sliding on a linear rail, two ball-and-socket magnetic couplers for mounting to robotic arms, and a wireless communication module for data transmission. For validation, the proposed system monitored the two robotic arms programmed to simulate symmetrical coordinated motions.

 

92-99

Bo Yu, Hanlin Kou, Zhaoyao Shi, Yanqiang Sun:

A Virtual Measurement Method of the Transmission Error Based on Point Clouds of the Gear

Abstract: 

As the most widely used gear measuring instrument, the gear measuring center can measure the individual deviations of a gear tooth flank other than the comprehensive deviations of the gear. However, gear transmission error is an important transmission performance indicator in the gear meshing process. It is an important trend of gear measuring to obtain the transmission error from individual deviations. In this study, a calculation method of gear transmission error is proposed based on the point clouds of the gear obtained by optical sensors. According to the gear meshing principle, a method is introduced to determine the contact status between the tooth flanks formed by the point clouds. According to this introduced method, the single tooth pair meshing process and the meshing process of multiple tooth pairs are analyzed to determine the gear transmission error curve. The comparison results of tooth contact analysis and gear measurement experiments verify the proposed virtual measurement method.

 

   
 

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No. 3  

 

100-106

 José Dias Pereira, Mário Alves:

An Integrated Testing Solution for Piezoelectric Sensors and Energy Harvesting

Abstract: 

With the fast growth of wireless communications between nodes and sensor units and the increase of devices installed in remote places, and the development of IIoT applications, new requirements for power energy supply are needed to assure device functionality and data communication capabilities during extended periods of time. For these applications, energy harvesting takes place as a good solution to increase the autonomy of remote measuring solutions, since the usage of conventional power supply solutions has clear limitations in terms of equipment access and increased maintenance costs. In this context, regenerative energy sources such as thermoelectric, magnetic and piezoelectric based, as well as renewable energy sources, such as photovoltaic and wind based, among others, make the development of different powering solutions for remote sensing units possible. The main purpose of this paper is to present a flexible testing platform to characterize piezoelectric devices and to evaluate their performance in terms of harvesting energy. The power harvesting solutions are focused on converting the energy from mechanical vibrations, provided by different types of equipment and mechanical structures, to electrical energy. This study is carried out taking into account the power supply capabilities of piezoelectric devices as a function of the amplitude, frequency and spectral contents of the vibration stimulus. Several experimental results using, as an example, a specific piezoelectric module, are included in the paper.

 

107-111

Wei-Yu Chen, Yu-Reng Tsao, Jin-Yi Lai, Ching-Jung Hung, Yu-Cheng Liu, Cheng-Yang Liu:

Real-Time Instance Segmentation of Metal Screw Defects Based on Deep Learning Approach

Abstract: 

In general, manual methods are often used to inspect defects in the production of metal screws. As deep learning shines in the field of visual detection, this study employs the You Only Look At CoefficienTs (YOLACT) algorithm to detect the surface defects of the metal screw heads. The raw images with different defects are collected by an automated microscopic camera scanning system to build the training and validation datasets. The experimental results demonstrate that the trained YOLACT is sufficient to achieve a mean average accuracy of 92.8 % with low missing and false rates. The processing speed of the trained YOLACT reaches 30 frames per second. Compared with other segmentation methods, the proposed model provides excellent performance in both segmentation and detection accuracy. Our efficient deep learning-based system may support the advancement of non-contact defect assessment methods for quality control of the screw manufacture.

 

112-121

Chifaa Aber, Azzedine Hamid, Mokhtar Elchikh, Tierry Lebey:

Eddy Current Microsensor and RBF Neural Networks for Detection and Characterization of Small Surface Defects

Abstract: 

The growing complexity of industrial processes and manufactured parts, the growing need for safety in service and the desire to optimize the life of parts, require the implementation of increasingly complex quality assessments. Among the various anomalies to consider, sub-millimeter surface defects must be the subject of particular care. These defects are extremely dangerous as they are often the starting point for larger defects such as fatigue cracks, which can lead to the destruction of the parts.

Penetrant testing is now widely used for this type of defect, due to its good performance. Nevertheless, it should be abandoned eventually due to environmental standards. Among the possible alternatives, the use of eddy currents (EC) for conductive materials is a reliable, fast, and inexpensive alternative.

The study concerns the design and modeling of eddy current probe structures comprising micro-sensors for non-destructive testing. The moving band finite element method is implemented for this purpose to take into account the movement of the sensor, experimental validations were conducted on a nickel-based alloy specimen. The real and imaginary parts of the impedance at every position of the sensor computed by experiments and simulations were in good agreement. The crack detection quality was quantified and the geometric characteristics of the defects were estimated using RBF NN (Radial Basis Function Neural Networks) that were designed and implemented on the acquired signals.

 

122-135

Hao Yang, Yuwen Fu, Jiansheng Yang:

Review of Measurement Techniques of Hydrocarbon Flame Equivalence Ratio and Applications of Machine Learning

Abstract: 

Flame combustion diagnostics is a technique that uses different methods to diagnose the flame combustion process and study its physical and chemical basis. As one of the most important parameters of the combustion process, the flame equivalence ratio has a significant influence on the entire flame combustion, especially on the combustion efficiency and the emission of pollutants. Therefore, the measurement of the flame equivalence ratio has a huge impact on efficient combustion and environment protection. In view of this, several effective measuring methods were proposed, which were based on the different characteristics of flames radicals such as spectral properties. With the rapid growth of machine learning, more and more scholars applied it in the combustion diagnostics due to the excellent ability to fit parameters. This paper presents a review of various measuring techniques of hydrocarbon flame equivalent ratio and the applications of machine learning in combustion diagnostics, finally making a brief comparison between different measuring methods.

 

136-142

Patrik Šarga, Alena Galajdová, Marek Vagaš, František Menda:

Complex Analysis of the Necessary Geometric Parameters of the Tested Component in the Ring-Core Evaluation Process

Abstract:

Residual stress measurement in different sorts of mechanical and mechatronic objects has become an important part of the designing process and following maintenance. Therefore, a sufficient experimental method could significantly increase the accuracy and reliability of the evaluation process. Ring-Core method is a well-known semi-destructive method, yet it is still not standardized. This work tries to improve the evaluation process of the Ring-Core method by analyzing the influence of the necessary geometric parameters of the investigated object. Subsequently, residual stress computation accuracy is increased by proposed recommendations.

 

143-151

Shanshan Yu , Przystupa Krzysztof, Lingyu Yan, Volodymyr Maksymovych, Roman Stakhiv, Andrii Malohlovets, Orest Kochan:

Development of Modified Blum-Blum-Shub Pseudorandom Sequence Generator and its Use in Education

Abstract:

In information security systems, the algorithm of the Blum-Blum-Shub (BBS) generator, which is based on the use of a one-way function and is a cryptographically secure pseudorandom number generator, became widespread. In this paper, the problem of the analysis of modified algorithms of the BBS generator operation is considered to improve their statistical characteristics, namely, the sequence repetition period. It has been established that in order to improve the characteristics of the classic BBS algorithm, it is necessary to systematize approaches to change the recurrent equation itself, the relationship between the current and the previous members of the sequence. For this purpose, a generalized unified model of the modification of the classical BBS algorithm is derived. The repetition period with computational complexity were analyzed for classical algorithm and 80 proposed modifications. A gain in statistical characteristics is improved with slight increase in the required computing power of the system. The proposed modified BBS pseudorandom sequence generator can be used in training of students when teaching cryptographic stability of information security systems. The study of this generator combines the knowledge of students acquired in both digital electronics and mathematics.

 

   
 

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No. 4  

 

152-159

Martin Grötschel, Harald Hanche-Olsen, Helge Holden, Michael P. Krystek:

On Angular Measures in Axiomatic Euclidean Planar Geometry Devices

Abstract:

We address the issue of angular measure, which is a contested issue for the International System of Units (SI). We provide a mathematically rigorous and axiomatic presentation of angular measure that leads to the traditional way of measuring a plane angle subtended by a circular arc as the length of the arc divided by the radius of the arc, a scalar quantity. We distinguish between the angular magnitude, defined in terms of congruence classes of angles, and the (numerical) angular measure that can be assigned to each congruence class in such a way that, e.g., the right angle has the numerical value π/2. We argue that angles are intrinsically different from lengths, as there are angles of special significance (such as the right angle, or the straight angle), while there is no distinguished length in Euclidean geometry. This is further underlined by the observation that, while units such as the metre and kilogram have been refined over time due to advances in metrology, no such refinement of the radian is conceivable. It is a mathematically defined unit, set in stone for eternity. We conclude thatangular measures are numbers, and the current definition in SI should remain unaltered.

 

160-169

Bayu Utomo, Nanang Kusnandar, Himma Firdaus, Intan Paramudita, Iput Kasiyanto, Qudsiyyatul Lailiyah, Wahyudin P. Syam:

Comparison of GUM and Monte Carlo Methods for Measurement Uncertainty Estimation of the Energy Performance Measurements of Gas Stoves

Abstract:

The paper presents the comparison of uncertainty measurement estimations of the energy performances of gas stoves. The Guide to the Expression of Uncertainty in Measurement (GUM) framework and two Monte Carlo Simulation (MCM) approaches: ordinary and adaptive MCM were applied for the energy performance uncertainty: thermal energy and efficiency measurement uncertainties. The validation of the two MCMs is performed by comparing the MCM estimations to the GUM estimations for the thermal energy and efficiency measurement results. A test method designed in Indonesia National Standard SNI 7368:2011 was employed for the thermal energy and efficiency determinations. The results of the GUM and two MCM methods are in good agreement for the estimation of the thermal energy value. Significant differences of the uncertainty estimations for the thermal energy and efficiency results are observed for both GUM and MCM methods. Both the ordinary and adaptive MCM estimations give larger coverage interval compared to the GUM method. The adaptive MCM can give similar estimations with a much lower number of iterations compared to the ordinary MCM.  From the estimation difference between the GUM and MCM methods, suggestions are needed for the improvement in measurement models for thermal energy and efficiency of the standard.

 

170-176

Marius Saunoris, Žilvinas Nakutis, Mindaugas Knyva:

Estimation of Energy Meter Accuracy using Remote Non-invasive Observation

Abstract:

This paper presents an error analysis of the estimation of energy meter correction factor (CF) using a remote non-invasive technique. A method of the CF estimation based on the comparison of synchronously detected power steps in power consumption profiles of meter under test and reference meter is elaborated. The dependence of meter CF estimation uncertainty upon the magnitude of power steps, the number of power steps per observation interval, and the number of meters under test monitored by one reference meter is approximated. The synthesized consumer active power profiles are used to obtain training data points that are fit by these approximating equations.

 

177-186

VietHung Nguyen, JunSheng Cheng, VanTrong Thai:

Stacked Auto-encoder Based Feature Transfer Learning and Optimized LSSVM-PSO Classifier in Bearing Fault Diagnosis

Abstract:

This paper proposes a new diagnosis technique for predicting the big data of roller bearing multi-level fault, which uses the deep learning method for the feature representation of the vibration signal and an optimized machine learning model. First, vibration feature extraction by stacked auto-encoders (VFE-SAE) with two layers in roller bearing fault signals is proposed. The unsupervised learning algorithm in VFE-SAE is used to reveal significant properties in the vibration data, such as nonlinear and non-stationary properties. The extracted features can provide good discriminability for fault diagnosis tasks. Second, a classifier model is optimized based on least squares support vector machine classification and particle swarm optimization (LSSVM-PSO). This model is used to perform supervised fine-tuning and classification; it is trained with the labelled features to identify the target data. Especially, using transfer learning, the performance of the bearing fault diagnosis technique can be fine-tuned. In other words, the features of the target vibration signal can be extracted by the learning of feature representation, which is dependent on the weight matrix of hidden layers of the VFE-SAE method. The experimental results (by analyzing the roller bearing vibration signals with multi-status fault) demonstrate that VFE-SAE based feature extraction in conjunction with the LSSVM-PSO classification is more accurate than other popular classifier models. The proposed VFE-SAE – LSSVM-PSO method can effectively diagnose bearing faults with 97.76 % accuracy, even when using 80 % of the target data.

 

187-192

Mary Christeena Thomas, Sridhar P. Arjunan:

Deep Learning Measurement Model to Segment the Nuchal Translucency Region for the Early Identification of Down Syndrome

Abstract:

Down syndrome (DS) or Trisomy 21 is a genetic disorder that causes intellectual and mental disability in fetuses. The most essential marker for detecting DS during the first trimester of pregnancy is nuchal translucency (NT). Effective segmentation of the NT contour from the ultrasound (US) images becomes challenging due to the presence of speckle noise and weak edges. This study presents a Convolutional Neural Network (CNN) based SegNet model using a Visual Geometry Group (VGG-16) for semantically segmenting the NT region from the US fetal images and providing a fast and affordable diagnosis during the early stages of gestation. A transfer learning approach using AlexNet is implemented to train the NT segmented regions for the identification of DS. The proposed model achieved a Jaccard index of 0.96 and classification accuracy of 91.7 %, sensitivity of 85.7 %, and a Receiver operating characteristic (ROC) of 0.95.

 

193-201

Mingxing Zhang, Hongpeng Li, Tian Ge, Zhaozong Meng, Nan Gao, Zonghua Zhang:

Integrated Sensing and Computing for Wearable Human Activity Recognition with MEMS IMU and BLE Network

Abstract:

The miniature sensor devices and power-efficient Body Area Networks (BANs) for Human Activity Recognition (HAR) have gained increasing interest in different fields, including Daily Life Assistants (DLAs), medical treatment, sports analysis, etc. The HAR systems normally collect data with wearable sensors and implement the computational tasks with a host machine, where real-time transmission and processing of sensor data raise a challenge for both the network and the host machine. This investigation focuses on the hardware/software co-design for optimized sensing and computing of wearable HAR sensor networks. The contributions include (1) design of a miniature wearable sensor node integrating a Micro-Electro-Mechanical System Inertial Measurement Unit (MEMS IMU) with a Bluetooth Low Energy (BLE) in-built Micro-Control Unit (MCU) for unobtrusive wearable sensing; (2) task-centric optimization of the computation by shifting data pre-processing and feature extraction to sensor nodes for in-situ computing, which reduces data transmission and relieves the load of the host machine; (3) optimization and evaluation of classification algorithms Particle Swarm Optimization-based Support Vector Machine (PSO-SVM) and Cross Validation-based K-Nearest Neighbors (CV-KNN) for HAR with the presented techniques. Finally, experimental studies were conducted with two sensor nodes worn on the wrist and elbow to verify the effectiveness of the recognition of 10 virtual handwriting activities, where 10 recruited participants each repeated an activity 5 times. The results demonstrate that the proposed system can implement HAR tasks effectively with an accuracy of 99.20 %.

 

   
 

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