EMG-Centered Multisensory Based Technologies for Pattern Recognition in Rehabilitation: State of the Art and Challenges

In the field of rehabilitation, the electromyography (EMG) signal plays an important role in interpreting patients’ intentions and physical conditions. Nevertheless, utilizing merely the EMG signal suffers from difficulty in recognizing slight body movements, and the detection accuracy is strongly influenced by environmental factors. To address the above issues, multisensory integration-based EMG pattern recognition (PR) techniques have been developed in recent years, and fruitful results have been demonstrated in diverse rehabilitation scenarios, such as achieving high locomotion detection and prosthesis control accuracy. Owing to the importance and rapid development of the EMG centered multisensory fusion technologies in rehabilitation, this paper reviews both theories and applications in this emerging field. The principle of EMG signal generation and the current pattern recognition process are explained in detail, including signal preprocessing, feature extraction, classification algorithms, etc. Mechanisms of collaborations between two important multisensory fusion strategies (kinetic and kinematics) and EMG information are thoroughly explained; corresponding applications are studied, and the pros and cons are discussed. Finally, the main challenges in EMG centered multisensory pattern recognition are discussed, and a future research direction of this area is prospected.

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EMG Pattern Recognition in the Era of Big Data and Deep Learning

Big Data and Cognitive Computing ◽

10.3390/bdcc2030021 ◽

2018 ◽

Vol 2 (3) ◽

pp. 21 ◽

Cited By ~ 37

Author(s):

Angkoon Phinyomark ◽

Erik Scheme

Keyword(s):

Pattern Recognition ◽

Big Data ◽

Deep Learning ◽

Data Analysis ◽

Big Data Analytics ◽

Machine Learning Techniques ◽

Topological Data Analysis ◽

Future Research ◽

Emg Signal ◽

Emg Pattern Recognition

The increasing amount of data in electromyographic (EMG) signal research has greatly increased the importance of developing advanced data analysis and machine learning techniques which are better able to handle “big data”. Consequently, more advanced applications of EMG pattern recognition have been developed. This paper begins with a brief introduction to the main factors that expand EMG data resources into the era of big data, followed by the recent progress of existing shared EMG data sets. Next, we provide a review of recent research and development in EMG pattern recognition methods that can be applied to big data analytics. These modern EMG signal analysis methods can be divided into two main categories: (1) methods based on feature engineering involving a promising big data exploration tool called topological data analysis; and (2) methods based on feature learning with a special emphasis on “deep learning”. Finally, directions for future research in EMG pattern recognition are outlined and discussed.

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The Role of Lung Ultrasound in Viral Lower Respiratory Tract Infections

American Journal of Perinatology ◽

10.1055/s-0038-1637758 ◽

2018 ◽

Vol 35 (06) ◽

pp. 527-529 ◽

Cited By ~ 4

Author(s):

Nadya Yousef ◽

Daniele De Luca

Keyword(s):

Respiratory Tract ◽

Respiratory Tract Infections ◽

Lung Ultrasound ◽

Rapid Development ◽

Research Direction ◽

Future Research ◽

Ultrasound Findings ◽

Significant Burden ◽

Tract Infections

AbstractDespite being a bedside technique under rapid development and diffusion, lung ultrasound has not been often used in the management of viral low respiratory tract infections, although these infections represent a significant burden of care in neonatology and pediatrics. The aim of this article is to review the lung ultrasound findings and the evidence-based data available on this topic. Guidance on bedside imaging interpretation and future research direction are also discussed in this article.

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TRAJECTORY SIMULATION OF BADMINTON ROBOT BASED ON FRACTAL BROWN MOTION

Fractals ◽

10.1142/s0218348x20400216 ◽

2020 ◽

Vol 28 (08) ◽

pp. 2040021

Author(s):

GAOYUAN CUI ◽

BIN ZHANG ◽

RODRIGUES MARLENE

Keyword(s):

Real Time ◽

Pose Estimation ◽

Three Dimensional ◽

Estimation Algorithm ◽

Research Direction ◽

Future Research ◽

Detection Accuracy ◽

Binocular Stereo Vision ◽

Executive Mechanism ◽

Brown Motion

This paper focuses on the design of badminton robots, and designs high-precision binocular stereo vision synchronous acquisition system hardware and multithreaded acquisition programs to ensure the left and right camera exposure synchronization and timely reading of data. Aiming at specific weak moving targets, a shape-based Brown motion model based on dynamic threshold adjustment based on singular value decomposition is proposed, and a discriminative threshold is set according to the similarity between the background and the foreground to improve detection accuracy. The three-dimensional trajectory points are extended by Kalman filter and the kinematics equation of badminton is established. The parameters of the kinematics equation of badminton are solved by the method of least squares. Based on the fractal Brownian motion algorithm, a real-time robot pose estimation algorithm is proposed to realize the real-time accurate pose estimation of the robot. A PID control model for the badminton robot executive mechanism is established between the omnidirectional wheel speed and the robot’s translation and rotation movements to achieve the precise movement of the badminton robot. All the algorithms can meet the system’s requirements for real-time performance, realize the badminton robot’s simple hit to the ball, and prospect the future research direction.

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Environmental and Safety Impacts of Vehicle-to-Everything Enabled Applications: A Review of State-of-the-Art Studies

10.20944/preprints202201.0144.v1 ◽

2022 ◽

Author(s):

Jianhe Du ◽

Kyoungho Ahn ◽

Mohamed Farag ◽

Hesham Rakha

Keyword(s):

Rapid Development ◽

Data Communication ◽

Research Direction ◽

Vehicle Safety ◽

Future Research ◽

Full Potential ◽

New Radio ◽

Data Rates ◽

Share Data ◽

4G Lte

With the rapid development of communication technology, connected vehicles (CV) have the potential, through the sharing of data, to enhance vehicle safety and reduce vehicle energy consumption and emissions. Numerous research efforts have been conducted to quantify the impacts of CV applications, assuming instant and accurate communication among vehicles, devices, pedestrians, infrastructure, the network, the cloud, and the grid, collectively known as V2X (vehicle-to-everything). The use of cellular vehicle-to-everything (C-V2X), to share data is emerging as an efficient means to achieve this objective. C-V2X releases 14 and 15 utilize the 4G LTE technology and release 16 utilizes the new 5G new radio (NR) technology. C-V2X can function without network infrastructure coverage and has a better communication range, improved latency, and greater data rates compared to older technologies. Such highly efficient interchange of information among all participating parts in a CV environment will not only provide timely data to enhance the capacity of the transportation system but can also be used to develop applications that enhance vehicle safety and minimize negative environmental impacts. However, before the full benefits of CV can be achieved, there is a need to thoroughly investigate the effectiveness, strengths, and weaknesses of different CV applications, the communication protocols, the varied results with different CV market penetration rates (MPRs), the interaction of CVs and human driven vehicles, the integration of multiple applications, and the errors and latencies associated with data communication. This paper reviews existing literature on the environmental, mobility and safety impacts of CV applications, identifies the gaps in our current research of CVs and recommends future research directions. The results of this paper will help shape the future research direction for CV applications to realize their full potential benefits.

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Recent Advances on Cellulose Nanocrystals and Their Derivatives

Polymers ◽

10.3390/polym13193247 ◽

2021 ◽

Vol 13 (19) ◽

pp. 3247

Author(s):

Shuting Peng ◽

Qiguan Luo ◽

Guofu Zhou ◽

Xuezhu Xu

Keyword(s):

Chemical Modification ◽

Cellulose Nanocrystals ◽

Chemical Reactivity ◽

Structural Characteristics ◽

Research Direction ◽

Small Dimension ◽

Future Research ◽

Synthesis Methods ◽

Recent Advances ◽

Pros And Cons

Nanocellulose, typically cellulose nanocrystals (CNCs), has excellent properties and is widely used. In particular, CNC has a small dimension, high chemical reactivity, and high sustainability, which makes it an excellent candidate as a starting material to be converted into nanocellulose derivatives. Chemical modification is essential for obtaining the desired products; the modifications create different functional attachment levels and generate novel microstructures. Recent advances on nanocellulose derivatives have not yet been reviewed and evaluated for the last five years. Nanocellulose derivative materials are being used in a wide variety of high-quality functional applications. To meet these requirements, it is essential for researchers to fully understand CNCs and derivative materials, precisely their characteristics, synthesis methods, and chemical modification approaches. This paper discusses CNC and its derivatives concerning the structural characteristics, performance, and synthesis methods, comparing the pros and cons of these chemical modification approaches reported in recent years. This review also discusses the critical physicochemical properties of CNC derivative products, including solubility, wetting performance, and associated impacts on properties. Lastly, this paper also comments on the bottlenecks of nanocellulose derivatives in various applications and briefly discusses their future research direction.

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ECONOMIC GROWTH ANALYSIS: A STUDY ON MALAYSIAN MARKET

e-Academia Journal ◽

10.24191/e-aj.v9i2.7379 ◽

2019 ◽

Vol 8 (2) ◽

Author(s):

Suhaily Maizan Abdul Manaf ◽

Shuhada Mohamed Hamidi ◽

Nur Shafini Mohd Said ◽

Siti Rapidah Omar Ali ◽

Nur Dalila Adenan

Keyword(s):

Economic Growth ◽

Foreign Direct Investment ◽

Direct Investment ◽

Inflation Rate ◽

Government Expenditure ◽

Correlation Method ◽

Research Direction ◽

Least Square ◽

Future Research ◽

Internal And External Factors

Economic performance of a country is mostly determined by the growth and any other internal and external factors. In this study, researchers purposely focused on Malaysian market by examining the relationship between export, inflation rate, government expenditure and foreign direct investment towards economic growth in Malaysia by applying the yearly data of 47 years from 1970 to 2016 using descriptive statistics, regression model and correlation method analysis. By applying Ordinary Least Square (OLS) method, the result suggests that export, government expenditure and foreign direct investment are positively and significantly correlated with the economic growth. However, inflation rate has negative and insignificant relationship with the economic growth. The outcome of the study is suggested to be useful in providing the future research direction towards the economic growth in Malaysia. Keywords: economic growth; export; inflation rate; government expenditure

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Review of Research Trends on Coaching Studies and Recommendations for Future Research Direction in Korea - Progress from 1995 to 2017 and Challenges -

Korean Journal of Resources Development ◽

10.24991/kjhrd.2018.09.21.3.249 ◽

2018 ◽

Vol 21 (3) ◽

pp. 249-313

Author(s):

Seong Jhin Joh ◽

Yi Su Jung

Keyword(s):

Research Direction ◽

Research Trends ◽

Future Research ◽

Future Research Direction

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A Review on Automatic Bill of Material Generation and Visual Inspection on PCBs

ISTFA 2019: Conference Proceedings from the 45th International Symposium for Testing and Failure Analysis ◽

10.31399/asm.cp.istfa2019p0256 ◽

2019 ◽

Author(s):

Mukhil Azhagan M. S ◽

Dhwani Mehta ◽

Hangwei Lu ◽

Sudarshan Agrawal ◽

Mark Tehranipoor ◽

...

Keyword(s):

Image Analysis ◽

Visual Inspection ◽

Automated System ◽

Imaging Modalities ◽

Future Research ◽

Analysis Techniques ◽

Bill Of Materials ◽

Pros And Cons ◽

Index Terms ◽

Image Analysis Techniques

Abstract Globalization and complexity of the PCB supply chain has made hardware assurance a challenging task. An automated system to extract the Bill of Materials (BoM) can save time and resources during the authentication process, however, there are numerous imaging modalities and image analysis techniques that can be used to create such a system. In this paper we review different imaging modalities and their pros and cons for automatic PCB inspection. In addition, image analysis techniques commonly used for such images are reviewed in a systematic way to provide a direction for future research in this area. Index Terms—Component Detection, PCB, Authentication, Image Analysis, Machine Learning

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A Robust Blind Image Forensic-Detection Method based on Fuzzy Technique

International Journal of Recent Technology and Engineering - 2 ◽

10.35940/ijrte.c4742.098319 ◽

2019 ◽

Vol 8 (3) ◽

pp. 5926-5929

Keyword(s):

Research Direction ◽

Geometric Transformation ◽

Detection Accuracy ◽

Forensic Investigation ◽

Image Forensic ◽

Fuzzy Logic Approach ◽

Logic Approach ◽

Tampered Image ◽

New Research ◽

Blind Image

Blind forensic-investigation in a digital image is a new research direction in image security. It aims to discover the altered image content without any embedded security scheme. Block and key point based methods are the two dispensation options in blind image forensic investigation. Both the techniques exhibit the best performance to reveal the tampered image. The success of these methods is limited due to computational complexity and detection accuracy against various image distortions and geometric transformation operations. This article introduces different blind image tampering methods and introduces a robust image forensic investigation method to determine the copy-move tampered image by means of fuzzy logic approach. Empirical outcomes facilitate that the projected scheme effectively classifies copy-move type of forensic images as well as blurred tampered image. Overall detection accuracy of this method is high over the existing methods.

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