Article
Computer Science, Artificial Intelligence
Yikun Wang, Zhibin Pan, Jing Dong
Summary: A new neighbor selection method called two-layer nearest neighbor (TLNN) rule is proposed in this study, which considers both the query's neighborhood and the neighborhoods of all selected training instances. Experimental results show that the proposed TLNN rule outperforms not only the kNN classifier, but also seven other state-of-the-art NN-based classifiers.
KNOWLEDGE-BASED SYSTEMS
(2022)
Article
Engineering, Biomedical
Haoyu Zhang, Yan Liu, Zhongfei Qing, Ji He, Shenghua Teng, Xujian Wang, Chenxu Hao, Shuo Zhang, Dongsheng Fan, Guiping Su
Summary: In this paper, a novel Domain Contrast Network (DCN) is proposed for extracting common features of neurogenic injury for cross-muscle ALS disease identification. The proposed method demonstrates efficiency and robustness on EMG data from different individuals, different devices, and different human races. It will be useful in exploring more sensitive muscle parts for early ALS disease identification in clinical applications.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2023)
Article
Clinical Neurology
Sajid Hameed, Ayisha Farooq Khan, Sara Khan
Summary: Neurological manifestations in COVID-19 patients vary, with myopathic EMG changes commonly seen, especially in intubated patients, and also found in non-intubated patients, with one case presenting Guillain-Barre syndrome.
CLINICAL NEUROPHYSIOLOGY
(2021)
Article
Computer Science, Information Systems
Haider Ali Javaid, Mohsin Islam Tiwana, Ahmed Alsanad, Javaid Iqbal, Muhammad Tanveer Riaz, Saeed Ahmad, Faisal Abdulaziz Almisned
Summary: This study proposed a classification and recognition of hand gestures using electromyography signals, achieving an overall accuracy of 83.9% with the ensemble (bagged tree) classifier having the highest accuracy. An embedded system-based classification approach was used to design an upper limb prosthesis, making the movement and performance of the prosthesis more flexible.
Article
Energy & Fuels
Arangarajan Vinayagam, Veerapandiyan Veerasamy, Mohd Tariq, Asma Aziz
Summary: This paper proposes a heterogeneous based ensemble classifiers method for identifying and classifying power system disturbances in wind integrated microgrid network. The method utilizes discrete wavelet transform for feature extraction and involves two levels of classification. Experimental results demonstrate the effectiveness and robustness of the proposed stacking ensemble model.
SUSTAINABLE ENERGY GRIDS & NETWORKS
(2022)
Review
Clinical Neurology
N. Ahmed, M. R. Baker, J. Bashford
Summary: This article summarizes interventional clinical trials in amyotrophic lateral sclerosis (ALS) that utilized neurophysiological techniques as outcome measures. By identifying the strengths and limitations of these studies, the aim is to guide future trial design. The results show that neurophysiology offers promising biomarkers for outcome measures in ALS trials.
CLINICAL NEUROPHYSIOLOGY
(2022)
Article
Clinical Neurology
Reinhard Dengler
Summary: The article discusses the role of needle EMG in the modern diagnosis of myopathies, including the description of pathological spontaneous activity, differentiation between neuropathic and myopathic changes in motor unit potentials, and the significance of interference patterns during maximum muscle contraction. EMG cannot reliably distinguish between various forms of myopathies, except for myotonic syndromes, but can differentiate between normal and pathologic as well as neuropathic and myopathic conditions, aiding in the decision of whether to continue the diagnostic process with muscle biopsy or genetic testing.
KLINISCHE NEUROPHYSIOLOGIE
(2022)
Article
Computer Science, Artificial Intelligence
Jue Shi, Xiaofang Chen, Yongfang Xie, Hongliang Zhang, Yubo Sun
Summary: With the increasing demands for profit and safety, advanced intelligent analysis for abnormity forecast of the synthetical balance of material and energy (AF-SBME) on aluminum reduction cells (ARCs) becomes more necessary. This article proposes a refined R-KNN classifier called DR-KNN/CE, which improves R-KNN by using expert knowledge as external assistance and enhancing self-ability to mine and synthesize data knowledge. The experiments conducted on AF-SBME have demonstrated that DR-KNN/CE not only effectively improves R-KNN, but also outperforms other existing high-performance data-driven classifiers.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2023)
Article
Clinical Neurology
Mark Crook-Rumsey, Abdi Malik Musa, Raquel Iniesta, Emmanuel Drakakis, Martyn G. Boutelle, Christopher E. Shaw, James Bashford
Summary: For patients with ALS and BFS, HDSEMG recordings can be shortened from 30 to 15 minutes without significantly compromising the primary outputs. The 15-minute recordings showed more acceptable and stable agreement with the 30-minute baselines, indicating improved tolerability and repeatability among patients for longitudinal remote monitoring in patients' homes.
Article
Engineering, Electrical & Electronic
Yuang Cai, Liangliang Hao, Yanzhen Zhou, Jianlin Chen, Qihao Hu, Xianwen Duan, Guang Wang
Summary: In this article, a novel diagnosis method using field current waveforms and artificial intelligence is introduced to accurately diagnose the faults of the rotating rectifier. Various shape features in field current waveforms of different faults are analyzed, and then a hybrid algorithm based on the dynamic time warping (DTW) metric and the k-nearest neighbors (kNN) classifier (DTW-kNN) is used for fault diagnosis. Experimental results on an 11-phase prototype demonstrate the effectiveness of the hybrid method DTW-kNN. It is important to select an improved training set that includes all trends of field current waveforms to avoid asymmetry between each pair of field poles. This learning method provides a new idea for fault diagnosis of the rotating rectifier.
IEEE TRANSACTIONS ON POWER ELECTRONICS
(2023)
Article
Computer Science, Artificial Intelligence
Xianyong Zhang, Hongyuan Gou
Summary: This paper develops more general and robust double-quantitative classifiers by constructing two statistical-average double-quantitative distances based on neighborhood granulation and distance measurement. The experimental results demonstrate that these classifiers have better applicability and performance.
KNOWLEDGE-BASED SYSTEMS
(2022)
Article
Medicine, General & Internal
Shenguang Li, Po Zhu, Guoying Cai, Jing Li, Tao Huang, Wenchao Tang
Summary: This study explores the use of machine learning models, specifically the Random Forest Classifier, combined with Traditional Chinese Medicine (TCM) constitution classifications, to predict the severity of insomnia. The results demonstrate that TCM constitution classifications, such as Damp-heat and Yang-deficiency, are important determinants, highlighting their potential in guiding targeted insomnia treatments. This approach enables the development of more personalized and efficient interventions, thereby enhancing patient outcomes.
FRONTIERS IN MEDICINE
(2023)
Proceedings Paper
Acoustics
K. M. Naimul Hassan, Md Shamiul Alam Hridoy, Naima Tasnim, Atia Faria Chowdhury, Tanvir Alam Roni, Sheikh Tabrez, Arik Subhana, Celia Shahnaz
Summary: A new method ALSNet is proposed for identifying Amyotrophic Lateral Sclerosis, which showed better performance than other existing methods with an overall accuracy of 97.74%.
2022 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP)
(2022)
Article
Computer Science, Information Systems
Alberto Botter, Taian Vieira, Marco Carbonaro, Giacinto L. Cerone, Emma F. Hodson-Tole
Summary: This study compared the detection sensitivity of muscle fasciculations by ultrasound imaging and multichannel surface EMG techniques, and investigated their performance in different muscle regions and with varying EMG electrode configurations. The results showed that both techniques had similar sensitivities to muscle fasciculations, but had relatively low agreement between them. The study suggests that a combination of ultrasound imaging and EMG may maximize the sensitivity to muscle fasciculations.
Article
Computer Science, Artificial Intelligence
R. Raja Sudharsan, J. Deny, E. Muthukumaran, R. Varatharajan
Summary: This article describes the design of a wearable, remote inserted framework for Peripheral Myopathy (PM), providing information about muscle and nerve conditions through electromyographic analysis. The system collects data from four electromyographic channels on both hands and processes it using an embedded positional filtering algorithm. Experimental results demonstrate the system's potential for planning physiological muscle fiber conduction velocity values with low error rates.
JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING
(2021)
Article
Engineering, Electrical & Electronic
Hamed Abdzadeh-Ziabari, Wei-Ping Zhu, M. N. S. Swamy
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS
(2020)
Article
Engineering, Electrical & Electronic
Sachitha Kusaladharma, Wei-Ping Zhu, Wessam Ajib
IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS
(2020)
Article
Engineering, Electrical & Electronic
Kefeng Guo, Min Lin, Bangning Zhang, Jun-Bo Wang, Yongpeng Wu, Wei-Ping Zhu, Julian Cheng
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2020)
Article
Engineering, Electrical & Electronic
Xiaohuan Wu, Hua Chen, Wei-Ping Zhu
DIGITAL SIGNAL PROCESSING
(2020)
Article
Engineering, Electrical & Electronic
Weidong Wang, Qunfei Zhang, Wei-Ping Zhu, Wentao Shi, Weijie Tan
IEEE SENSORS JOURNAL
(2020)
Article
Engineering, Electrical & Electronic
Xiaohuan Wu, Wei-Ping Zhu
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2020)
Article
Computer Science, Information Systems
Abul Doulah, Tonmoy Ghosh, Delwar Hossain, Masudul H. Imtiaz, Edward Sazonov
Summary: A novel wearable sensor AIM-2 was proposed in the study, which can accurately capture food intake images, reduce the number of images for analysis, and alleviate privacy concerns of users.
IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS
(2021)
Article
Telecommunications
Lve Han, Wei-Ping Zhu, Min Lin
Summary: This letter analyzes the outage performance of a novel hybrid satellite-terrestrial relay network, providing exact and asymptotic outage probabilities for both users and discussing the impacts of imperfect successive interference cancellation, number of antennas, and choice of relaying protocols on system performance.
IEEE COMMUNICATIONS LETTERS
(2021)
Article
Computer Science, Information Systems
Yan Yan, Kang An, Bangning Zhang, Wei-Ping Zhu, Guoru Ding, Daoxing Guo
Summary: This article presents a cognitive satellite-terrestrial framework to improve the spectrum efficiency of satellite systems for coexistence with terrestrial networks. Numerical results confirm the effectiveness and superiority of the proposed scheme, revealing the impact of key parameters on system performance.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Article
Endocrinology & Metabolism
Abul Doulah, Tonmoy Ghosh, Delwar Hossain, Tyson Marden, Jason M. Parton, Janine A. Higgins, Megan A. McCrory, Edward Sazonov
Summary: This study compared the agreement between energy intake (EI) estimates derived from the AIM-2 chewing sensor signals, AIM-2 images, and an internet-based diet diary, with researcher conducted weighed food records (WFR) as the gold standard. Sensor-derived EI from regression modeling showed the closest agreement with WFR, followed by diet diary estimates. Image analysis differed significantly from WFR. Nutritionist error and differences in portion size estimation between databases contributed to the differences in image analysis and WFR. Estimation of daily EI using sensor-derived features offers a promising alternative to self-report, but image analysis may benefit from computerized analytical procedures to reduce errors.
INTERNATIONAL JOURNAL OF OBESITY
(2022)
Proceedings Paper
Engineering, Biomedical
Md. Rabiul Islam, Daniel Massicotte, Francois Nougarou, Philippe Massicotte, Wei-Ping Zhu
42ND ANNUAL INTERNATIONAL CONFERENCES OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY: ENABLING INNOVATIVE TECHNOLOGIES FOR GLOBAL HEALTHCARE EMBC'20
(2020)
Proceedings Paper
Acoustics
Xiaohuan Wu, Wei-Ping Zhu, Jun Yan
2020 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING
(2020)
Article
Engineering, Electrical & Electronic
Sachitha Kusaladharma, Wei-Ping Zhu, Wessam Ajib, Gayan Amarasuriya Aruma Baduge
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2020)
Proceedings Paper
Computer Science, Hardware & Architecture
S. Kusaladharma, W. -P. Zhu, W. Ajib
2020 IEEE 17TH ANNUAL CONSUMER COMMUNICATIONS & NETWORKING CONFERENCE (CCNC 2020)
(2020)
Proceedings Paper
Engineering, Electrical & Electronic
S. Kusaladharma, W. -P. Zhu, W. Ajib, G. Amarasuriya
ICC 2019 - 2019 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS (ICC)
(2019)