Porta A , Nollo G , Faes L . Bridging the gap between the development of advanced biomedical signal processing tools and clinical practice. Physiological Measurement 2016; 36:627-631.
 Braojos R , Bortolotti D , Bartolini A , et al. A Synchronization-Based Hybrid-Memory Multi-Core Architecture for Energy-Efficient Biomedical Signal Processing. IEEE Transactions on Computers 2017; 66:575-585.
 Roy R N , Charbonnier S , Bonnet, Stéphane. Eye blink characterization from frontal EEG electrodes using source separation and pattern recognition algorithms. Biomedical Signal Processing and Control 2014; 14:256-264.
 Sun L , Chen B , Toh K A , et al. Sequential extreme learning machine incorporating survival error potential. Neurocomputing 2015; 155:194-204.
 Bruce EN. Biomedical Signal Processing and Signal Modeling. Expert Systems with Applications 2000; 38:6190–6201.
 Rubén Fraile, Kob M, Godino-Llorente JI, et al. Physical simulation of laryngeal disorders using a multiple-mass vocal fold model. Biomedical Signal Processing and Control 2012; 7:65-78.
 Li DC, Rastegar-Mojarad M, Okamoto J, et al. A Bibliometric Analysis on Cancer Population Science with Topic Modeling. Amia Jt Summits Transl Sci Proc 2015; 2015:102-106.
 Bornmann L , Mutz, Rüdiger. Growth rates of modern science: A bibliometric analysis based on the number of publications and cited references. Journal of the Association for Information Science and Technology 2015; 66:2215-2222.
 Xiaoxu Y, Junpeng Y, Jiping G, et al. The Comparative Study of Scientific Knowledge Mapping Tools Based on the Actual Case. Digital Library Forum 2014; 5: 66-71.(in Chinese)
 Eck NJV , Waltman L . Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics 2010; 84:523-538.
 JuárezAguirre, Raúl, DomínguezNicolás, Saúl M, Manjarrez, Elías, et al. Digital Signal Processing by Virtual Instrumentation of a MEMS Magnetic Field Sensor for Biomedical Applications. Sensors 2013; 13:15068-15084.
 Polosin VG, Bodin ON, Ivanchukov AG, et al. Isoline Drift Correction in Digital Processing of the Electrocardiosignal. Biomedical Engineering 2016; 50:119-123.
 Liu G, Huang G, Meng J, et al. A frequency-weighted method combined with Common Spatial Patterns for electroencephalogram classification in brain-computer interface. Biomedical Signal Processing and Control 2010; 5:174-180.
 Lee YC, Chen C, Tsai XT. Visualizing the Knowledge Domain of Nanoparticle Drug Delivery Technologies: A Scientometric Review. Applied Sciences 2016; 6: 11.
 Cifrek M , Medved V , Tonković S, et al. Surface EMG based muscle fatigue evaluation in biomechanics. Clinical biomechanics (Bristol, Avon) 2009; 24:0-340.
 Skog I , Handel P , Nilsson JO , et al. Zero-Velocity Detection—An Algorithm Evaluation. IEEE Transactions on Biomedical Engineering 2010; 57:2657-2666.
 Mijović Bogdan, De Vos M, Gligorijević Ivan, et al. Source separation from single-channel recordings by combining empirical-mode decomposition and independent component analysis. IEEE Transactions on Biomedical Engineering 2010; 57:2188-2196.
 Acar E , Dunlavy DM , Kolda TG, et al. Scalable tensor factorizations for incomplete data. 2011;106:41-56.
 Colominas MA, Schlotthauer Gastón, Torres María E. Improved complete ensemble EMD: A suitable tool for biomedical signal processing. Biomedical Signal Processing and Control 2014; 14:19-29.
 Ihlen EAF. Introduction to multifractal detrended fluctuation analysis in Matlab. Frontiers in Physiology 2012, 3:141.
 Min S , Lee B , Yoon S . Deep Learning in Bioinformatics. Briefings in Bioinformatics 2016; 18:851.
 Jin KH , Mccann MT, Froustey E, et al. Deep Convolutional Neural Network for Inverse Problems in Imaging. IEEE Transactions on Image Processing 2017; 26:4509-4522.
 Sazonov E S , Makeyev O , Schuckers S , et al. Automatic detection of swallowing events by acoustical means for applications of monitoring of ingestive behavior[J]. IEEE Transactions on Biomedical Engineering, 2010, 57(3):626-633.
 Chappell MA, Groves AR, Whitcher BJ, et al. Variational Bayesian Inference for a Nonlinear Forward Model. IEEE Transactions on Signal Processing 2009; 57:223-236.
 Evans NA , Emily D , Tim U . An electromyography study of muscular endurance during the posterior shoulder endurance test. Journal of Electromyography and Kinesiology 2018; 41:132-138.
 Karthick PA , Ghosh DM , Ramakrishnan S. Surface electromyography based muscle fatigue detection using high-resolution time-frequency methods and machine learning algorithms. Computer Methods & Programs in Biomedicine 2018; 154:45-56.
 Bigliassi M , Karageorghis CI , Nowicky AV , et al. Cerebral mechanisms underlying the effects of music during a fatiguing isometric ankle-dorsiflexion task. Psychophysiology 2016; 53: 1472-1483.
 Shahtalebi S , Mohammadi A . Bayesian Optimized Spectral Filters Coupled with Ternary ECOC for Single Trial EEG Classification. IEEE Transactions on Neural Systems and Rehabilitation Engineering 2018; 26: 2249-2259.
 Zille P , Calhoun VD , Wang YP . Enforcing Co-expression Within a Brain-Imaging Genomics Regression Framework. IEEE Transactions on Medical Imaging 2017; 37:2561-2571.
 Manish S , Bhurane AA , Rajendra AU . MMSFL-OWFB: A novel class of orthogonal wavelet filters for epileptic seizure detection. Knowledge-Based Systems 2018; 160: 265-277.
 Zafer C , Fatih KA , Velappan S. Prognostic model based on image-based time-frequency features and genetic algorithm for fetal hypoxia assessment. Computers in Biology and Medicine 2018; 99: 85-97.
 Ucar MK; Bozkurt MR; Bilgin C, et al. Automatic sleep staging in obstructive sleep apnea patients using photoplethysmography, heart rate variability signal and machine learning techniques. Neural Computing and Applications 2016; 29:1-16.
 Dai M, Xiao X, Chen X, et al. A low-power and miniaturized electrocardiograph data collection system with smart textile electrodes for monitoring of cardiac function[J]. Australasian Physical & Engineering Sciences in Medicine 2016; 39:1029-1040.
 Wedekind D , Kleyko D , Osipov E , et al. Robust Methods for Automated Selection of Cardiac Signals after Blind Source Separation. IEEE Transactions on Biomedical Engineering 2018; 65: 2248-2258.
 Mei Z, Gu X, Chen H, et al. Automatic Atrial Fibrillation Detection Based on Heart Rate Variability and Spectral Features. IEEE Access 2018; 6: 53566-53575.
 Manish S, Bhurane AA, Rajendra AU. MMSFL-OWFB: A novel class of orthogonal wavelet filters for epileptic seizure detection. Knowledge-Based Systems 2018; 160: 265-277.
 Roilhi F. Ibarra-Hernández, Miguel A. Alonso-Arévalo, Alejandro Cruz-Gutiérrez, et al. Design and evaluation of a parametric model for cardiac sounds. Computers in Biology and Medicine 2017; 89:170-180.
 Algueta-Miguel JM , Blas CADLC , A. J. López-martín, et al. Design of CMOS amplifiers with offset rejection using positive-feedback QFG transistors. Analog Integrated Circuits and Signal Processing 2015; 85:217-221.
 Narasimhan S , Chiel HJ , Bhunia S . Ultra-low-power and robust digital-signal-processing hardware for implantable neural interface microsystems. IEEE Transactions on Biomedical Circuits & Systems 2011; 5:169-178.
 Kakareka JW , Faranesh AZ , Pursley RH , et al. Physiological Recording in the MRI Environment (PRiME): MRI-compatible hemodynamic recording system[J]. IEEE Journal of Translational Engineering in Health and Medicine 2018; 6: 4100112.
 Clifton DA, Wong D, Clifton L, et al. A Large-Scale Clinical Validation of an Integrated Monitoring System in the Emergency Department[J]. IEEE Journal of Biomedical and Health Informatics 2013;17:835-842.
 Abdelaal M, Elsarnagawy T. Analysis of Biomedical Signals with High Frequency Components of Wavelet Transform Compression Method on Electrocardiogram Signals[J]. Journal of Medical Imaging and Health Informatics 2018, 8: 785-788.
 Jin KH, Mccann MT, Froustey E, et al. Deep Convolutional Neural Network for Inverse Problems in Imaging. IEEE Transactions on Image Processing 2017; 21: 4721-4733.
 Valle BGD , Cash SS , Sodini CG . Low-Power, 8-Channel EEG Recorder and Seizure Detector ASIC for a Subdermal Implantable System. IEEE Transactions on Biomedical Circuits & Systems 2016, 10:1058-1067.
 Kumar SU , Inbarani HH . Neighborhood rough set based ECG signal classification for diagnosis of cardiac diseases. Soft Computing 2016; 21: 4721-4733.
 Cecília M. Costa, Silva IS , Sousa RDD , et al. The Association between Reconstructed Phase Space and Artificial Neural Networks for Vectorcardiographic Recognition of Myocardial Infarction. Journal of Electrocardiology 2018; 51: 443-449.