Dah-Jing Jwo^*, Kun-Chan Lee

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3803-3820, 2022, DOI:10.32604/cmc.2022.023442

Abstract The decentralized pre-filter based vector tracking loop (VTL) configuration with data wipe-off (DWO) method of the Global Positioning System (GPS) receiver is proposed for performance enhancement. It is a challenging task to continuously track the satellites’ signals in weak signal environment for the GPS receiver. VTL is a very attractive technique as it can provide tracking capability in signal-challenged environments. In the VTL, each channel will not form a loop independently. On the contrary, the signals in the channels of VTL are shared with each other; the navigation processor in turn predicts the code phases. Thus, the receiver can successfully… More >

S. Karthik¹, M. Santhosh^1,*, M. S. Kavitha¹, A. Christopher Paul²

Computer Systems Science and Engineering, Vol.42, No.1, pp. 183-199, 2022, DOI:10.32604/csse.2022.021698

Abstract Automated biomedical signal processing becomes an essential process to determine the indicators of diseased states. At the same time, latest developments of artificial intelligence (AI) techniques have the ability to manage and analyzing massive amounts of biomedical datasets results in clinical decisions and real time applications. They can be employed for medical imaging; however, the 1D biomedical signal recognition process is still needing to be improved. Electrocardiogram (ECG) is one of the widely used 1-dimensional biomedical signals, which is used to diagnose cardiovascular diseases. Computer assisted diagnostic models find it difficult to automatically classify the 1D ECG signals owing to… More >

Yun-Kyu Lee¹, Dong-Sung Pae², Dae-Ki Hong³, Myo-Taeg Lim¹, Tae-Koo Kang^4,*

Intelligent Automation & Soft Computing, Vol.32, No.2, pp. 657-673, 2022, DOI:10.32604/iasc.2022.020849

Abstract With the advancement of human-computer interaction and artificial intelligence, emotion recognition has received significant research attention. The most commonly used technique for emotion recognition is EEG, which is directly associated with the central nervous system and contains strong emotional features. However, there are some disadvantages to using EEG signals. They require high dimensionality, diverse and complex processing procedures which make real-time computation difficult. In addition, there are problems in data acquisition and interpretation due to body movement or reduced concentration of the experimenter. In this paper, we used photoplethysmography (PPG) and electromyography (EMG) to record signals. Firstly, we segmented the… More >

R. Krishnaswamy^1,*, B. Sivakumar², B. Viswanathan³, Fahd N. Al-Wesabi^4,5, Marwa Obayya⁶, Anwer Mustafa Hilal⁷

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 255-268, 2022, DOI:10.32604/cmc.2022.021995

Abstract Automatic biomedical signal recognition is an important process for several disease diagnoses. Particularly, Electrocardiogram (ECG) is commonly used to identify cardiovascular diseases. The professionals can determine the existence of cardiovascular diseases using the morphological patterns of the ECG signals. In order to raise the diagnostic accuracy and reduce the diagnostic time, automated computer aided diagnosis model is necessary. With the advancements of artificial intelligence (AI) techniques, large quantity of biomedical datasets can be easily examined for decision making. In this aspect, this paper presents an intelligent biomedical ECG signal processing (IBECG-SP) technique for CVD diagnosis. The proposed IBECG-SP technique examines… More >

Khalid Mahmood Aamir¹, Muhammad Ramzan^1,2, Saima Skinadar¹, Hikmat Ullah Khan³, Usman Tariq⁴, Hyunsoo Lee⁵, Yunyoung Nam^5,*, Muhammad Attique Khan⁶

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 17-33, 2022, DOI:10.32604/cmc.2022.018613

Abstract This paper focuses on detecting diseased signals and arrhythmias classification into two classes: ventricular tachycardia and premature ventricular contraction. The sole purpose of the signal detection is used to determine if a signal has been collected from a healthy or sick person. The proposed research approach presents a mathematical model for the signal detector based on calculating the instantaneous frequency (IF). Once a signal taken from a patient is detected, then the classifier takes that signal as input and classifies the target disease by predicting the class label. While applying the classifier, templates are designed separately for ventricular tachycardia and… More >

V. R. Vimal^1,*, P. Anandan², N. Kumaratharan³

Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 31-43, 2022, DOI:10.32604/iasc.2022.017622

Abstract

Electrocardiogram (ECG) monitoring models are commonly employed for diagnosing heart diseases. Since ECG signals are normally acquired for a longer time duration with high resolution, there is a need to compress the ECG signals for transmission and storage. So, a novel compression technique is essential in transmitting the signals to the telemedicine center to monitor and analyse the data. In addition, the protection of ECG signals poses a challenging issue, which encryption techniques can resolve. The existing Encryption-Then-Compression (ETC) models for multimedia data fail to properly maintain the trade-off between compression performance and signal quality. In this view, this study… More >

Dah-Jing Jwo^*, Sheng-Feng Chiu

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 6159-6176, 2022, DOI:10.32604/cmc.2022.020793

Abstract In this paper, the data wipe-off (DWO) algorithm is incorporated into the vector tracking loop of the Global Positioning System (GPS) receiver for improving signal tracking performance. The navigation data, which contains information that is necessary to perform navigation computations, are binary phase-shift keying (BPSK) modulated onto the GPS carrier phase with the bit duration of 20 ms (i.e., 50 bits per second). To continuously track the satellite’s signal in weak signal environment, the DWO algorithm on the basis of pre-detection method is adopted to detect data bit sign reversal every 20 ms. Tracking accuracy of a weak GPS signal… More >

Junyu Chen¹, Yunwen Feng^1,*, Cheng Lu^1,2, Chengwei Fei²

CMES-Computer Modeling in Engineering & Sciences, Vol.129, No.2, pp. 1013-1027, 2021, DOI:10.32604/cmes.2021.016980

Abstract As the key component in aeroengine rotor systems, the health status of rolling bearings directly influences the reliability and safety of aeroengine rotor systems. In order to monitor rolling bearing conditions, a fusion fault diagnosis method, namely empirical mode decomposition (EMD)-Mahalanobis distance (E2MD) and improved wavelet threshold (IWT) (E2MD-IWT) for vibrational signals and acoustic emission (AE) signals is developed to improve the diagnostic accuracy of rolling bearings. The IWT method is proposed with a hard wavelet threshold and a soft wavelet threshold. Moreover, it is shown to be effective through numerical simulation. EMD is utilized to process the original AE… More >

Wen-Tsai Sung¹, Sung-Jung Hsiao^2,*

Computer Systems Science and Engineering, Vol.41, No.1, pp. 289-304, 2022, DOI:10.32604/csse.2022.020453

Abstract The safety of patients and the quality of medical care provided to them are vital for their wellbeing. This study establishes a set of RFID (Radio Frequency Identification)-based systems of patient care based on physiological signals in the pursuit of a remote medical care system. The RFID-based positioning system allows medical staff to continuously observe the patient's health and location. The staff can thus respond to medical emergencies in time and appropriately care for the patient. When the COVID-19 pandemic broke out, the proposed system was used to provide timely information on the location and body temperature of patients who… More >

Chih-Ta Yen^1,*, Sheng-Nan Chang², Liao Jia-Xian³, Yi-Kai Huang³

CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2937-2952, 2022, DOI:10.32604/cmc.2022.020493

Abstract This study proposed a measurement platform for continuous blood pressure estimation based on dual photoplethysmography (PPG) sensors and a deep learning (DL) that can be used for continuous and rapid measurement of blood pressure and analysis of cardiovascular-related indicators. The proposed platform measured the signal changes in PPG and converted them into physiological indicators, such as pulse transit time (PTT), pulse wave velocity (PWV), perfusion index (PI) and heart rate (HR); these indicators were then fed into the DL to calculate blood pressure. The hardware of the experiment comprised 2 PPG components (i.e., Raspberry Pi 3 Model B and analog-to-digital… More >