Xiaodan Wang^1,*, Zheng Xie², Guiping Du³

International Journal of Mental Health Promotion, Vol.26, No.2, pp. 149-160, 2024, DOI:10.32604/ijmhp.2023.030755

Abstract Research purpose: This study implemented somatosensory music therapy on patients with depressive disorders, and explored the effects of somatosensory music therapy on the degree of depression, positive and negative emotions, intuitive stress and autonomic nervous function of patients. Research method: We collected 66 patients diagnosed with depression from the Department of Psychological Medicine of Henan Provincial People’s Hospital, and divided them into a control group and an intervention group according to the random number table, with 33 people in each group. The control group received routine psychiatric treatment and nursing. On the basis of the control group, the intervention group… More >

Shu-Yin Chiang^*, Dong-Ye Wu

CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 2509-2526, 2023, DOI:10.32604/cmc.2023.036466

Abstract Physiological signals indicate a person’s physical and mental state at any given time. Accordingly, many studies extract physiological signals from the human body with non-contact methods, and most of them require facial feature points. However, under COVID-19, wearing a mask has become a must in many places, so how non-contact physiological information measurements can still be performed correctly even when a mask covers the facial information has become a focus of research. In this study, RGB and thermal infrared cameras were used to execute non-contact physiological information measurement systems for heart rate, blood pressure, respiratory rate, and forehead temperature for… More >

Ayan Kumar¹, Abdul Quadir Md¹, J. Christy Jackson^1,*, Celestine Iwendi²

CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 5837-5852, 2023, DOI:10.32604/cmc.2023.033431

Abstract In today’s world, there are many people suffering from mental health problems such as depression and anxiety. If these conditions are not identified and treated early, they can get worse quickly and have far-reaching negative effects. Unfortunately, many people suffering from these conditions, especially depression and hypertension, are unaware of their existence until the conditions become chronic. Thus, this paper proposes a novel approach using Bi-directional Long Short-Term Memory (Bi-LSTM) algorithm and Global Vector (GloVe) algorithm for the prediction and treatment of these conditions. Smartwatches and fitness bands can be equipped with these algorithms which can share data with a… More >

Aya Miyazaki^1,2,*, Hideki Uemura², Yasuyo Takeuchi³, Junya Tomida⁴, Yasuo Ono¹, Yoshifumi Fujimoto¹, Norie Mitsushita¹, Akio Ikai¹

Congenital Heart Disease, Vol.17, No.6, pp. 647-652, 2022, DOI:10.32604/chd.2022.021837

Abstract Appropriate heart rate in a failing pulmonary ventricle remains unknown, particularly in congenital heart disease with unique hemodynamics. A 71-year-old male with repaired tetralogy of Fallot and a pacemaker for a sinus node dysfunction suffered from heart failure symptoms with preserved left ventricular function. Simply changing the pacemaker’s lower rate from 60 to 75 bpm, New York Heart Association classification improved from III to II, and hemodynamic parameters drastically improved. We regarded this case as informative. Appropriate heart rate could be higher in congenital patients with failing right and non-failing left ventricles than in adults with malfunctioning LV. More > Graphic Abstract

Yi Sheng¹, Wu Zeng^1,*, Qiuyu Hu¹, Weihua Ou², Yuxuan Xie³, Jie Li¹

CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 2773-2783, 2022, DOI:10.32604/cmc.2022.027985

Abstract Heart rate is an important metric for determining physical and mental health. In recent years, remote photoplethysmography (rPPG) has been widely used in characterizing physiological signals in human subjects. Currently, research on non-contact detection of heart rate mainly focuses on the capture and separation of spectral signals from video imagery. However, this method is very sensitive to the movement of the test subject and light intensity variation, and this results in motion artifacts which presents challenges in extracting accurate physiological signals such as heart rate. In this paper, an improved method for rPPG signal preprocessing is proposed. Based on the… More >

Qiuyu Hu¹, Wu Zeng^1,*, Yi Sheng¹, Jian Xu¹, Weihua Ou², Ruochen Tan³

Computer Systems Science and Engineering, Vol.44, No.2, pp. 1397-1408, 2023, DOI:10.32604/csse.2023.027980

Abstract Heart rate is an important vital characteristic which indicates physical and mental health status. Typically heart rate measurement instruments require direct contact with the skin which is time-consuming and costly. Therefore, the study of non-contact heart rate measurement methods is of great importance. Based on the principles of photoelectric volumetric tracing, we use a computer device and camera to capture facial images, accurately detect face regions, and to detect multiple facial images using a multi-target tracking algorithm. Then after the regional segmentation of the facial image, the signal acquisition of the region of interest is further resolved. Finally, frequency detection… More >

Chih-Fang Huang^1,*, Ai-Hsien Fan², Jin-Huang Huang³, Hsing-Cheng Huang³

Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 661-673, 2023, DOI:10.32604/iasc.2023.027165

Abstract This study applies the diatonic chord in music theory, utilization rate, and the close relationship between the main chord system, the dominant chord system, and the subordinate chord system. From the perspective of music theory, the computer can automatically and quickly analyze the music, and establish a set of algorithms for configuring the chord accompaniment for the main melody, called the symmetrical circle of fifths algorithm, SCFA (Symmetrical Circle of Fifths Algorithm). SCFA can immediately confirm the key, perform harmony analysis, configure chord accompaniment for the main melody, and effectively and correctly complete any given melody or interval. It can… More >

Yudan Zhao^*, Chaoyu Wang

Journal of Information Hiding and Privacy Protection, Vol.3, No.3, pp. 121-130, 2021, DOI:10.32604/jihpp.2021.026380

Abstract Heart rate is an important data reflecting human vital characteristics and an important reference index to describe human physical and mental state. Currently, widely used heart rate measurement devices require direct contact with a person’s skin, which is not suitable for people with burns, delicate skin, newborns and the elderly. Therefore, the research of non-contact heart rate measurement method is of great significance. Based on the basic principle of Photoplethysmography, we use the camera of computer equipment to capture the face image, detect the face region accurately, and detect multiple faces in the image based on multi-target tracking algorithm. Then… More >

Iqra Afzal¹, Fiaz Majeed¹, Muhammad Usman Ali², Shahzada Khurram³, Akber Abid Gardezi⁴, Shafiq Ahmad⁵, Saad Aladyan⁵, Almetwally M. Mostafa⁶, Muhammad Shafiq^7,*

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2191-2207, 2022, DOI:10.32604/cmc.2022.022711

Abstract In this era of electronic health, healthcare data is very important because it contains information about human survival. In addition, the Internet of Things (IoT) revolution has redefined modern healthcare systems and management by providing continuous monitoring. In this case, the data related to the heart is more important and requires proper analysis. For the analysis of heart data, Electrocardiogram (ECG) is used. In this work, machine learning techniques, such as adaptive boosting (AdaBoost) is used for detecting normal sinus rhythm, atrial fibrillation (AF), and noise in ECG signals to improve the classification accuracy. The proposed model uses ECG signals… More >

Chih-Ta Yen^1,*, Cheng-Hong Liao²

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1973-1986, 2022, DOI:10.32604/cmc.2022.022679

Abstract In this study, single-channel photoplethysmography (PPG) signals were used to estimate the heart rate (HR), diastolic blood pressure (DBP), and systolic blood pressure (SBP). A deep learning model was proposed using a long-term recurrent convolutional network (LRCN) modified from a deep learning algorithm, the convolutional neural network model of the modified inception deep learning module, and a long short-term memory network (LSTM) to improve the model's accuracy of BP and HR measurements. The PPG data of 1,551 patients were obtained from the University of California Irvine Machine Learning Repository. How to design a filter of PPG signals and how to… More >