Article
Engineering, Biomedical
Chuanmin Wu, Jiafeng Qiu, Gang Shen
Summary: Heart rate variability (HRV) is a reliable measure of physical and mental fitness. This study proposes a self-supervised learning approach to address the challenge of undesirable artifacts in BCG signals, and demonstrates high accuracy in heartbeat identification and interbeat interval measurements through evaluations.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2024)
Article
Engineering, Biomedical
Miao Zhang, Lishen Qiu, Yuhang Chen, Shuchen Yang, Zhiming Zhang, Lirong Wang
Summary: This study proposes a Conv-Transformer network for estimating heart rate using non-contact ballistocardiography technology. The results demonstrate the effectiveness of the proposed method, which introduces transformer and electrocardiogram noise into BCG signal analysis. This research has potential implications for healthcare applications, particularly in the prevention of chronic diseases.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2023)
Article
Engineering, Multidisciplinary
Zonglei Mou, Lei Han, Yu Chen
Summary: This paper proposes a noise reduction model for the BCG signal based on GAF and an improved DAE, referred to as the GDAE model, for accurately detecting heart rate in noise-contaminated signals. The experimental results show that the proposed method has a better detection effect compared to the traditional method under strong noise interference.
ENGINEERING RESEARCH EXPRESS
(2023)
Article
Engineering, Electrical & Electronic
Weidong Gao, Zhenwei Zhao
Summary: This article proposes a method to extract cardiac characteristics from ballistocardiogram (BCG) signals and compares them with ECG signals. The results show that this method has high detection accuracy and is suitable for noncontact heart health monitoring.
IEEE SENSORS JOURNAL
(2023)
Article
Engineering, Electrical & Electronic
Chulseung Yang, Gi Won Ku, Jeong-Gi Lee, Kyungho Kim
Summary: With changes in the socio-economic environment, the number of single and elderly households has increased, leading to a greater demand for maintaining long and healthy lives. Personalized healthcare services, based on recording and analyzing living patterns and biometric information unconsciously, are essential to meet these needs. This paper proposes a method to improve the accuracy of BCG measurement using similarity and Signal-to-noise ratio analysis, with a focus on continuous personal health monitoring in home without user awareness.
JOURNAL OF ELECTRICAL ENGINEERING & TECHNOLOGY
(2021)
Article
Engineering, Civil
Guanglong Du, Tao Li, Chunquan Li, Peter X. Liu, Di Li
Summary: This paper proposes a method that uses a single RGB-D camera to extract three fatigue features and improves the accuracy of driver fatigue detection through a novel multimodal fusion recurrent neural network. By addressing the fuzziness and noise of the heart rate feature and identifying the relationship between features, the proposed method outperforms similar methods in both simulation and field experiments.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2021)
Article
Nutrition & Dietetics
Shing-Hong Liu, Bing-Hao Zhang, Wenxi Chen, Chun-Hung Su, Chiun-Li Chin
Summary: This study aims to develop a cuffless and touchless method for measuring blood pressure using a commercial weight scale and a PPG sensor. By analyzing the BCG and PPG signals, blood pressure can be estimated. The results show that this method can accurately measure blood pressure.
Article
Engineering, Electrical & Electronic
Weijuan Chen, Yi Zhang, Huicheng Yang, Yishen Qiu, Hui Li, Zhihao Chen, Changyuan Yu
Summary: Researches have proposed and demonstrated a non-invasive and continuous ballistocardiogram (BCG) based vital signs monitoring system using a seven-core fiber interferometer (SCFI) sensor, providing a more convenient, compact, and cost-effective way to measure vital signs. Results show that the measured heart rate (HR) and respiratory rate (RR) of the proposed sensor are in good agreement with commercial physiological devices, suggesting promising potential for long-term and non-invasive vital signs monitoring.
IEEE SENSORS JOURNAL
(2021)
Article
Engineering, Multidisciplinary
Haijun Lin, Sirao Zhang, Qinghao Li, Ya Li, Jianmin Li, Yuxiang Yang
Summary: This paper proposes a new method for heart rate prediction based on LSTM-BiLSTM-Att model. The model combines LSTM, BiLSTM, and attention mechanism to capture the long-term relationship, high-dimensional features, and forward/backward correlation information of heart rate data. Experimental results show that the proposed method significantly improves the accuracy of heart rate prediction.
Article
Optics
Xiang Guo, Yingtao Yuan, Tao Suo, Xin Su, Yan Liu, Zhendong Ge
Summary: The study introduced a novel method for synchronously measuring the temperature and strain distribution of an object, effectively corresponding data in non-uniform temperature and strain fields, thus providing technical support for studying thermal-mechanical coupling deformation.
OPTICS AND LASERS IN ENGINEERING
(2021)
Article
Pediatrics
Libor Svoboda, Jan Sperrhake, Maria Nisser, Chen Zhang, Gunter Notni, Hans Proquitte
Summary: This study conducted a pilot study on contactless heart rate monitoring in newborns and preterm infants using a camera-based photoplethysmography method. The results showed the feasibility and accuracy of this emerging method compared to conventional pulse oximetry. There were differences in heart rate measurements between 2D and 3D techniques when compared to pulse oximetry.
FRONTIERS IN PEDIATRICS
(2022)
Article
Health Care Sciences & Services
Yanting Xu, Zhengyuan Yang, Gang Li, Jinghong Tian, Yonghua Jiang
Summary: In this study, a non-contact biomedical signal of ballistocardiogram (BCG) was collected using an optical fiber sensor cushion during cognitive tasks for 20 subjects. Heart rate variability (HRV) was calculated from the BCG signal and a machine learning classification model based on random forest was used to quantify and recognize brain fatigue. The results showed high accuracy in identifying brain fatigue state and a strong correlation between HRV and accuracy, indicating its potential as an indicator for quantitative brain fatigue evaluation during tasks.
Article
Chemistry, Analytical
Xianyou Li, Ke Xu, Shun Wang
Summary: This paper presents a large-scale shaft diameter precision measurement method based on a dual camera measurement system and verifies its effectiveness. The experimental results show that the measurement accuracy of the proposed method is comparable to that of CMM.
Article
Biophysics
Yingli Shi, Jian Qiu, Li Peng, Peng Han, Kaiqing Luo, Dongmei Liu
Summary: To improve the accuracy, robustness, and real-time performance of heart rate measurement using imaging photoplethysmography (IPPG), a new method combined with modified ensemble empirical mode decomposition (EEMD) and fast independent component analysis (FastICA) was proposed. Experimental results showed that the method achieved a mean absolute error (MAE) of 0.93 beats per minute and a correlation coefficient of 0.820 in the hybrid natural light and computer screen light scenario.
PHYSIOLOGICAL MEASUREMENT
(2023)
Review
Chemistry, Analytical
Aoxin Ni, Arian Azarang, Nasser Kehtarnavaz
Summary: The study conducted a comparison of deep learning methods with publicly available codes for heart rate measurement, revealing that PhysNet generated the best outcome among these methods.
