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学者姓名：高跃明
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Abstract ：
Heart rate variability (HRV), indicating the variation in intervals between consecutive heartbeats, is a crucial physiological indicator of human health. However, detecting HRV using frequency-modulated continuous-wave (FMCW) radar is highly susceptible to interference from respiration, minor body movements, and environmental noise, especially in multitarget scenarios. To address these challenges, we propose the Health-Radar system, which comprises three functional modules. In the target detection module, the system accurately identifies the number and locations of targets. In the phase extraction module, the signal undergoes dc offset calibration to extract the chest displacement signals. In the heartbeat signal extraction module, we introduce Health-VMD, an adaptive parameter variational mode decomposition (VMD) method. This method optimizes the VMD parameters using an improved grasshopper optimization algorithm (GOA) and accurately extracts vital sign signals from chest displacement signals to estimate HRV. In addition, we propose a novel objective function, composed of permutation entropy, mutual information, and energy loss rate (PME), specifically designed for vital sign extraction. Experiments with multiple participants in various scenarios demonstrated that the designed system can accurately identify different targets and detect HRV with high precision. The root-mean-square error (RMSE) of the detected interbeat intervals (IBIs) is 29.72 ms, the RMSE of the standard deviation of NN intervals (SDNN) is 4.1 ms, and the RMSE of the root mean square of successive differences (RMSSD) is 18.61 ms, outperforming existing methods.
Keyword ：
Accuracy Accuracy Biomedical monitoring Biomedical monitoring Estimation Estimation Frequency-modulated continuous-wave (FMCW) radar Frequency-modulated continuous-wave (FMCW) radar Harmonic analysis Harmonic analysis Heart beat Heart beat Heart rate variability Heart rate variability heart rate variability (HRV) heart rate variability (HRV) multitarget vital signs detection multitarget vital signs detection noncontact detection noncontact detection Optimization Optimization Radar Radar Radar detection Radar detection Sensors Sensors variational mode decomposition (VMD) variational mode decomposition (VMD)
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| GB/T 7714 | Xu, Zhimeng , Ye, Tao , Chen, Liangqin et al. Health-Radar: Noncontact Multitarget Heart Rate Variability Detection Using FMCW Radar [J]. | IEEE SENSORS JOURNAL , 2025 , 25 (1) : 405-418 . |
| MLA | Xu, Zhimeng et al. "Health-Radar: Noncontact Multitarget Heart Rate Variability Detection Using FMCW Radar" . | IEEE SENSORS JOURNAL 25 . 1 (2025) : 405-418 . |
| APA | Xu, Zhimeng , Ye, Tao , Chen, Liangqin , Gao, Yueming , Chen, Zhizhang . Health-Radar: Noncontact Multitarget Heart Rate Variability Detection Using FMCW Radar . | IEEE SENSORS JOURNAL , 2025 , 25 (1) , 405-418 . |
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Conductive intracardiac communication (CIC) is an essential approach for achieving multichamber pacing in leadless pacemakers (LCPs), significantly enhancing the therapeutic outcomes for conditions, such as bradycardia. However, the characteristics of the intracardiac channel are profoundly affected by the heart's rhythmic contractions. Accurately understanding the dynamic transmission mechanisms and channel parameters under various cardiac pathological states is crucial for enhancing the multichamber pacing functionality of LCPs. In this article, the relationship between cardiac chamber volume and channel impedance is mapped based on the electrocardiogram (ECG) data. This mapping enables precise, real-time adjustments to variable impedance, simulating the impedance changes occurring with each heartbeat. Through this approach, a time-frequency equivalent circuit phantom is proposed to accurately simulate channel characteristics for various pacemaker indications (PIs). Utilizing a quasi-dual-pump structural analogy to the heart, we designed a dynamic experimental measurement platform capable of simulating the cardiac beating process under various PIs, which is employed to validate the accuracy of the circuit phantom. The results demonstrate that the correlation coefficients in the frequency and time domains are greater than 0.9432 and 0.9150, respectively, with a time-domain consistency coefficient of less than 3.25. Through cross validation in both frequency and time domains, the circuit effectively simulates the channel characteristics of normal and PI hearts. The empirical formula established based on the time-domain measurement results can be utilized for the rapid estimation of the right atrium (RA)-right ventricle (RV) channel characteristics. The proposed phantom offers a highly accurate and reproducible experimental method for the design of intracardiac communication transceivers, advancing the development and validation of leadless multichamber pacemaker systems.
Keyword ：
Conductive intracardiac communication (CIC) Conductive intracardiac communication (CIC) intracardiac circuit phantom intracardiac circuit phantom leadless pacemakers (LCPs) leadless pacemakers (LCPs) pacemaker indications (PIs) pacemaker indications (PIs)
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| GB/T 7714 | Li, Dongming , Wang, Jiamei , Wang, Han et al. A Dynamic High-Fidelity Equivalent Circuit Phantom for Intracardiac Communication in Pacemaker Indications [J]. | IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT , 2025 , 74 . |
| MLA | Li, Dongming et al. "A Dynamic High-Fidelity Equivalent Circuit Phantom for Intracardiac Communication in Pacemaker Indications" . | IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT 74 (2025) . |
| APA | Li, Dongming , Wang, Jiamei , Wang, Han , Huang, Xiaojiang , Yang, Jiejie , Gao, Yueming et al. A Dynamic High-Fidelity Equivalent Circuit Phantom for Intracardiac Communication in Pacemaker Indications . | IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT , 2025 , 74 . |
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Leadless pacemakers (LCPs) have emerged as a viable solution to mitigate the side effects associated with traditional pacing leads. Nevertheless, the absence of suitable intracardiac communication methods restricts most LCPs to single-chamber pacing. Galvanic conductive communication (GCC) offers a promising approach for achieving intracardiac communication in multichamber LCPs. However, impedance mismatch between the receiver and myocardium during the cardiac cycle can lead to a reduction in path gain, thereby affecting communication stability. This article proposed a dynamic compensation method to reduce impedance mismatch and enhance communication stability. We developed a simplified LCP system with dynamic path gain compensation and validated it on an ex vivo porcine heart dynamic experimental platform. The results demonstrated a path gain improvement of 9.23 dB and a reduction in path gain variation from 3.95 to 0.3 dB. Additionally, the bit error rate (BER) decreased by over 50% across various transmission rates, with the most significant improvement observed at 5 kbps, where it decreased by 82.7%. These findings provide a high-reliability solution for intracardiac communication and establish a foundation for future multichamber sequential pacing applications in LCPs.
Keyword ：
Dynamic compensation Dynamic compensation galvanic conductive communications (GCCs) galvanic conductive communications (GCCs) impedance matching impedance matching leadless pacemakers (LCPs) leadless pacemakers (LCPs)
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| GB/T 7714 | Li, Dongming , Wang, Zhijiong , Wang, Han et al. Dynamic Path Gain Compensation for Enhancing Intracardiac Communication in Leadless Pacemakers [J]. | IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT , 2025 , 74 . |
| MLA | Li, Dongming et al. "Dynamic Path Gain Compensation for Enhancing Intracardiac Communication in Leadless Pacemakers" . | IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT 74 (2025) . |
| APA | Li, Dongming , Wang, Zhijiong , Wang, Han , Hang Pun, Sio , Un Mak, Peng , Zhang, Anguo et al. Dynamic Path Gain Compensation for Enhancing Intracardiac Communication in Leadless Pacemakers . | IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT , 2025 , 74 . |
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Abstract ：
Intracardiac wireless communication is crucial for the development of multi-chamber leadless cardiac pacemakers (LCP). However, the time-varying characteristics of intracardiac channel pose major challenges. As such, mastering the dynamic conduction properties of the intracardiac channel and modeling the equivalent time-varying channel are imperative for realizing LCP multi-chamber pacing. In this article, we present a limiting volume variational approach based on the electrical properties of cardiac tissues and trends in chamber volume variation. This approach was used to establish a quasi-static and a continuous time-varying equivalent circuit model of an intracardiac channel. An equivalence analysis was conducted on the model, and a discrete time-varying equivalent circuit phantom grounded on the cardiac cycle was subsequently established. Moreover, an ex vivo cardiac experimental platform was developed for verification. Results indicate that in the frequency domain, the congruence between phantom and ex vivo experimental outcomes is as high as 94.3%, affirming the reliability of the equivalent circuit model. In the time domain, the correlation is up to 75.3%, corroborating its effectiveness. The proposed time-varying equivalent circuit model exhibits stable and standardized dynamic attributes, serving as a powerful tool for addressing time-varying challenges and simplifying in vivo or ex vivo experiments.
Keyword ：
Blood Blood Equivalent circuits Equivalent circuits Frequency measurement Frequency measurement Heart Heart Integrated circuit modeling Integrated circuit modeling intracardiac circuit phantom intracardiac circuit phantom Intracardiac communication Intracardiac communication leadless pacemakers leadless pacemakers Myocardium Myocardium Pacemakers Pacemakers time-varying equivalent model time-varying equivalent model
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| GB/T 7714 | Wei, Ziliang , Wang, Han , Li, Dongming et al. A Time-Varying Equivalent Circuit Modeling and Measuring Approach for Intracardiac Communication in Leadless Pacemakers [J]. | IEEE TRANSACTIONS ON BIOMEDICAL CIRCUITS AND SYSTEMS , 2024 , 18 (4) : 872-884 . |
| MLA | Wei, Ziliang et al. "A Time-Varying Equivalent Circuit Modeling and Measuring Approach for Intracardiac Communication in Leadless Pacemakers" . | IEEE TRANSACTIONS ON BIOMEDICAL CIRCUITS AND SYSTEMS 18 . 4 (2024) : 872-884 . |
| APA | Wei, Ziliang , Wang, Han , Li, Dongming , Vai, Mang, I , Pun, Sio Hang , Yang, Jiejie et al. A Time-Varying Equivalent Circuit Modeling and Measuring Approach for Intracardiac Communication in Leadless Pacemakers . | IEEE TRANSACTIONS ON BIOMEDICAL CIRCUITS AND SYSTEMS , 2024 , 18 (4) , 872-884 . |
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In this paper a decomposition of isometric high-density surface electromyography (HDsEMG) signals was performed using the blind source separaion (BSS) algorithm. The algorithm is a combination of the modified convolution kernel compensation algorithm and the K-means clustering (kmCKC) algorithm. The obtained decomposition results represent discharge times of the reconstructed motor units. Signals from a publicly available database of high-density surface electromyograms comprising 65 isometric hand gestures were used as input. The movements of the fingers representing the isometric activity of the forearm extensor muscles were selected for decomposition. Five time intervals of muscle activity for a single movement were taken. Decomposition was started separately for each interval. On average, 12.40 +/- 1.14 motor units were successfully reconstructed, with an average pulse-to-noise ratio (PNR) of 18.9272 +/- 2.0383 dB and coefficient of variation of interspike interval (CoVISI) of 0.4298 +/- 0.0383. The average firing rate was 12.3723 +/- 3.7259 pps. The expected number of reconstructed motor units for the extensor muscle and the theoretical average firing rate are in accordance with the obtained results. In addition to using the metrics themselves, visual inspection of the motor units also provides additional validation. The mentioned motor units appear visually credible, and the PNR and CoVISI metrics confirm this. The overall conclusion is that the decomposition was successfully performed and that the algorithm proved to be reliable and robust enough.
Keyword ：
Blind Source Separation (BSS) Blind Source Separation (BSS) Convolution Kernel Compensation with K-means Clustering (kmCKC) Convolution Kernel Compensation with K-means Clustering (kmCKC) High Density Surface Electromyography (HDsEMG) High Density Surface Electromyography (HDsEMG) Motor unit firing times Motor unit firing times
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| GB/T 7714 | Krmek, Simun , Cifrek, Mario , Gao, Yueming et al. Decomposition of HDsEMG Signals Recorded from a Forearm Extensor Muscle Based on Blind Source Separation [J]. | MEDICON 2023 AND CMBEBIH 2023, VOL 1 , 2024 , 93 : 125-134 . |
| MLA | Krmek, Simun et al. "Decomposition of HDsEMG Signals Recorded from a Forearm Extensor Muscle Based on Blind Source Separation" . | MEDICON 2023 AND CMBEBIH 2023, VOL 1 93 (2024) : 125-134 . |
| APA | Krmek, Simun , Cifrek, Mario , Gao, Yueming , Vasic, Zeljka Lucev . Decomposition of HDsEMG Signals Recorded from a Forearm Extensor Muscle Based on Blind Source Separation . | MEDICON 2023 AND CMBEBIH 2023, VOL 1 , 2024 , 93 , 125-134 . |
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Out-to-in (O2I) body wireless communication is crucial for achieving personalized parameter modulation and ensuring reliable cardiac rhythm management in leadless cardiac pacemakers. Compared to traditional radio frequency (RF) wireless communication technology, magnetic resonance coupled human communication (MRC-HBC) technology is a promising method of O2I communication that utilizes human tissue as a conduction medium for electrical signals. In this paper, we present an O2I body communication method that combines low power consumption and high reliability for leadless cardiac pacemakers to enhance the performance of programmed management of leadless cardiac pacemakers (LCPs) and prolong the operating life of the pacemakers. Based on the dielectric properties of human tissues, a transceiver coil was designed for executing O2I body magnetic resonant coupling signal transmission. An O2I body multilayer electromagnetic model for finite element numerical computation was further constructed, and a chest phantom experimental platform was built for mutual verification. The results show that the highest channel gains of simulation and phantom experiment is -35.02 dB @ 13.56 MHz and -27.84 dB @ 13.56 MHz respectively, when the relative distance between the transceiver coils is in the range of 8-12 cm, which represents a significant advantage over the RF wireless communication methods used in previous studies.
Keyword ：
leadless pacemakers leadless pacemakers magnetic resonant coupling magnetic resonant coupling programmable control programmable control wireless communication wireless communication
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| GB/T 7714 | Yang, Shuang , Wei, Ziliang , Chen, Lina et al. A Preliminary Exploration of Magnetic Resonance Coupled Human Body Communication in Out-to-In Body Transmission for Leadless Pacemakers [J]. | 2024 IEEE INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND VIRTUAL ENVIRONMENTS FOR MEASUREMENT SYSTEMS AND APPLICATIONS, CIVEMSA 2024 , 2024 . |
| MLA | Yang, Shuang et al. "A Preliminary Exploration of Magnetic Resonance Coupled Human Body Communication in Out-to-In Body Transmission for Leadless Pacemakers" . | 2024 IEEE INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND VIRTUAL ENVIRONMENTS FOR MEASUREMENT SYSTEMS AND APPLICATIONS, CIVEMSA 2024 (2024) . |
| APA | Yang, Shuang , Wei, Ziliang , Chen, Lina , Liu, Hanyue , Pun, Sio Hang , Vai, Mang, I et al. A Preliminary Exploration of Magnetic Resonance Coupled Human Body Communication in Out-to-In Body Transmission for Leadless Pacemakers . | 2024 IEEE INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND VIRTUAL ENVIRONMENTS FOR MEASUREMENT SYSTEMS AND APPLICATIONS, CIVEMSA 2024 , 2024 . |
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Transcutaneous auricular vagus nerve stimulation (taVNS), in addition to its application in treating specific disorders such as epilepsy, has shown promise in aiding the functional rehabilitation of the upper limb. Most patients with upper limb dysfunction have brain lesions and structural damage to brain networks. By conducting structural analysis of brain networks through electroencephalogram (EEG), we can investigate the effects of taVNS on the cortex directly from the source of the disease, offering a unique, bioelectrical perspective. To investigate the impact of taVNS on the neuromodulated upstream brain structures and to analyze the correlation between taVNS and the functional rehabilitation of the upper limbs, we proposed an analytical approach incorporating the network structure analysis. We conducted power spectra and phase lag index (PLI) calculations on experimentally collected EEG data and further analyzed network topology using graph theory. The results showed that compared with prestimulation, the relative power decreased in low frequencies and increased in high frequencies ( p < 0.05 ). In the alpha frequency band, the PLI showed an increasing trend ( p = 0.03), the minimum spanning tree (MST) analysis showed that the network topology became more integrated, and there were no regular changes observed in the control data ( p > 0.05). In this work, we found that taVNS activates cortical motor areas and leads to stable changes in PLI and network structure in the alpha frequency band. The mechanisms through which taVNS modulates the power spectrum, alters connectivity, and enhances network structure integration in rehabilitation therapy have been revealed as having a positive impact on motor function recovery, providing valuable implications for the clinical application of taVNS in upper limb functional rehabilitation.
Keyword ：
Electroencephalogram (EEG) Electroencephalogram (EEG) Electroencephalography Electroencephalography Epilepsy Epilepsy minimum spanning tree (MST) minimum spanning tree (MST) Network topology Network topology Pain Pain phase lag index (PLI) phase lag index (PLI) Sensors Sensors Spectral analysis Spectral analysis Stroke (medical condition) Stroke (medical condition) transcutaneous auricular vagus nerve stimulation (taVNS) transcutaneous auricular vagus nerve stimulation (taVNS)
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| GB/T 7714 | Ma, Wei , Xu, Peitao , Xu, Pan et al. Exploring the Physiological Effect of taVNS on Upper Limb Functional Rehabilitation [J]. | IEEE SENSORS JOURNAL , 2024 , 24 (7) : 10691-10699 . |
| MLA | Ma, Wei et al. "Exploring the Physiological Effect of taVNS on Upper Limb Functional Rehabilitation" . | IEEE SENSORS JOURNAL 24 . 7 (2024) : 10691-10699 . |
| APA | Ma, Wei , Xu, Peitao , Xu, Pan , Zhou, Junwei , Vasic, Zeljka Lucev , Cifrek, Mario et al. Exploring the Physiological Effect of taVNS on Upper Limb Functional Rehabilitation . | IEEE SENSORS JOURNAL , 2024 , 24 (7) , 10691-10699 . |
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Real -time emotion recognition via wearable devices is a pivotal component of health monitoring and human- computer interaction. To realize this objective, a spiking feed-forward neural networks (SFNNs) model was developed, which leverages six physiological signals from the psychophysiology of positive and negative emotions (POPANE) dataset to construct feature vectors. By converting well-trained artificial neural networks (ANNs) to spiking neural networks (SNNs) and employing weight normalization techniques, the SFNNs with data-based normalization achieved a maximum classification accuracy of 88.17% at a maximum input firing rate of 1000 Hz. In comparison to existing models, the SFNNs model integrates multimodal physiological signals to classify six discrete emotions, demonstrating high classification performance and rapid convergence speed, rendering it ideal for real -time emotion recognition. This work has potential applications in psychological diagnosis and medical rehabilitation through the use of wearable wristbands.
Keyword ：
Emotion recognition Emotion recognition Feature extraction Feature extraction Multimodal physiological signals Multimodal physiological signals Spiking feed-forward neural networks Spiking feed-forward neural networks Time series Time series Wearable wristbands Wearable wristbands
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| GB/T 7714 | Yang, Xudong , Yan, Hongli , Zhang, Anguo et al. Emotion recognition based on multimodal physiological signals using spiking feed-forward neural networks [J]. | BIOMEDICAL SIGNAL PROCESSING AND CONTROL , 2024 , 91 . |
| MLA | Yang, Xudong et al. "Emotion recognition based on multimodal physiological signals using spiking feed-forward neural networks" . | BIOMEDICAL SIGNAL PROCESSING AND CONTROL 91 (2024) . |
| APA | Yang, Xudong , Yan, Hongli , Zhang, Anguo , Xu, Pan , Pan, Sio Hang , Vai, Mang I. et al. Emotion recognition based on multimodal physiological signals using spiking feed-forward neural networks . | BIOMEDICAL SIGNAL PROCESSING AND CONTROL , 2024 , 91 . |
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This article presents a novel millimeter-wave (mm-wave) radar-based continuous motion detection approach called mmCMD for the long-term care of the elderly. The proposed mmCMD visualizes the micro-Doppler signatures of continuous motions generated from millimeter radar as images, which are then analyzed by an object detection network for continuous motion detection. To improve the imaging quality of micro-Doppler signatures, a dynamic feature visualization (DFV) method is proposed by selectively mapping the micro-Doppler matrix (MDM) elements with significant values, highlighting human motion to enhance subsequent detection network's accuracy in capturing the details of the motion. Furthermore, a novel detection network is designed for the visualized micro-Doppler images by combining the specially designed fusion squeeze-and-excitation (FSE) module with the coordinate attention (CA) into the YOLOv5 architecture, which is distinct from prior works that overlook global contextual information. Experimental results demonstrate that the proposed mmCMD achieves a mean average precision (mAP) of 93% at the intersection over union (IoU) thresholds from 0.5 to 0.95 and an F1 score of 99% for 12 actions, which makes it a promising solution for remotely monitoring and detecting elderly individuals' activities to enhance safety and risk prevention capabilities.
Keyword ：
Continuous human motion detection Continuous human motion detection frequency-modulated continuous-wave (FMCW) radar frequency-modulated continuous-wave (FMCW) radar micro-Doppler effect micro-Doppler effect object detection object detection YOLOv5 YOLOv5
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| GB/T 7714 | Xu, Zhimeng , Ding, Junyin , Zhang, Shanshan et al. mmCMD: Continuous Motion Detection From Visualized Radar Micro-Doppler Signatures Using Visual Object Detection Techniques [J]. | IEEE SENSORS JOURNAL , 2024 , 24 (3) : 3394-3405 . |
| MLA | Xu, Zhimeng et al. "mmCMD: Continuous Motion Detection From Visualized Radar Micro-Doppler Signatures Using Visual Object Detection Techniques" . | IEEE SENSORS JOURNAL 24 . 3 (2024) : 3394-3405 . |
| APA | Xu, Zhimeng , Ding, Junyin , Zhang, Shanshan , Gao, Yueming , Chen, Liangqin , Vasic, Zeljka Lucev et al. mmCMD: Continuous Motion Detection From Visualized Radar Micro-Doppler Signatures Using Visual Object Detection Techniques . | IEEE SENSORS JOURNAL , 2024 , 24 (3) , 3394-3405 . |
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ElectricalImpedance Myography (EIM) is an innovative, non-invasive technique offering a convenient means of localized exogenous electrophysiological recording. By measuring muscle impedance parameters, this method characterizes the physiological state of muscles, functioning as a biomarker for muscle contractility, injuries, and the progression of neuromuscular diseases. This paper provides an overview of the current state of EIM technology development, along with modeling and data analysis methods, focusing on their application requirements. It further highlights the advancements in EIM research within the realm of sports health, emphasizing its efficacy in identifying injuries and monitoring wound healing, and discusses existing technological limitations. Additionally, the paper explores future research directions. Serving as a transient biosensor during physical activity, EIM holds significant potential in sports health. It presents a promising alternative to invasive and costly clinical assessment methods, positioning itself as a viable personal monitoring tool for both professional athletes and fitness enthusiasts. Nevertheless, the resolution of technical challenges and the establishment of industry-standard implementation programs are essential prerequisites for EIM to evolve into a standard clinical assessment tool.
Keyword ：
Clinical assessment tool Clinical assessment tool electrical impedance myography electrical impedance myography electrophysiological recording electrophysiological recording muscle physiological state muscle physiological state sports health sports health
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| GB/T 7714 | Xu, Pan , Zhou, Junwei , Chen, Zhizhang et al. Advancements and Challenges in Electrical Impedance Myography (EIM): A Comprehensive Overview of Technology Development, Applications in Sports Health, and Future Directions [J]. | IEEE JOURNAL OF MICROWAVES , 2024 , 4 (4) : 605-625 . |
| MLA | Xu, Pan et al. "Advancements and Challenges in Electrical Impedance Myography (EIM): A Comprehensive Overview of Technology Development, Applications in Sports Health, and Future Directions" . | IEEE JOURNAL OF MICROWAVES 4 . 4 (2024) : 605-625 . |
| APA | Xu, Pan , Zhou, Junwei , Chen, Zhizhang , Yang, Xudong , Yan, Hongli , Vasic, Zeljka Lucev et al. Advancements and Challenges in Electrical Impedance Myography (EIM): A Comprehensive Overview of Technology Development, Applications in Sports Health, and Future Directions . | IEEE JOURNAL OF MICROWAVES , 2024 , 4 (4) , 605-625 . |
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