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检索条件"任意字段=International Congress on Image and Signal Processing, BioMedical Engineering and Informatics"

共 2036 条记录，以下是51-60 订阅

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LRCu: A High-Performance Parallel Program for Identifying Hub Genes 17

LRCu: A High-Performance Parallel Program for Identifying Hu...

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17th international congress on image and signal processing, biomedical engineering and informatics, CISP-BMEI 2024

作者： Liu, Jiaxin Ji, Xinglai Nanjing University of Posts and Telecommunications Smart Health Big Data Analysis and Location Services Engineering Lab of Jiangsu Province Nanjing210003 China Yunnan University State Key Laboratory for Conservation and Utilization of Bio-Resources in Yunan Kunming650091 China

ISBN: (纸本)9798331507398

The LeaderRank algorithm identifies influential nodes using the idea of the random walk and performs well in the identification of hub genes in biological networks. The rapid development of biological technologies promotes the evolution of networks to be highly complex and increasing largely in size. In this study, we introduce LRCu, for computing LeaderRank using CUDA, to identify hub genes. The results show that the parallel implementation is highly effective and achieves a speedup of more than 42 times for a 13,000-gene network, thereby enhancing large-scale network computation. © 2024 IEEE.

关键词： CUDA gene co-expression network hub gene parallel computing

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Non-Contact Respiratory Rate Measurement via Visible Camera Based on the Demodulation of Remote Photoplethysmography signal 17

Non-Contact Respiratory Rate Measurement via Visible Camera ...

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17th international congress on image and signal processing, biomedical engineering and informatics, CISP-BMEI 2024

作者： Li, Yuanhui Chen, Zhiqiang Chen, Yuguo Xu, Feng Wang, Jiali Guo, Yafei Li, Ke The Institute of Intelligent Medical Engineering School of Control Science and Engineering Shandong University Department of Biomedical Engineering Jinan China Qilu Hospital Shandong University Department of Emergency Jinan China Imperial College London Department of Life Science United Kingdom

ISBN: (纸本)9798331507398

Respiratory rate measurement is a critical component of health monitoring. Among the existing methods of respiratory rate measurement, visualization is often time-consuming and unsuitable for real-time monitoring while wearable devices can cause discomfort due to their contact with the body. In this study, we propose a novel respiratory rate measurement method based on remote photoplethysmography signal demodulation, utilizing a visible light camera as the measurement device to achieve real-time and comfortable respiratory measurement. To validate the performance of the algorithm, we conducted experiments capturing video and real respiration signals from 31 subjects. The results indicate a mean error of -0.4382 breaths per minute (bpm), a mean absolute error of 2.1012 bpm and a root mean square error of 2.6828 bpm. The respiratory rates measured by our proposed method demonstrated good consistency with the true values. © 2024 IEEE.

关键词： Demodulation

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SFM-IQA: A Hierarchical Model for image Quality Assessment via Optimization-Based Meta Learning 17

SFM-IQA: A Hierarchical Model for Image Quality Assessment v...

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17th international congress on image and signal processing, biomedical engineering and informatics, CISP-BMEI 2024

作者： Shi, Zaifeng Kang, Tai Wang, Yunfeng Xiao, Yunze Luo, Tao School of Microelectronics Tianjin University Tianjin300072 China Tianjin Key Laboratory of Imaging and Sensing Microelectronic Technology Tianjin300072 China College of Intelligence and Computing Tianjin University Tianjin300072 China

ISBN: (纸本)9798331507398

Training data-driven IQA models is trapped in large size datasets, and when assessing authentic images with unknown distortion types, insufficient labeled data can lead to the decrease in the prediction accuracy. Therefore, a model named SFM-IQA that uses gradient optimization is proposed for authentic image assessment scenarios. A meta learning framework in this model is developed to acquire the prior knowledge shared by different kinds of distortions, so as to adapt to unknown distortions. A Swin hierarchical extractor is used to extract global and local quality-aware features to characterize distortions. In order to make full use of features at different scales to enhance the feature representation, a multi-scale fusion module is designed. On LIVEC and KonIQ-10k, the proposed model achieved SROCC of 0.894 and 0.933 respectively. The result demonstrates that the proposed model outperforms other state-of-art IQA metrics. © 2024 IEEE.

关键词： image quality

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Impact of Approximate QRS Identification on RR Interval-Based Arrhythmia Detection and Classification 17

Impact of Approximate QRS Identification on RR Interval-Base...

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17th international congress on image and signal processing, biomedical engineering and informatics, CISP-BMEI 2024

作者： Nagatomo, Taiki Sato, Toshinori Graduate School of Engineering Fukuoka University Department of Electronics Engineering and Computer Science Japan Faculty of Engineering Fukuoka University Department of Electronics Engineering and Computer Science Japan

ISBN: (纸本)9798331507398

Wearable devices for arrhythmia diagnosis are battery-powered and require improved power efficiency. In our previous study, we applied approximate computing, which is effective for power reduction, to QRS identification algorithm and achieved significant power reduction. However, the impact of this approximation on arrhythmia detection and classification was not fully investigated. In this study, we investigate how the approximation - - specifically, the use of two approximate multipliers and eight approximate squarers applied to the Pan-Tompkins algorithm - - affects RR interval-based arrhythmia detection and classification. We use 48 samples from the MIT-BIH Arrhythmia Database to evaluate the accuracy of arrhythmia detection and classification. It was found that the approximate multiplier mul16s_GQU is the best choice, achieving nearly 100% accuracy and less than 1 % false negatives in abnormal/normal classification. Additionally, the most power-efficient approximate squarer, E10C1, achieves relatively high accuracy with less than 5 % false negatives. © 2024 IEEE.

关键词： approximate computing arrhythmia biomedical electronics electrocardiogram QRS complex

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GMTI with Multi-channel SAR Based on the MUSIC Technique 16

GMTI with Multi-channel SAR Based on the MUSIC Technique

引用

16th international congress on image and signal processing, biomedical engineering and informatics, CISP-BMEI 2023

作者： Tian, Yongbo Wang, Junfeng Shanghai Jiao Tong University Department of Electronic Engineering Shanghai China

ISBN: (纸本)9798350330755

This paper proposes an algorithm for ground moving target indication (GMTI) with multi-channel synthetic aperture radar (SAR) based on the multiple signal classification (MUSIC) technique. First, the images of different channels are registered in position and equalized in phase. Then, the MUSIC technique is used to estimate the spatial frequency and the intensity of the strongest scatterer at each pixel, and the spatial frequencies and the intensities are used to generate the feature image. Finally, a constant false alarm rate (CFAR) method is used to extract moving targets from the feature image. The results of simulated data and field data demonstrate the excellent performance of this algorithm, especially for the scenes with high clutter and high noise. © 2023 IEEE.

关键词： Multiple signal classification

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A 40nm CMOS Ultra-Wide Output Power Range Bluetooth RF Front-End for Hydropower Management System 17

A 40nm CMOS Ultra-Wide Output Power Range Bluetooth RF Front...

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17th international congress on image and signal processing, biomedical engineering and informatics, CISP-BMEI 2024

作者： Wu, Yifan Yuan, Yongbin Diao, Shengxi Zhang, Ni Liu, Haodong School of Communication and Electronic Engineering East China Normal University Shanghai200241 China Seschip Technology Co. LTD China

ISBN: (纸本)9798331507398

This article presents a Bluetooth Low Energy (BLE) Transceiver RF front-end with low power consumption and ultra-wide controllable output power range. The receiver includes a low-noise amplifier (LNA) followed by four-phase passive mixers and a trans-impedance amplifier (TIA). The transmitter has a direct upconversion architecture, including a double-balanced mixer and a Class E power amplifier (PA) with ultra-wide output power range. Implemented in 40-nm CMOS, the LNA exhibits a gain of more than 20-dB, a noise figure of 3.6-dB, an Input Third Order Intercept Point (IIP3) of -17dBm, over a frequency range of 2.4 to 2.5 GHz. The passive mixers are driven by 25% duty-cycle, non-overlapping quadrature local oscillator (LO). The wide output power range of -50dBm to 10dBm adapts to the 60dBc changes of signal strength. © 2024 IEEE.

关键词： CMOS integrated circuits

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A Dual-path Interactive ECG Denoising Algorithm 17

A Dual-path Interactive ECG Denoising Algorithm

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17th international congress on image and signal processing, biomedical engineering and informatics, CISP-BMEI 2024

作者： Zhang, Xiuxin Chen, Meng Li, Yongjian Gao, Jiahui Sun, Yiheng Liu, Feifei Wei, Shoushui School of Control Science and Engineering Shandong University Jinan China School of Science Shandong Jianzhu University Jinan China

ISBN: (纸本)9798331507398

Denoising of dynamic electrocardiography (ECG) is a hotspot in ECG processing. Existing denoising methods mainly target single-lead signals or single noise sources, with limited research addressing mixed noise across multiple leads. To address the aforementioned issues, this study proposes a Dual-Path Interactive Denoising Autoencoder (DP-IDAE). The Convolutional Local Denoising Path (CL-Path) of DP-IDAE employs convolutional operations to extract local features of the ECG signal, while the Temporal Global Denoising Path (TG-Path) utilizes bidirectional Long Short-Term Memory networks to capture the signal's temporal global features. Additionally, an Interactive Communication Mechanism (ICM) based on the attention mechanism is proposed to facilitate the exchange of information between the different features of the two paths. The model was tested on denoising performance under different input signal-to-noise ratios for seven types of noise, including single and mixed noise sources comprising baseline wander (BW), muscle artifact (MA), and electrode motion (EM), which are common noise sources in ECG signals. In the MIT-BIH Arrhythmia Database (MLII lead), experimental results demonstrate the superiority of DP-IDAE in ECG signal denoising. Additionally, the study investigates the relationship between denoising effects and signal similarity of different lead ECG, demonstrating excellent cross-lead generalization performance. © 2024 IEEE.

关键词： Convolutional neural networks

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M-ary Spread Spectrum OFDM Hybrid Transmission with Multiple Subsets of Different Length Sequences 17

M-ary Spread Spectrum OFDM Hybrid Transmission with Multiple...

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17th international congress on image and signal processing, biomedical engineering and informatics, CISP-BMEI 2024

作者： Zhang, Zhenyu Xuan, Guixin Zhang, Hongde Gong, Xuejiao Zhang, Xiaobo Cao, Chengkun Army Engineering University of PLA Communication Petty Officer Academy Chongqing China

ISBN: (纸本)9798331507398

Based on multiple subsets with different length sequences, a novel hybrid transmission method for M-ary spread spectrum (MSS) orthogonal frequency division multiplexing (OFDM) systems is presented. Similar to traditional methods for MSS-OFDM transmission, orthogonality property will be preserved. However, due to the mixing of multiple subsets of sequences with different lengths, MSS-OFDM systems with hybrid transmission will obtain a higher data rate and more flexible subcarrier parameter settings. The data rate can be increased to several times of the traditional methods, and the number of subcarriers for MSS-OFDM transmission systems can be expanded from an integer power of 2 to a multiple of 4. At the same time, with the improvement of the above performance, the processing gain and peak-to-average power ratio properties of MSS-OFDM transmission system will decrease. © 2024 IEEE.

关键词： Orthogonal frequency division multiplexing

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Sensorimotor Integration Mechanism for Precise Grasping Movements in Mixed Reality Environments 17

Sensorimotor Integration Mechanism for Precise Grasping Move...

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17th international congress on image and signal processing, biomedical engineering and informatics, CISP-BMEI 2024

作者： Zhuang, Ji Liu, Mengqi Cui, Xi Guo, Yafei Li, Ke Institute of Intelligent Medical Engineering School of Control Science and Engineering Shandong University Laboratory of Rehabilitation Engineering Jinan China Imperial College London Department of Life Science United Kingdom

ISBN: (纸本)9798331507398

The mechanism of sensorimotor integration involves how the brain integrates multisensory information to form a unified perception of movement and space. Precision grasping, a hand function unique to humans, is the foundation for various dexterous manipulations. However, the sensorimotor integration mechanism underlying precision grasping remains unclear, particularly when there is a discrepancy between visual and tactile information. This study aims to develop an immersive mixed-reality-based precision grasping control system, synchronously collecting multiple physiological signals to reveal the control mechanisms of precision grasping from two perspectives: central-peripheral coordination and perception-movement coupling. The results show that during precision grasping, conflicts between visual and tactile perception induce differences in oscillatory activity across multiple brain regions (p © 2024 IEEE.

关键词： Sensory feedback

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A Hybrid CNN-LSTM Framework and Infrared image processing for Solar Irradiance Forecasting 17

A Hybrid CNN-LSTM Framework and Infrared Image Processing fo...

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17th international congress on image and signal processing, biomedical engineering and informatics, CISP-BMEI 2024

作者： Nijhum, Ifran Rahman Hossain, Md Yearat Akinola, Toluwabori Rakib, Md Mahbub Hasan Dev, Soumyabrata North South University Dhaka Bangladesh The ADAPT SFI Research Centre Dublin Ireland School of Computer Science University College Dublin Dublin Ireland Beijing-Dublin International College Beijing China

ISBN: (纸本)9798331507398

Accurate solar irradiance forecasting is crucial for optimizing photovoltaic power generation, especially given the intermittent nature of solar energy. This paper proposes a novel framework for short-term solar irradiance forecasting using low-resolution infrared (IR) sky images. By leveraging bicubic interpolation and OpenCV colormaps, the framework enhances the quality of IR images, providing better inputs to a Convolutional Neural Network (CNN)-based nowcasting model, which is followed by a Long Short-Term Memory (LSTM) model for univariate solar forecasting. Key results indicate that the proposed method reduces the Root Mean Squared Error (RMSE) from 47.24 W/m2 to 33.51 W/m2. Extensive evaluations demonstrate that image processing techniques significantly improve forecasting accuracy compared to baseline models using raw IR images. © 2024 IEEE.

关键词： Solar irradiance

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