生物医学工程学杂志最新文献_第6页

[Gesture accuracy recognition based on grayscale image of surface electromyogram signal and multi-view convolutional neural network].

生物医学工程学杂志 Pub Date : 2024-12-25 DOI: 10.7507/1001-5515.202309007

Qingzheng Chen, Qing Tao, Xiaodong Zhang, Xuezheng Hu, Tianle Zhang

{"title":"[Gesture accuracy recognition based on grayscale image of surface electromyogram signal and multi-view convolutional neural network].","authors":"Qingzheng Chen, Qing Tao, Xiaodong Zhang, Xuezheng Hu, Tianle Zhang","doi":"10.7507/1001-5515.202309007","DOIUrl":"10.7507/1001-5515.202309007","url":null,"abstract":"This study aims to address the limitations in gesture recognition caused by the susceptibility of temporal and frequency domain feature extraction from surface electromyography signals, as well as the low recognition rates of conventional classifiers. A novel gesture recognition approach was proposed, which transformed surface electromyography signals into grayscale images and employed convolutional neural networks as classifiers. The method began by segmenting the active portions of the surface electromyography signals using an energy threshold approach. Temporal voltage values were then processed through linear scaling and power transformations to generate grayscale images for convolutional neural network input. Subsequently, a multi-view convolutional neural network model was constructed, utilizing asymmetric convolutional kernels of sizes 1 × n and 3 × n within the same layer to enhance the representation capability of surface electromyography signals. Experimental results showed that the proposed method achieved recognition accuracies of 98.11% for 13 gestures and 98.75% for 12 multi-finger movements, significantly outperforming existing machine learning approaches. The proposed gesture recognition method, based on surface electromyography grayscale images and multi-view convolutional neural networks, demonstrates simplicity and efficiency, substantially improving recognition accuracy and exhibiting strong potential for practical applications.","PeriodicalId":39324,"journal":{"name":"生物医学工程学杂志","volume":"41 6","pages":"1153-1160"},"PeriodicalIF":0.0,"publicationDate":"2024-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11955366/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143504588","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

[A study on post-traumatic stress disorder classification based on multi-atlas multi-kernel graph convolutional network].

生物医学工程学杂志 Pub Date : 2024-12-25 DOI: 10.7507/1001-5515.202407031

Lijun Zhou, Hongru Zhu, Yunfei Liu, Xian Mo, Jun Yuan, Changyu Luo, Junran Zhang

{"title":"[A study on post-traumatic stress disorder classification based on multi-atlas multi-kernel graph convolutional network].","authors":"Lijun Zhou, Hongru Zhu, Yunfei Liu, Xian Mo, Jun Yuan, Changyu Luo, Junran Zhang","doi":"10.7507/1001-5515.202407031","DOIUrl":"10.7507/1001-5515.202407031","url":null,"abstract":"Post-traumatic stress disorder (PTSD) presents with complex and diverse clinical manifestations, making accurate and objective diagnosis challenging when relying solely on clinical assessments. Therefore, there is an urgent need to develop reliable and objective auxiliary diagnostic models to provide effective diagnosis for PTSD patients. Currently, the application of graph neural networks for representing PTSD is limited by the expressiveness of existing models, which does not yield optimal classification results. To address this, we proposed a multi-graph multi-kernel graph convolutional network (MK-GCN) model for classifying PTSD data. First, we constructed functional connectivity matrices at different scales for the same subjects using different atlases, followed by employing the k-nearest neighbors algorithm to build the graphs. Second, we introduced the MK-GCN methodology to enhance the feature extraction capability of brain structures at different scales for the same subjects. Finally, we classified the extracted features from multiple scales and utilized graph class activation mapping to identify the top 10 brain regions contributing to classification. Experimental results on seismic-induced PTSD data demonstrated that our model achieved an accuracy of 84.75%, a specificity of 84.02%, and an AUC of 85% in the classification task distinguishing between PTSD patients and non-affected subjects. The findings provide robust evidence for the auxiliary diagnosis of PTSD following earthquakes and hold promise for reliably identifying specific brain regions in other PTSD diagnostic contexts, offering valuable references for clinicians.","PeriodicalId":39324,"journal":{"name":"生物医学工程学杂志","volume":"41 6","pages":"1110-1118"},"PeriodicalIF":0.0,"publicationDate":"2024-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11955359/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143504083","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

[Research progress on endoscopic image diagnosis of gastric tumors based on deep learning].

生物医学工程学杂志 Pub Date : 2024-12-25 DOI: 10.7507/1001-5515.202404004

Yuan Gao, Guohui Wei

引用次数: 0

[Study on the regulatory effect of low intensity retinal ultrasound stimulation on the neural activity of visual cortex].

生物医学工程学杂志 Pub Date : 2024-12-25 DOI: 10.7507/1001-5515.202401047

Qianqian Wang, Yi Yuan, Jiaqing Yan

{"title":"[Study on the regulatory effect of low intensity retinal ultrasound stimulation on the neural activity of visual cortex].","authors":"Qianqian Wang, Yi Yuan, Jiaqing Yan","doi":"10.7507/1001-5515.202401047","DOIUrl":"10.7507/1001-5515.202401047","url":null,"abstract":"Low-intensity ultrasound stimulation of the retina has the ability to modulate neural activity in the primary visual cortex (V1), however, it is currently unclear how different intensities and durations of ultrasonic stimulation of the retina modulate neural activity in V1. In this paper, we recorded local field potential (LFP) signals in the V1 brain region of mice under different ultrasound intensities and different stimulation times. The amplitude of LFP corresponding to 1 s before ultrasound stimulation to 2 s after stimulation (-1-2 s) was analyzed, including the power and sample entropy of delta, theta, alpha beta, and low gamma frequency bands. The experimental results showed that, as the stimulation intensity increased, the peak value of the LFP in the visual cortex showed a linear upward trend; the power in the delta and theta frequency bands showed a linear upward trend, and the sample entropy showed a linear downward trend. With increases of stimulation duration, the peak value of the LFP in the visual cortex showed an upward trend, and the upward trend gradually weakened; the power in the delta frequency band showed an upward trend, the sample entropy showed a linear upward trend, and the sample entropy in the theta frequency band showed a downward trend. The results show that low-intensity ultrasonic stimulation of the retina has a significant modulatory effect on neural activity in the visual cortex. The study provides insights into the mechanisms by which ultrasonic stimulation regulates visual system function. Furthermore, it clarifies the patterns of parameter selection, facilitating the development of personalized multi-parameter modulation for the treatment of visual neural degeneration, retinal disorders and related research areas.","PeriodicalId":39324,"journal":{"name":"生物医学工程学杂志","volume":"41 6","pages":"1161-1168"},"PeriodicalIF":0.0,"publicationDate":"2024-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11955374/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143504716","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

[Reinforcement learning-based method for type B aortic dissection localization]. [基于强化学习的 B 型主动脉夹层定位方法]。

生物医学工程学杂志 Pub Date : 2024-10-25 DOI: 10.7507/1001-5515.202309047

An Zeng, Xianyang Lin, Jingliang Zhao, Dan Pan, Baoyao Yang, Xin Liu

{"title":"[Reinforcement learning-based method for type B aortic dissection localization].","authors":"An Zeng, Xianyang Lin, Jingliang Zhao, Dan Pan, Baoyao Yang, Xin Liu","doi":"10.7507/1001-5515.202309047","DOIUrl":"10.7507/1001-5515.202309047","url":null,"abstract":"In the segmentation of aortic dissection, there are issues such as low contrast between the aortic dissection and surrounding organs and vessels, significant differences in dissection morphology, and high background noise. To address these issues, this paper proposed a reinforcement learning-based method for type B aortic dissection localization. With the assistance of a two-stage segmentation model, the deep reinforcement learning was utilized to perform the first-stage aortic dissection localization task, ensuring the integrity of the localization target. In the second stage, the coarse segmentation results from the first stage were used as input to obtain refined segmentation results. To improve the recall rate of the first-stage segmentation results and include the segmentation target more completely in the localization results, this paper designed a reinforcement learning reward function based on the direction of recall changes. Additionally, the localization window was separated from the field of view window to reduce the occurrence of segmentation target loss. Unet, TransUnet, SwinUnet, and MT-Unet were selected as benchmark segmentation models. Through experiments, it was verified that the majority of the metrics in the two-stage segmentation process of this paper performed better than the benchmark results. Specifically, the Dice index improved by 1.34%, 0.89%, 27.66%, and 7.37% for each respective model. In conclusion, by incorporating the type B aortic dissection localization method proposed in this paper into the segmentation process, the overall segmentation accuracy is improved compared to the benchmark models. The improvement is particularly significant for models with poorer segmentation performance.","PeriodicalId":39324,"journal":{"name":"生物医学工程学杂志","volume":"41 5","pages":"878-885"},"PeriodicalIF":0.0,"publicationDate":"2024-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11527745/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142509903","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

[Research on motion impedance cardiography de-noising method based on two-step spectral ensemble empirical mode decomposition and canonical correlation analysis]. [基于两步谱集合经验模式分解和典型相关分析的运动阻抗心动图去噪方法研究]。

生物医学工程学杂志 Pub Date : 2024-10-25 DOI: 10.7507/1001-5515.202210059

Yao Xie, Dong Yang, Honglong Yu, Qilian Xie

{"title":"[Research on motion impedance cardiography de-noising method based on two-step spectral ensemble empirical mode decomposition and canonical correlation analysis].","authors":"Yao Xie, Dong Yang, Honglong Yu, Qilian Xie","doi":"10.7507/1001-5515.202210059","DOIUrl":"10.7507/1001-5515.202210059","url":null,"abstract":"Impedance cardiography (ICG) is essential in evaluating cardiac function in patients with cardiovascular diseases. Aiming at the problem that the measurement of ICG signal is easily disturbed by motion artifacts, this paper introduces a de-noising method based on two-step spectral ensemble empirical mode decomposition (EEMD) and canonical correlation analysis (CCA). Firstly, the first spectral EEMD-CCA was performed between ICG and motion signals, and electrocardiogram (ECG) and motion signals, respectively. The component with the strongest correlation coefficient was set to zero to suppress the main motion artifacts. Secondly, the obtained ECG and ICG signals were subjected to a second spectral EEMD-CCA for further denoising. Lastly, the ICG signal is reconstructed using these share components. The experiment was tested on 30 subjects, and the results showed that the quality of the ICG signal is greatly improved after using the proposed denoising method, which could support the subsequent diagnosis and analysis of cardiovascular diseases.","PeriodicalId":39324,"journal":{"name":"生物医学工程学杂志","volume":"41 5","pages":"986-994"},"PeriodicalIF":0.0,"publicationDate":"2024-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11527760/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142509906","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

[Research progress of breast pathology image diagnosis based on deep learning]. [基于深度学习的乳腺病理图像诊断研究进展]。

生物医学工程学杂志 Pub Date : 2024-10-25 DOI: 10.7507/1001-5515.202311061

Liang Jiang, Cheng Zhang, Hui Cao, Baihao Jiang

引用次数: 0

[Colon polyp detection based on multi-scale and multi-level feature fusion and lightweight convolutional neural network]. [基于多尺度、多层次特征融合和轻量级卷积神经网络的结肠息肉检测]。

生物医学工程学杂志 Pub Date : 2024-10-25 DOI: 10.7507/1001-5515.202312014

Yiyang Li, Jiayi Zhao, Ruoyi Yu, Huixiang Liu, Shuang Liang, Yu Gu

{"title":"[Colon polyp detection based on multi-scale and multi-level feature fusion and lightweight convolutional neural network].","authors":"Yiyang Li, Jiayi Zhao, Ruoyi Yu, Huixiang Liu, Shuang Liang, Yu Gu","doi":"10.7507/1001-5515.202312014","DOIUrl":"10.7507/1001-5515.202312014","url":null,"abstract":"Early diagnosis and treatment of colorectal polyps are crucial for preventing colorectal cancer. This paper proposes a lightweight convolutional neural network for the automatic detection and auxiliary diagnosis of colorectal polyps. Initially, a 53-layer convolutional backbone network is used, incorporating a spatial pyramid pooling module to achieve feature extraction with different receptive field sizes. Subsequently, a feature pyramid network is employed to perform cross-scale fusion of feature maps from the backbone network. A spatial attention module is utilized to enhance the perception of polyp image boundaries and details. Further, a positional pattern attention module is used to automatically mine and integrate key features across different levels of feature maps, achieving rapid, efficient, and accurate automatic detection of colorectal polyps. The proposed model is evaluated on a clinical dataset, achieving an accuracy of 0.9982, recall of 0.9988, F1 score of 0.9984, and mean average precision (mAP) of 0.9953 at an intersection over union (IOU) threshold of 0.5, with a frame rate of 74 frames per second and a parameter count of 9.08 M. Compared to existing mainstream methods, the proposed method is lightweight, has low operating configuration requirements, high detection speed, and high accuracy, making it a feasible technical method and important tool for the early detection and diagnosis of colorectal cancer.","PeriodicalId":39324,"journal":{"name":"生物医学工程学杂志","volume":"41 5","pages":"911-918"},"PeriodicalIF":0.0,"publicationDate":"2024-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11527748/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142509890","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

[Enhancement algorithm for surface electromyographic-based gesture recognition based on real-time fusion of muscle fatigue features]. [基于肌肉疲劳特征实时融合的表面肌电图手势识别增强算法]。

生物医学工程学杂志 Pub Date : 2024-10-25 DOI: 10.7507/1001-5515.202312023

Shijia Yan, Ye Yang, Peng Yi

{"title":"[Enhancement algorithm for surface electromyographic-based gesture recognition based on real-time fusion of muscle fatigue features].","authors":"Shijia Yan, Ye Yang, Peng Yi","doi":"10.7507/1001-5515.202312023","DOIUrl":"10.7507/1001-5515.202312023","url":null,"abstract":"This study aims to optimize surface electromyography-based gesture recognition technique, focusing on the impact of muscle fatigue on the recognition performance. An innovative real-time analysis algorithm is proposed in the paper, which can extract muscle fatigue features in real time and fuse them into the hand gesture recognition process. Based on self-collected data, this paper applies algorithms such as convolutional neural networks and long short-term memory networks to provide an in-depth analysis of the feature extraction method of muscle fatigue, and compares the impact of muscle fatigue features on the performance of surface electromyography-based gesture recognition tasks. The results show that by fusing the muscle fatigue features in real time, the algorithm proposed in this paper improves the accuracy of hand gesture recognition at different fatigue levels, and the average recognition accuracy for different subjects is also improved. In summary, the algorithm in this paper not only improves the adaptability and robustness of the hand gesture recognition system, but its research process can also provide new insights into the development of gesture recognition technology in the field of biomedical engineering.","PeriodicalId":39324,"journal":{"name":"生物医学工程学杂志","volume":"41 5","pages":"958-968"},"PeriodicalIF":0.0,"publicationDate":"2024-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11527766/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142509893","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

[Functional study of amine oxidase copper-containing 1 (AOC1) in lipid metabolism]. [含铜胺氧化酶 1 (AOC1) 在脂质代谢中的功能研究]。

生物医学工程学杂志 Pub Date : 2024-10-25 DOI: 10.7507/1001-5515.202407066

Siting Xiang, Shenying Liu, Kuangzheng Li, Tongjin Zhao, Xu Wang

{"title":"[Functional study of amine oxidase copper-containing 1 (AOC1) in lipid metabolism].","authors":"Siting Xiang, Shenying Liu, Kuangzheng Li, Tongjin Zhao, Xu Wang","doi":"10.7507/1001-5515.202407066","DOIUrl":"10.7507/1001-5515.202407066","url":null,"abstract":"Amine oxidase copper-containing 1 (AOC1) is a key member of copper amine oxidase family, which is responsible for deamination oxidation of histamine and putrescine. In recent years, AOC1 has been reported to be associated with various cancers, with its expression levels significantly elevated in certain cancer cells, suggesting its potential role in cancer progression. However, its function in lipid metabolism still remains unclear. Through genetic analysis, we have discovered a potential relationship between AOC1 and lipid metabolism. To further investigate, we generated Aoc1 -/- mice and characterized their metabolic phenotypes on both chow diet and high-fat diet (HFD) feeding conditions. On HFD feeding conditions, Aoc1 -/- mice exhibited significantly higher fat mass and impaired glucose sensitivity, and lipid accumulation in white adipose tissue and liver was also increased. This study uncovers the potential role of AOC1 in lipid metabolism and its implications in metabolic disorders such as obesity and type 2 diabetes, providing new targets and research directions for treating metabolic diseases.","PeriodicalId":39324,"journal":{"name":"生物医学工程学杂志","volume":"41 5","pages":"1019-1025"},"PeriodicalIF":0.0,"publicationDate":"2024-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11527758/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142509895","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0