Cyborg and bionic systems (Washington, D.C.)最新文献_第4页

Multi-Section Magnetic Soft Robot with Multirobot Navigation System for Vasculature Intervention. 基于多机器人导航系统的多段磁软机器人血管介入研究。

IF 10.5

Cyborg and bionic systems (Washington, D.C.) Pub Date : 2024-11-28 eCollection Date: 2024-01-01 DOI: 10.34133/cbsystems.0188

Zhengyang Li, Qingsong Xu

{"title":"Multi-Section Magnetic Soft Robot with Multirobot Navigation System for Vasculature Intervention.","authors":"Zhengyang Li, Qingsong Xu","doi":"10.34133/cbsystems.0188","DOIUrl":"10.34133/cbsystems.0188","url":null,"abstract":"Magnetic soft robots have recently become a promising technology that has been applied to minimally invasive cardiovascular surgery. This paper presents the analytical modeling of a novel multi-section magnetic soft robot (MS-MSR) with multi-curvature bending, which is maneuvered by an associated collaborative multirobot navigation system (CMNS) with magnetic actuation and ultrasound guidance targeted for intravascular intervention. The kinematic and dynamic analysis of the MS-MSR's telescopic motion is performed using the optimized Cosserat rod model by considering the effect of an external heterogeneous magnetic field, which is generated by a mobile magnetic actuation manipulator to adapt to complex steering scenarios. Meanwhile, an extracorporeal mobile ultrasound navigation manipulator is exploited to track the magnetic soft robot's distal tip motion to realize a closed-loop control. We also conduct a quadratic programming-based optimization scheme to synchronize the multi-objective task-space motion of CMNS with null-space projection. It allows the formulation of a comprehensive controller with motion priority for multirobot collaboration. Experimental results demonstrate that the proposed magnetic soft robot can be successfully navigated within the multi-bifurcation intravascular environment with a shape modeling error <math><mn>3.62</mn> <mo>±</mo> <msup><mn>1.28</mn> <mo>∘</mo></msup> </math> and a tip error of <math><mn>1.08</mn> <mo>±</mo> <mn>0.45</mn> <mspace></mspace> <mi>mm</mi></math> under the actuation of a CMNS through in vitro ultrasound-guided vasculature interventional tests.","PeriodicalId":72764,"journal":{"name":"Cyborg and bionic systems (Washington, D.C.)","volume":"5 ","pages":"0188"},"PeriodicalIF":10.5,"publicationDate":"2024-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11602701/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142751665","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

Advances in Biointegrated Wearable and Implantable Optoelectronic Devices for Cardiac Healthcare. 用于心脏保健的生物集成可穿戴和植入式光电设备的进展。

IF 10.5

Cyborg and bionic systems (Washington, D.C.) Pub Date : 2024-10-18 eCollection Date: 2024-01-01 DOI: 10.34133/cbsystems.0172

Cheng Li, Yangshuang Bian, Zhiyuan Zhao, Yunqi Liu, Yunlong Guo

{"title":"Advances in Biointegrated Wearable and Implantable Optoelectronic Devices for Cardiac Healthcare.","authors":"Cheng Li, Yangshuang Bian, Zhiyuan Zhao, Yunqi Liu, Yunlong Guo","doi":"10.34133/cbsystems.0172","DOIUrl":"10.34133/cbsystems.0172","url":null,"abstract":"With the prevalence of cardiovascular disease, it is imperative that medical monitoring and treatment become more instantaneous and comfortable for patients. Recently, wearable and implantable optoelectronic devices can be seamlessly integrated into human body to enable physiological monitoring and treatment in an imperceptible and spatiotemporally unconstrained manner, opening countless possibilities for the intelligent healthcare paradigm. To achieve biointegrated cardiac healthcare, researchers have focused on novel strategies for the construction of flexible/stretchable optoelectronic devices and systems. Here, we overview the progress of biointegrated flexible and stretchable optoelectronics for wearable and implantable cardiac healthcare devices. Firstly, the device design is addressed, including the mechanical design, interface adhesion, and encapsulation strategies. Next, the practical applications of optoelectronic devices for cardiac physiological monitoring, cardiac optogenetics, and nongenetic stimulation are presented. Finally, an outlook on biointegrated flexible and stretchable optoelectronic devices and systems for intelligent cardiac healthcare is discussed.","PeriodicalId":72764,"journal":{"name":"Cyborg and bionic systems (Washington, D.C.)","volume":"5 ","pages":"0172"},"PeriodicalIF":10.5,"publicationDate":"2024-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11486891/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142486071","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

Sensors and Devices Guided by Artificial Intelligence for Personalized Pain Medicine. 人工智能引导的传感器和设备用于个性化疼痛治疗。

IF 10.5

Cyborg and bionic systems (Washington, D.C.) Pub Date : 2024-09-13 eCollection Date: 2024-01-01 DOI: 10.34133/cbsystems.0160

Yantao Xing, Kaiyuan Yang, Albert Lu, Ken Mackie, Feng Guo

{"title":"Sensors and Devices Guided by Artificial Intelligence for Personalized Pain Medicine.","authors":"Yantao Xing, Kaiyuan Yang, Albert Lu, Ken Mackie, Feng Guo","doi":"10.34133/cbsystems.0160","DOIUrl":"https://doi.org/10.34133/cbsystems.0160","url":null,"abstract":"Personalized pain medicine aims to tailor pain treatment strategies for the specific needs and characteristics of an individual patient, holding the potential for improving treatment outcomes, reducing side effects, and enhancing patient satisfaction. Despite existing pain markers and treatments, challenges remain in understanding, detecting, and treating complex pain conditions. Here, we review recent engineering efforts in developing various sensors and devices for addressing challenges in the personalized treatment of pain. We summarize the basics of pain pathology and introduce various sensors and devices for pain monitoring, assessment, and relief. We also discuss advancements taking advantage of rapidly developing medical artificial intelligence (AI), such as AI-based analgesia devices, wearable sensors, and healthcare systems. We believe that these innovative technologies may lead to more precise and responsive personalized medicine, greatly improved patient quality of life, increased efficiency of medical systems, and reducing the incidence of addiction and substance use disorders.","PeriodicalId":72764,"journal":{"name":"Cyborg and bionic systems (Washington, D.C.)","volume":"5 ","pages":"0160"},"PeriodicalIF":10.5,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11395709/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142302423","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

Modeling Grid Cell Distortions with a Grid Cell Calibration Mechanism. 用网格单元校准机制模拟网格单元畸变。

IF 10.5

Cyborg and bionic systems (Washington, D.C.) Pub Date : 2024-09-12 eCollection Date: 2024-01-01 DOI: 10.34133/cbsystems.0140

Daniel Strauß, Zhenshan Bing, Genghang Zhuang, Kai Huang, Alois Knoll

{"title":"Modeling Grid Cell Distortions with a Grid Cell Calibration Mechanism.","authors":"Daniel Strauß, Zhenshan Bing, Genghang Zhuang, Kai Huang, Alois Knoll","doi":"10.34133/cbsystems.0140","DOIUrl":"10.34133/cbsystems.0140","url":null,"abstract":"The medial entorhinal cortex of rodents is known to contain grid cells that exhibit precise periodic firing patterns based on the animal's position, resulting in a distinct hexagonal pattern in space. These cells have been extensively studied due to their potential to unveil the navigational computations that occur within the mammalian brain and interesting phenomena such as so-called grid cell distortions have been observed. Previous neuronal models of grid cells assumed their firing fields were independent of environmental boundaries. However, more recent research has revealed that the grid pattern is, in fact, dependent on the environment's boundaries. When rodents are placed in nonsquare cages, the hexagonal pattern tends to become disrupted and adopts different shapes. We believe that these grid cell distortions can provide insights into the underlying neural circuitry involved in grid cell firing. To this end, a calibration circuit for grid cells is proposed. Our simulations demonstrate that this circuit is capable of reproducing grid distortions observed in several previous studies. Our model also reproduces distortions in place cells and incorporates experimentally observed distortions of speed cells, which present further opportunities for exploration. It generates several experimentally testable predictions, including an alternative behavioral description of boundary vector cells that predicts behaviors in nonsquare environments different from the current model of boundary vector cells. In summary, our study proposes a calibration circuit that reproduces observed grid distortions and generates experimentally testable predictions, aiming to provide insights into the neural mechanisms governing spatial computations in mammals.","PeriodicalId":72764,"journal":{"name":"Cyborg and bionic systems (Washington, D.C.)","volume":"5 ","pages":"0140"},"PeriodicalIF":10.5,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11639139/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142831132","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

Federated Abnormal Heart Sound Detection with Weak to No Labels. 联合异常心音检测，标记弱或无标记。

IF 10.5

Cyborg and bionic systems (Washington, D.C.) Pub Date : 2024-09-10 eCollection Date: 2024-01-01 DOI: 10.34133/cbsystems.0152

Wanyong Qiu, Chen Quan, Yongzi Yu, Eda Kara, Kun Qian, Bin Hu, Björn W Schuller, Yoshiharu Yamamoto

{"title":"Federated Abnormal Heart Sound Detection with Weak to No Labels.","authors":"Wanyong Qiu, Chen Quan, Yongzi Yu, Eda Kara, Kun Qian, Bin Hu, Björn W Schuller, Yoshiharu Yamamoto","doi":"10.34133/cbsystems.0152","DOIUrl":"https://doi.org/10.34133/cbsystems.0152","url":null,"abstract":"Cardiovascular diseases are a prominent cause of mortality, emphasizing the need for early prevention and diagnosis. Utilizing artificial intelligence (AI) models, heart sound analysis emerges as a noninvasive and universally applicable approach for assessing cardiovascular health conditions. However, real-world medical data are dispersed across medical institutions, forming \"data islands\" due to data sharing limitations for security reasons. To this end, federated learning (FL) has been extensively employed in the medical field, which can effectively model across multiple institutions. Additionally, conventional supervised classification methods require fully labeled data classes, e.g., binary classification requires labeling of positive and negative samples. Nevertheless, the process of labeling healthcare data is time-consuming and labor-intensive, leading to the possibility of mislabeling negative samples. In this study, we validate an FL framework with a naive positive-unlabeled (PU) learning strategy. Semisupervised FL model can directly learn from a limited set of positive samples and an extensive pool of unlabeled samples. Our emphasis is on vertical-FL to enhance collaboration across institutions with different medical record feature spaces. Additionally, our contribution extends to feature importance analysis, where we explore 6 methods and provide practical recommendations for detecting abnormal heart sounds. The study demonstrated an impressive accuracy of 84%, comparable to outcomes in supervised learning, thereby advancing the application of FL in abnormal heart sound detection.","PeriodicalId":72764,"journal":{"name":"Cyborg and bionic systems (Washington, D.C.)","volume":"5 ","pages":"0152"},"PeriodicalIF":10.5,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11382922/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142302422","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

Development of Wrist Separated Exoskeleton Socket of Myoelectric Prosthesis Hand for Symbrachydactyly. 开发治疗共济失调的腕分离式外骨骼肌电假手。

IF 10.5

Cyborg and bionic systems (Washington, D.C.) Pub Date : 2024-07-15 eCollection Date: 2024-01-01 DOI: 10.34133/cbsystems.0141

Yuki Inoue, Yuki Kuroda, Yusuke Yamanoi, Yoshiko Yabuki, Hiroshi Yokoi

{"title":"Development of Wrist Separated Exoskeleton Socket of Myoelectric Prosthesis Hand for Symbrachydactyly.","authors":"Yuki Inoue, Yuki Kuroda, Yusuke Yamanoi, Yoshiko Yabuki, Hiroshi Yokoi","doi":"10.34133/cbsystems.0141","DOIUrl":"10.34133/cbsystems.0141","url":null,"abstract":"In recent years, the functionality of myoelectric prosthetic hands has improved as motors have become smaller and controls have become more advanced. Attempts have been made to reproduce the rotation and flexion of the wrist by adding degrees of freedom to the wrist joint. However, it is still difficult to fully reproduce the functionality of the wrist joint owing to the weight of the prosthesis and size limitations. In this study, we developed a new socket and prosthetic hand control system that does not interfere with the wrist joint motion. This allows individuals with hand defects who previously used prosthetic hands with fixed wrist joints to freely use their remaining wrist functionality. In the pick-and-place experiment, where blocks were moved from higher to lower locations, we confirmed that the proposed system resulted in a lower elbow position compared with the traditional prosthesis, and the number of blocks transported increased. This significantly reduced the compensatory motion of the elbow and improved the user's performance compared with the use of a conventional prosthetic hand. This study demonstrates the usefulness of a new myoelectric prosthetic hand that utilizes the residual functions of people with hand deficiencies, which have not been utilized in the past, and the direction of its development.","PeriodicalId":72764,"journal":{"name":"Cyborg and bionic systems (Washington, D.C.)","volume":"5 ","pages":"0141"},"PeriodicalIF":10.5,"publicationDate":"2024-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11246980/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141621900","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

Biomimetic Peripheral Nerve Stimulation Promotes the Rat Hindlimb Motion Modulation in Stepping: An Experimental Analysis. 仿生外周神经刺激促进大鼠后肢在迈步中的运动调节：实验分析

IF 10.5

Cyborg and bionic systems (Washington, D.C.) Pub Date : 2024-07-04 eCollection Date: 2024-01-01 DOI: 10.34133/cbsystems.0131

Pengcheng Xi, Qingyu Yao, Yafei Liu, Jiping He, Rongyu Tang, Yiran Lang

{"title":"Biomimetic Peripheral Nerve Stimulation Promotes the Rat Hindlimb Motion Modulation in Stepping: An Experimental Analysis.","authors":"Pengcheng Xi, Qingyu Yao, Yafei Liu, Jiping He, Rongyu Tang, Yiran Lang","doi":"10.34133/cbsystems.0131","DOIUrl":"10.34133/cbsystems.0131","url":null,"abstract":"Peripheral nerve stimulation is an effective neuromodulation method in patients with lower extremity movement disorders caused by stroke, spinal cord injury, or other diseases. However, most current studies on rehabilitation using sciatic nerve stimulation focus solely on ankle motor regulation through stimulation of common peroneal and tibial nerves. Using the electrical nerve stimulation method, we here achieved muscle control via different sciatic nerve branches to facilitate the regulation of lower limb movements during stepping and standing. A map of relationships between muscles and nerve segments was established to artificially activate specific nerve fibers with the biomimetic stimulation waveform. Then, characteristic curves depicting the relationship between neural electrical stimulation intensity and joint control were established. Finally, by testing the selected stimulation parameters in anesthetized rats, we confirmed that single-cathode extraneural electrical stimulation could activate combined movements to promote lower limb movements. Thus, this method is effective and reliable for use in treatment for improving and rehabilitating lower limb motor dysfunction.","PeriodicalId":72764,"journal":{"name":"Cyborg and bionic systems (Washington, D.C.)","volume":"5 ","pages":"0131"},"PeriodicalIF":10.5,"publicationDate":"2024-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11223769/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141536074","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

Augmented Recognition of Distracted Driving State Based on Electrophysiological Analysis of Brain Network. 基于脑网络电生理分析的分心驾驶状态增强识别。

IF 10.5

Cyborg and bionic systems (Washington, D.C.) Pub Date : 2024-07-04 eCollection Date: 2024-01-01 DOI: 10.34133/cbsystems.0130

Geqi Qi, Rui Liu, Wei Guan, Ailing Huang

{"title":"Augmented Recognition of Distracted Driving State Based on Electrophysiological Analysis of Brain Network.","authors":"Geqi Qi, Rui Liu, Wei Guan, Ailing Huang","doi":"10.34133/cbsystems.0130","DOIUrl":"10.34133/cbsystems.0130","url":null,"abstract":"In this study, we propose an electrophysiological analysis-based brain network method for the augmented recognition of different types of distractions during driving. Driver distractions, such as cognitive processing and visual disruptions during driving, lead to distinct alterations in the electroencephalogram (EEG) signals and the extracted brain networks. We designed and conducted a simulated experiment comprising 4 distracted driving subtasks. Three connectivity indices, including both linear and nonlinear synchronization measures, were chosen to construct the brain network. By computing connectivity strengths and topological features, we explored the potential relationship between brain network configurations and states of driver distraction. Statistical analysis of network features indicates substantial differences between normal and distracted states, suggesting a reconfiguration of the brain network under distracted conditions. Different brain network features and their combinations are fed into varied machine learning classifiers to recognize the distracted driving states. The results indicate that XGBoost demonstrates superior adaptability, outperforming other classifiers across all selected network features. For individual networks, features constructed using synchronization likelihood (SL) achieved the highest accuracy in distinguishing between cognitive and visual distraction. The optimal feature set from 3 network combinations achieves an accuracy of 95.1% for binary classification and 88.3% for ternary classification of normal, cognitively distracted, and visually distracted driving states. The proposed method could accomplish the augmented recognition of distracted driving states and may serve as a valuable tool for further optimizing driver assistance systems with distraction control strategies, as well as a reference for future research on the brain-computer interface in autonomous driving.","PeriodicalId":72764,"journal":{"name":"Cyborg and bionic systems (Washington, D.C.)","volume":"5 ","pages":"0130"},"PeriodicalIF":10.5,"publicationDate":"2024-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11222012/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141536073","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

Advances in Prostate Cancer Biomarkers and Probes. 前列腺癌生物标志物及探针研究进展

IF 10.5

Cyborg and bionic systems (Washington, D.C.) Pub Date : 2024-06-27 eCollection Date: 2024-01-01 DOI: 10.34133/cbsystems.0129

Keyi Li, Qiao Wang, Xiaoying Tang, Ozioma Udochukwu Akakuru, Ruobing Li, Yan Wang, Renran Zhang, Zhenqi Jiang, Zhuo Yang

{"title":"Advances in Prostate Cancer Biomarkers and Probes.","authors":"Keyi Li, Qiao Wang, Xiaoying Tang, Ozioma Udochukwu Akakuru, Ruobing Li, Yan Wang, Renran Zhang, Zhenqi Jiang, Zhuo Yang","doi":"10.34133/cbsystems.0129","DOIUrl":"https://doi.org/10.34133/cbsystems.0129","url":null,"abstract":"Prostate cancer is one of the most prevalent malignant tumors in men worldwide, and early diagnosis is essential to improve patient survival. This review provides a comprehensive discussion of recent advances in prostate cancer biomarkers, including molecular, cellular, and exosomal biomarkers. The potential of various biomarkers such as gene fusions (TMPRSS2-ERG), noncoding RNAs (SNHG12), proteins (PSA, PSMA, AR), and circulating tumor cells (CTCs) in the diagnosis, prognosis, and targeted therapies of prostate cancer is emphasized. In addition, this review systematically explores how multi-omics data and artificial intelligence technologies can be used for biomarker discovery and personalized medicine applications. In addition, this review provides insights into the development of specific probes, including fluorescent, electrochemical, and radionuclide probes, for sensitive and accurate detection of prostate cancer biomarkers. In conclusion, this review provides a comprehensive overview of the status and future directions of prostate cancer biomarker research, emphasizing the potential for precision diagnosis and targeted therapy.","PeriodicalId":72764,"journal":{"name":"Cyborg and bionic systems (Washington, D.C.)","volume":"5 ","pages":"0129"},"PeriodicalIF":10.5,"publicationDate":"2024-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12063729/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144051327","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 Survey on 3D Skeleton-Based Action Recognition Using Learning Method. 使用学习方法进行基于 3D 骨架的动作识别研究。

Cyborg and bionic systems (Washington, D.C.) Pub Date : 2024-05-16 eCollection Date: 2024-01-01 DOI: 10.34133/cbsystems.0100

Bin Ren, Mengyuan Liu, Runwei Ding, Hong Liu

{"title":"A Survey on 3D Skeleton-Based Action Recognition Using Learning Method.","authors":"Bin Ren, Mengyuan Liu, Runwei Ding, Hong Liu","doi":"10.34133/cbsystems.0100","DOIUrl":"https://doi.org/10.34133/cbsystems.0100","url":null,"abstract":"Three-dimensional skeleton-based action recognition (3D SAR) has gained important attention within the computer vision community, owing to the inherent advantages offered by skeleton data. As a result, a plethora of impressive works, including those based on conventional handcrafted features and learned feature extraction methods, have been conducted over the years. However, prior surveys on action recognition have primarily focused on video or red-green-blue (RGB) data-dominated approaches, with limited coverage of reviews related to skeleton data. Furthermore, despite the extensive application of deep learning methods in this field, there has been a notable absence of research that provides an introductory or comprehensive review from the perspective of deep learning architectures. To address these limitations, this survey first underscores the importance of action recognition and emphasizes the significance of 3-dimensional (3D) skeleton data as a valuable modality. Subsequently, we provide a comprehensive introduction to mainstream action recognition techniques based on 4 fundamental deep architectures, i.e., recurrent neural networks, convolutional neural networks, graph convolutional network, and Transformers. All methods with the corresponding architectures are then presented in a data-driven manner with detailed discussion. Finally, we offer insights into the current largest 3D skeleton dataset, NTU-RGB+D, and its new edition, NTU-RGB+D 120, along with an overview of several top-performing algorithms on these datasets. To the best of our knowledge, this research represents the first comprehensive discussion of deep learning-based action recognition using 3D skeleton data.","PeriodicalId":72764,"journal":{"name":"Cyborg and bionic systems (Washington, D.C.)","volume":"5 ","pages":"0100"},"PeriodicalIF":0.0,"publicationDate":"2024-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11096730/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140960067","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