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Article ; Online: Detection of Rehabilitation Training Effect of Upper Limb Movement Disorder Based on MPL-CNN.

Shi, Lijuan / Wang, Runmin / Zhao, Jian / Zhang, Jing / Kuang, Zhejun

2024 Volume 24, Issue 4

Abstract: Stroke represents a medical emergency and can lead to the development of movement disorders such as abnormal muscle tone, limited range of motion, or abnormalities in coordination and balance. In order to help stroke patients recover as soon as possible, ...

Abstract	Stroke represents a medical emergency and can lead to the development of movement disorders such as abnormal muscle tone, limited range of motion, or abnormalities in coordination and balance. In order to help stroke patients recover as soon as possible, rehabilitation training methods employ various movement modes such as ordinary movements and joint reactions to induce active reactions in the limbs and gradually restore normal functions. Rehabilitation effect evaluation can help physicians understand the rehabilitation needs of different patients, determine effective treatment methods and strategies, and improve treatment efficiency. In order to achieve real-time and accuracy of action detection, this article uses Mediapipe's action detection algorithm and proposes a model based on MPL-CNN. Mediapipe can be used to identify key point features of the patient's upper limbs and simultaneously identify key point features of the hand. In order to detect the effect of rehabilitation training for upper limb movement disorders, LSTM and CNN are combined to form a new LSTM-CNN model, which is used to identify the action features of upper limb rehabilitation training extracted by Medipipe. The MPL-CNN model can effectively identify the accuracy of rehabilitation movements during upper limb rehabilitation training for stroke patients. In order to ensure the scientific validity and unified standards of rehabilitation training movements, this article employs the postures in the Fugl-Meyer Upper Limb Rehabilitation Training Functional Assessment Form (FMA) and establishes an FMA upper limb rehabilitation data set for experimental verification. Experimental results show that in each stage of the Fugl-Meyer upper limb rehabilitation training evaluation effect detection, the MPL-CNN-based method's recognition accuracy of upper limb rehabilitation training actions reached 95%. At the same time, the average accuracy rate of various upper limb rehabilitation training actions reaches 97.54%. This shows that the model is highly robust across different action categories and proves that the MPL-CNN model is an effective and feasible solution. This method based on MPL-CNN can provide a high-precision detection method for the evaluation of rehabilitation effects of upper limb movement disorders after stroke, helping clinicians in evaluating the patient's rehabilitation progress and adjusting the rehabilitation plan based on the evaluation results. This will help improve the personalization and precision of rehabilitation treatment and promote patient recovery.
MeSH term(s)	Humans ; Stroke Rehabilitation ; Upper Extremity/physiology ; Stroke ; Movement Disorders ; Hand ; Movement/physiology ; Treatment Outcome ; Recovery of Function/physiology ; Receptors, Thrombopoietin
Chemical Substances	MPL protein, human (143641-95-6) ; Receptors, Thrombopoietin
Language	English
Publishing date	2024-02-08
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2052857-7
ISSN	1424-8220 ; 1424-8220
ISSN (online)	1424-8220
ISSN	1424-8220
DOI	10.3390/s24041105
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Object Detection Based on Roadside LiDAR for Cooperative Driving Automation: A Review.

Sun, Pengpeng / Sun, Chenghao / Wang, Runmin / Zhao, Xiangmo

Sensors (Basel, Switzerland)

2022 Volume 22, Issue 23

Abstract: Light Detection and Ranging (LiDAR) technology has the advantages of high detection accuracy, a wide range of perception, and not being affected by light. The 3D LiDAR is placed at the commanding height of the traffic scene, the overall situation can be ... ...

Abstract	Light Detection and Ranging (LiDAR) technology has the advantages of high detection accuracy, a wide range of perception, and not being affected by light. The 3D LiDAR is placed at the commanding height of the traffic scene, the overall situation can be grasped from the perspective of top view, and the trajectory of each object in the traffic scene can be accurately perceived in real time, and then the object information can be distributed to the surrounding vehicles or other roadside LiDAR through advanced wireless communication equipment, which can significantly improve the local perception ability of an autonomous vehicle. This paper first describes the characteristics of roadside LiDAR and the challenges of object detection and then reviews in detail the current methods of object detection based on a single roadside LiDAR and multi-LiDAR cooperatives. Then, some studies for roadside LiDAR perception in adverse weather and datasets released in recent years are introduced. Finally, some current open challenges and future works for roadside LiDAR perception are discussed. To the best of our knowledge, this is the first work to systematically study roadside LiDAR perception methods and datasets. It has an important guiding role in further promoting the research of roadside LiDAR perception for practical applications.
Language	English
Publishing date	2022-11-30
Publishing country	Switzerland
Document type	Journal Article ; Review
ZDB-ID	2052857-7
ISSN	1424-8220 ; 1424-8220
ISSN (online)	1424-8220
ISSN	1424-8220
DOI	10.3390/s22239316
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Adaptive Inference for Change Points in High-Dimensional Data

Zhang, Yangfan / Wang, Runmin / Shao, Xiaofeng

Journal of the American Statistical Association. 2022 Oct. 2, v. 117, no. 540 p.1751-1762

2022

Abstract: In this article, we propose a class of test statistics for a change point in the mean of high-dimensional independent data. Our test integrates the U-statistic based approach in a recent work by Wang et al. and the Lq-norm based high-dimensional test in ... ...

Abstract	In this article, we propose a class of test statistics for a change point in the mean of high-dimensional independent data. Our test integrates the U-statistic based approach in a recent work by Wang et al. and the Lq-norm based high-dimensional test in a recent work by He et al., and inherits several appealing features such as being tuning parameter free and asymptotic independence for test statistics corresponding to even q’s. A simple combination of test statistics corresponding to several different q’s leads to a test with adaptive power property, that is, it can be powerful against both sparse and dense alternatives. On the estimation front, we obtain the convergence rate of the maximizer of our test statistic standardized by sample size when there is one change-point in mean and q = 2, and propose to combine our tests with a wild binary segmentation algorithm to estimate the change-point number and locations when there are multiple change-points. Numerical comparisons using both simulated and real data demonstrate the advantage of our adaptive test and its corresponding estimation method.
Keywords	algorithms ; sample size ; statistics ; Asymptotically pivotal ; Segmentation ; Self-normalization ; Structural break ; U-statistics
Language	English
Dates of publication	2022-1002
Size	p. 1751-1762.
Publishing place	Taylor & Francis
Document type	Article ; Online
ZDB-ID	2064981-2
ISSN	1537-274X
ISSN	1537-274X
DOI	10.1080/01621459.2021.1884562
Database	NAL-Catalogue (AGRICOLA)

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Article ; Online: Improved breast ultrasound tumor classification using dual-input CNN with GAP-guided attention loss.

Zou, Xiao / Zhai, Jintao / Qian, Shengyou / Li, Ang / Tian, Feng / Cao, Xiaofei / Wang, Runmin

Mathematical biosciences and engineering : MBE

2023 Volume 20, Issue 8, Page(s) 15244–15264

Abstract: Ultrasonography is a widely used medical imaging technique for detecting breast cancer. While manual diagnostic methods are subject to variability and time-consuming, computer-aided diagnostic (CAD) methods have proven to be more efficient. However, ... ...

Abstract	Ultrasonography is a widely used medical imaging technique for detecting breast cancer. While manual diagnostic methods are subject to variability and time-consuming, computer-aided diagnostic (CAD) methods have proven to be more efficient. However, current CAD approaches neglect the impact of noise and artifacts on the accuracy of image analysis. To enhance the precision of breast ultrasound image analysis for identifying tissues, organs and lesions, we propose a novel approach for improved tumor classification through a dual-input model and global average pooling (GAP)-guided attention loss function. Our approach leverages a convolutional neural network with transformer architecture and modifies the single-input model for dual-input. This technique employs a fusion module and GAP operation-guided attention loss function simultaneously to supervise the extraction of effective features from the target region and mitigate the effect of information loss or redundancy on misclassification. Our proposed method has three key features: (i) ResNet and MobileViT are combined to enhance local and global information extraction. In addition, a dual-input channel is designed to include both attention images and original breast ultrasound images, mitigating the impact of noise and artifacts in ultrasound images. (ii) A fusion module and GAP operation-guided attention loss function are proposed to improve the fusion of dual-channel feature information, as well as supervise and constrain the weight of the attention mechanism on the fused focus region. (iii) Using the collected uterine fibroid ultrasound dataset to train ResNet18 and load the pre-trained weights, our experiments on the BUSI and BUSC public datasets demonstrate that the proposed method outperforms some state-of-the-art methods. The code will be publicly released at https://github.com/425877/Improved-Breast-Ultrasound-Tumor-Classification.
MeSH term(s)	Female ; Humans ; Ultrasonography, Mammary ; Artifacts ; Electric Power Supplies ; Image Processing, Computer-Assisted ; Neoplasms
Language	English
Publishing date	2023-09-07
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2265126-3
ISSN	1551-0018 ; 1551-0018
ISSN (online)	1551-0018
ISSN	1551-0018
DOI	10.3934/mbe.2023682
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Biofeedback Respiratory Rehabilitation Training System Based on Virtual Reality Technology.

Shi, Lijuan / Liu, Feng / Liu, Yuan / Wang, Runmin / Zhang, Jing / Zhao, Zisong / Zhao, Jian

Sensors (Basel, Switzerland)

2023 Volume 23, Issue 22

Abstract: Traditional respiratory rehabilitation training fails to achieve visualization and quantification of respiratory data in improving problems such as decreased lung function and dyspnea in people with respiratory disorders, and the respiratory ... ...

Abstract	Traditional respiratory rehabilitation training fails to achieve visualization and quantification of respiratory data in improving problems such as decreased lung function and dyspnea in people with respiratory disorders, and the respiratory rehabilitation training process is simple and boring. Therefore, this article designs a biofeedback respiratory rehabilitation training system based on virtual reality technology. It collects respiratory data through a respiratory sensor and preprocesses it. At the same time, it combines the biofeedback respiratory rehabilitation training virtual scene to realize the interaction between respiratory data and virtual scenes. This drives changes in the virtual scene, and finally the respiratory data are fed back to the patient in a visual form to evaluate the improvement of the patient's lung function. This paper conducted an experiment with 10 participants to evaluate the system from two aspects: training effectiveness and user experience. The results show that this system has significantly improved the patient's lung function. Compared with traditional training methods, the respiratory data are quantified and visualized, the rehabilitation training effect is better, and the training process is more active and interesting.
MeSH term(s)	Humans ; Biofeedback, Psychology ; Virtual Reality ; Respiratory Rate ; User-Computer Interface
Language	English
Publishing date	2023-11-07
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2052857-7
ISSN	1424-8220 ; 1424-8220
ISSN (online)	1424-8220
ISSN	1424-8220
DOI	10.3390/s23229025
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Book ; Online: Treating Crowdsourcing as Examination

Han, Guangyang / Li, Sufang / Wang, Runmin / Wu, Chunming

How to Score Tasks and Online Workers?

2022

Abstract: Crowdsourcing is an online outsourcing mode which can solve the current machine learning algorithm's urge need for massive labeled data. Requester posts tasks on crowdsourcing platforms, which employ online workers over the Internet to complete tasks, ... ...

Abstract	Crowdsourcing is an online outsourcing mode which can solve the current machine learning algorithm's urge need for massive labeled data. Requester posts tasks on crowdsourcing platforms, which employ online workers over the Internet to complete tasks, then aggregate and return results to requester. How to model the interaction between different types of workers and tasks is a hot spot. In this paper, we try to model workers as four types based on their ability: expert, normal worker, sloppy worker and spammer, and divide tasks into hard, medium and easy task according to their difficulty. We believe that even experts struggle with difficult tasks while sloppy workers can get easy tasks right, and spammers always give out wrong answers deliberately. So, good examination tasks should have moderate degree of difficulty and discriminability to score workers more objectively. Thus, we first score workers' ability mainly on the medium difficult tasks, then reducing the weight of answers from sloppy workers and modifying the answers from spammers when inferring the tasks' ground truth. A probability graph model is adopted to simulate the task execution process, and an iterative method is adopted to calculate and update the ground truth, the ability of workers and the difficulty of the task successively. We verify the rightness and effectiveness of our algorithm both in simulated and real crowdsourcing scenes.
Keywords	Computer Science - Human-Computer Interaction ; Computer Science - Databases ; Computer Science - Machine Learning
Subject code	004
Publishing date	2022-04-26
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Identification of Denatured Biological Tissues Based on Compressed Sensing and Improved Multiscale Dispersion Entropy during HIFU Treatment.

Liu, Bei / Wang, Runmin / Peng, Ziqi / Qin, Lingjie

Entropy (Basel, Switzerland)

2020 Volume 22, Issue 9

Abstract: Identification of denatured biological tissue is crucial to high-intensity focused ultrasound (HIFU) treatment, which can monitor HIFU treatment and improve treatment efficiency. In this paper, a novel method based on compressed sensing (CS) and improved ...

Abstract	Identification of denatured biological tissue is crucial to high-intensity focused ultrasound (HIFU) treatment, which can monitor HIFU treatment and improve treatment efficiency. In this paper, a novel method based on compressed sensing (CS) and improved multiscale dispersion entropy (IMDE) is proposed to evaluate the complexity of ultrasonic scattered echo signals during HIFU treatment. In the analysis of CS, the method of orthogonal matching pursuit (OMP) is employed to reconstruct the denoised signal. CS-OMP can denoise the ultrasonic scattered echo signal effectively. Comparing with traditional multiscale dispersion entropy (MDE), IMDE improves the coarse-grained process in the multiscale analysis, which improves the stability of MDE. In the analysis of simulated signals, the entropy value of the IMDE method has less fluctuation compared with MDE, indicating that the IMDE method has better stability. In addition, MDE and IMDE are applied to the 300 cases of ultrasonic scattered echo signals after denoising (including 150 cases of normal tissues and 150 cases of denatured tissues). The experimental results show that the MDE and IMDE values of denatured tissues are higher than normal tissues. Both the MDE and IMDE method can be used to identify whether biological tissue is denatured. However, the multiscale entropy curve of IMDE is smoother and more stable than MDE. The interclass distance of IMDE is greater than MDE, and the intraclass distance of IMDE is less than MDE at different scale factors. This indicates that IMDE can better distinguish normal tissues and denatured tissues to obtain more accurate clinical diagnosis during HIFU treatment.
Language	English
Publishing date	2020-08-27
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2014734-X
ISSN	1099-4300 ; 1099-4300
ISSN (online)	1099-4300
ISSN	1099-4300
DOI	10.3390/e22090944
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: User experience and usability when the automated driving system fails: Findings from a field experiment.

Liu, Peng / Jiang, Zijun / Li, Tingting / Wang, Guanqun / Wang, Runmin / Xu, Zhigang

Accident; analysis and prevention

2021 Volume 161, Page(s) 106383

Abstract: We are entering an era of automated vehicles (AVs), which has potential to improve road safety considerably. A compelling user experience is crucial to AV adoption in the future commercial market. The automated driving system (ADS) that replaces human ... ...

Abstract	We are entering an era of automated vehicles (AVs), which has potential to improve road safety considerably. A compelling user experience is crucial to AV adoption in the future commercial market. The automated driving system (ADS) that replaces human drivers should be perceived as very useful before the latter are willing to give up their control and entrust their lives to the ADS. However, compared with the growing number of studies on public acceptance of AVs, there has been limited research focusing on user experience and usability. We examined AV and ADS user experience and usability, ADS failures' influence on them, and their influences on re-riding willingness. We conducted a field study using a real AV and a large-scale test track. We invited participants (N = 261) to travel in the AV as passengers in a low-speed environment. Participants were randomly assigned into the normal condition or the fault condition (its participants were exposed to an ADS failure). We measured participants' positive experience (feeling relaxed, safe, and comfortable) and negative experience (feeling tense and risky) while riding in the AV and perceived usability of the ADS based on the System Usability Scale. In both conditions, participants reported moderate positive experience and perceived usability but a relatively high level of willingness to ride in our AV again. The ADS failure reduced positive experience and perceived usability, and it increased negative experience. Positive experience and perceived usability, but not negative experience, influenced re-riding willingness. Compared with male participants, female participants reported less positive experience and lower perceived usability. We discuss implications of our results as well as limitations of this research.
MeSH term(s)	Accidents, Traffic/prevention & control ; Automation ; Automobile Driving ; Emotions ; Female ; Humans ; Male ; Travel
Language	English
Publishing date	2021-08-29
Publishing country	England
Document type	Journal Article ; Randomized Controlled Trial
ZDB-ID	210223-7
ISSN	1879-2057 ; 0001-4575
ISSN (online)	1879-2057
ISSN	0001-4575
DOI	10.1016/j.aap.2021.106383
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: Acupuncture Can Regulate the Distribution of Lymphocyte Subsets and the Levels of Inflammatory Cytokines in Patients With Mild to Moderate Vascular Dementia.

Zhi, Hui / Wang, Yao / Chang, Shichen / Pan, Pan / Ling, Zhenzhen / Zhang, Zhen / Ma, Zhinan / Wang, Runmin / Zhang, Xuezhu

Frontiers in aging neuroscience

2021 Volume 13, Page(s) 747673

Abstract: Background: ...

Abstract	Background:
Language	English
Publishing date	2021-11-29
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2558898-9
ISSN	1663-4365
ISSN	1663-4365
DOI	10.3389/fnagi.2021.747673
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: Acupuncture Can Regulate the Peripheral Immune Cell Spectrum and Inflammatory Environment of the Vascular Dementia Rat, and Improve the Cognitive Dysfunction of the Rats.

Pan, Pan / Ma, Zhinan / Zhang, Zhen / Ling, Zhenzhen / Wang, Yao / Liu, Qiuping / Lin, Xiaolin / Xu, Pan / Yang, Dan / Zhi, Hui / Wang, Runmin / Zhang, Xuezhu

Frontiers in aging neuroscience

2021 Volume 13, Page(s) 706834

Abstract: Objective: The aim of this study is to analyze the effects of acupuncture on peripheral immune function, inflammation, and cognitive impairment in vascular dementia (VD) rats.: Methods: In this study, 2-month-old healthy male Wistar rats (260-280 g) ... ...

Abstract	Objective: The aim of this study is to analyze the effects of acupuncture on peripheral immune function, inflammation, and cognitive impairment in vascular dementia (VD) rats. Methods: In this study, 2-month-old healthy male Wistar rats (260-280 g) were assigned to the groups as follows: normal group (Gn, Results: Compared with the Gn group, the Gi rats presented long escape latencies to find the platform. After acupuncture treatment, the escape latencies of the Ga group were rescued markedly when compared with the Gi group ( Conclusion: There are abnormal immune function and peripheral inflammation in VD rats. Acupuncture can regulate the peripheral immune function and inflammation of the VD rats and can improve the cognitive dysfunction of the rats.
Language	English
Publishing date	2021-07-19
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2558898-9
ISSN	1663-4365
ISSN	1663-4365
DOI	10.3389/fnagi.2021.706834
Database	MEDical Literature Analysis and Retrieval System OnLINE

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