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  1. Article: Understanding Senior Adults' Needs, Preferences, and Experiences of Commercial Exergames for Health: Usability Study.

    Wang, Yu-Han

    JMIR serious games

    2024  Volume 12, Page(s) e36154

    Abstract: Background: Many senior adults are at risk of mental and physical disorders due to a lack of sufficient exercise. Therefore, adherent exercise should be urgently promoted to improve senior adults' muscle strength, preventing falls and conditions caused ... ...

    Abstract Background: Many senior adults are at risk of mental and physical disorders due to a lack of sufficient exercise. Therefore, adherent exercise should be urgently promoted to improve senior adults' muscle strength, preventing falls and conditions caused by physical and cognitive decline. However, off-the-shelf exercise games, so-called exergames, are mainly targeted at the younger generation or children, while senior adults are neglected, when this age group strongly needs exercise. Exergames could serve as a health intervention for promoting exercise.
    Objective: This study aimed to investigate senior adults' experience, perceptions, and acceptance of game technology to promote exercise in order to suggest game design guidelines.
    Methods: In this usability study, participants engaged in playing Nintendo Switch and Xbox Kinect games, after which semistructured interviews were conducted. Before the gameplay, the participants provided their background information, exercise habits, and use of technology products. Next, all participants completed a workshop including 3 activities (brief instructions on how to play the games: 20 minutes; playing the selected exergames: 80 minutes; semistructured interviews: 20 minutes) for 2 hours a day for 3 days each. The participants played the latest Nintendo Switch games (eg, Just Dance, Boxing, Ring Fit Adventure) and Xbox Kinect games (eg, Kinect Adventures!, Mini Games). Just Dance, Zumba, and Boxing were played in activity 1; Ring Fit Adventure and Mini Games in activity 2; and Kinect Adventures! in activity 3. Reflexive thematic analysis was applied to identify the relative themes generated from the interviews.
    Results: In total, 22 participants (mean age 70.4, SD 6.1 years) were enrolled in the workshop in May 2021. The results of the generated themes included incomprehension of game instructions, psychological perception of game technology, and game art preferences. The subthemes generated from game art preferences included favorite game genres, characters, and scenes.
    Conclusions: There is a significant need for customized game tutorials considering senior adults' cognitive and physical aging. Furthermore, the adventure game genre is preferable to other games. Humanlike game characters are preferable, especially those with a fit and healthy body shape. Nature scenes are more enjoyable than indoor stages or rooms. Furthermore, the game intensity design and playing time should be carefully planned to meet the World Health Organization's criteria for physical activity in older adults. Intelligent recommendation systems might be helpful to support older adults with various health conditions. The guidelines suggested in this study might be beneficial for game design, exercise training, and game technology adoption of exergames for older adults to improve health.
    Language English
    Publishing date 2024-04-05
    Publishing country Canada
    Document type Journal Article
    ZDB-ID 2798265-8
    ISSN 2291-9279
    ISSN 2291-9279
    DOI 10.2196/36154
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article ; Online: The discussion about comprehensive regulation and control methods of Low and non-effective circulation layers in ultra-high water cut stage

    Wang Yu

    E3S Web of Conferences, Vol 352, p

    2022  Volume 01083

    Abstract: As the oilfield enters the ultra-high water cut stage, the development situation of water flooding is becoming increasingly severe, facing problems such as increasing natural decline, rapid water cut rise, and serious low and non-effective circulation. ... ...

    Abstract As the oilfield enters the ultra-high water cut stage, the development situation of water flooding is becoming increasingly severe, facing problems such as increasing natural decline, rapid water cut rise, and serious low and non-effective circulation. How to accurately identify low and non-effective circulation layers, effectively adjust them, and alleviate the interlayer contradiction, is an important subject of water control and efficiency improvement project. In recent years, in view of the difficulty in identifying low and non-effective circulation layers in water flooding and the unsatisfactory control effect, a platform of preferential seepage channels identification has been developed, to achieve accurate identification of low and non-effective circulation layers. A classification and evaluation of low and non-effective circulation layers use the recognition results combined with the dynamic and static data has been carried out. The personalized plan has been carried on the field application. It achieved good effect for improving producing reservoir effectively, controlling water cut rising, providing reference basis for determining control low and non-efficient circulation layers.
    Keywords low and non-effective circulation ; Environmental sciences ; GE1-350
    Language English
    Publishing date 2022-01-01T00:00:00Z
    Publisher EDP Sciences
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  3. Article: Mental health education on college students' english vocabulary memorization from the perspective of STEAM education.

    Wang, Yu

    Frontiers in psychology

    2022  Volume 13, Page(s) 944465

    Abstract: The formation and research of Constructivism theory is another understanding in developing educational psychology. Many problems exist in English vocabulary teaching and learning, which are too common to be noticed, negatively and implicitly impacting ... ...

    Abstract The formation and research of Constructivism theory is another understanding in developing educational psychology. Many problems exist in English vocabulary teaching and learning, which are too common to be noticed, negatively and implicitly impacting Students' English Vocabulary Memorization (EVM). In order to solve these problems, this work studies college Students' EVM from the perspective of Constructivism. Firstly, the literature review and observation method understand the Students' EVM performance and teaching behavior. Secondly, it analyzes the current situation, problems, and reasons for Students' poor EVM abilities. Finally, combined with relevant theories, a college Students' EVM-oriented teaching model is proposed, whose effectiveness is verified by teaching experiments. The experiment recruits100 freshmen, including 60 boys and 40 girls, and lasts half a semester. The average score of the final exam in the experimental group is more than 90, which is better than that in the control group. Then, the SPSS21.0 is used in the independent-samples
    Language English
    Publishing date 2022-09-30
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2563826-9
    ISSN 1664-1078
    ISSN 1664-1078
    DOI 10.3389/fpsyg.2022.944465
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article ; Online: Research on Intelligent Target Tracking Algorithm Based on MDNet under Artificial Intelligence.

    Wang, Yu

    Computational intelligence and neuroscience

    2022  Volume 2022, Page(s) 1550543

    Abstract: Target tracking is an important subject in computer vision technology, which has developed rapidly in recent ten years, and its application have become wider and wider. In this process, it has transferred from a simple experimental tracking environment ... ...

    Abstract Target tracking is an important subject in computer vision technology, which has developed rapidly in recent ten years, and its application have become wider and wider. In this process, it has transferred from a simple experimental tracking environment to a complex real scene where more challenges need to be solved. The rapid development of deep learning has promoted the research progress of digital vision. Target tracking technology is an important foundation of digital vision research, which makes it develop from academia to industry. In this paper, a method of target tracking using MDNet is introduced. Starting with the attention mechanism, two attention mechanisms are added to extract and integrate the better features. Case partitioning is used to reduce the investment of tracking module and minimize the network size during tracking, and its result can be prevented from getting worse. Finally, the experiment is analyzed in detail.
    MeSH term(s) Algorithms ; Artificial Intelligence ; Technology ; Vision, Ocular
    Language English
    Publishing date 2022-04-19
    Publishing country United States
    Document type Journal Article
    ZDB-ID 2388208-6
    ISSN 1687-5273 ; 1687-5273
    ISSN (online) 1687-5273
    ISSN 1687-5273
    DOI 10.1155/2022/1550543
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  5. Article ; Online: Retraction Note: Tripterine ameliorates monosodium urate crystal‑induced gouty arthritis by altering macrophage polarization via the miR‑449a/NLRP3 axis.

    Wang, Yu

    Inflammation research : official journal of the European Histamine Research Society ... [et al.

    2022  Volume 72, Issue 1, Page(s) 3

    Language English
    Publishing date 2022-09-21
    Publishing country Switzerland
    Document type Retraction of Publication
    ZDB-ID 1221794-3
    ISSN 1420-908X ; 1023-3830
    ISSN (online) 1420-908X
    ISSN 1023-3830
    DOI 10.1007/s00011-022-01630-x
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  6. Article ; Online: The Application of Computer-Based Multimedia Technology in Cognitive Computing.

    Wang, Yu

    Computational intelligence and neuroscience

    2022  Volume 2022, Page(s) 3354576

    Abstract: With the continuous development of science and technology, people's research on computer-related technologies is gradually deepening. The proposal of artificial intelligence makes the research of intelligent AI in urgent need for seeking breakthroughs. ... ...

    Abstract With the continuous development of science and technology, people's research on computer-related technologies is gradually deepening. The proposal of artificial intelligence makes the research of intelligent AI in urgent need for seeking breakthroughs. Among them, cognitive computing methods are important for computers and human brain thinking. Model learning is even more meaningful. This article aims to study the application of computer-based multimedia technology in cognitive computing methods. For this, this article proposes a method of distributed multimedia technology and a method of two-way cognition for cognitive computing through this technology to deepen the rapid improvement of cognition. In addition, this article finally designed relating experiments to study it. The experimental results show that the cognitive accuracy of the improved cognitive computing method has increased by 32.9%, and the cognitive ability has also been greatly improved compared to the past.
    MeSH term(s) Artificial Intelligence ; Cognition ; Computers ; Humans ; Multimedia ; Technology
    Language English
    Publishing date 2022-02-26
    Publishing country United States
    Document type Journal Article
    ZDB-ID 2388208-6
    ISSN 1687-5273 ; 1687-5273
    ISSN (online) 1687-5273
    ISSN 1687-5273
    DOI 10.1155/2022/3354576
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  7. Article ; Online: Review of Visual Question Answering Technology

    WANG Yu, SUN Haichun

    Jisuanji kexue yu tansuo, Vol 17, Iss 7, Pp 1487-

    2023  Volume 1505

    Abstract: Visual question answering (VQA) is a popular cross-modal task that combines natural language pro-cessing and computer vision techniques. The main objective of this task is to enable computers to intelligently recognize and retrieve visual content and ... ...

    Abstract Visual question answering (VQA) is a popular cross-modal task that combines natural language pro-cessing and computer vision techniques. The main objective of this task is to enable computers to intelligently recognize and retrieve visual content and provide accurate answers. VQA involves the integration of multiple technologies such as object recognition and detection, intelligent question answering, image attribute classification, and scene analysis. It can support a wide range of cutting-edge interactive AI tasks such as visual dialogue and visual navigation, and has broad application prospects and great value. Over the past few years, the development of computer vision, natural language processing, and cross-modal AI models has provided many new technologies and methods for achieving the task of visual question answering. This paper mainly summarizes the mainstream models and specialized datasets in the field of visual question answering between 2019 and 2022. Firstly, this paper provides a review and discussion of the mainstream technical methods used in the key steps of implementing the visual question answering task, based on the module framework. Next, it subdivides various types of models in this field according to the technical methods adopted by mainstream models, and briefly introduces their improvement focus and limitations. Then, it summarizes the commonly used datasets and evaluation metrics for visual question answering, and compares and discusses the performance of several typical models. Finally, this paper focuses on the key issues that need to be addressed in the current visual question answering field, and predicts and prospects the future application and technological development in this field.
    Keywords visual question answering (vqa) ; modal fusion ; visual dialogue ; intelligent question answering ; cross-modal technology ; Electronic computers. Computer science ; QA75.5-76.95
    Subject code 400 ; 700
    Language Chinese
    Publishing date 2023-07-01T00:00:00Z
    Publisher Journal of Computer Engineering and Applications Beijing Co., Ltd., Science Press
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  8. Book ; Online: Interpretable and Scalable Graphical Models for Complex Spatio-temporal Processes

    Wang, Yu

    2023  

    Abstract: This thesis focuses on data that has complex spatio-temporal structure and on probabilistic graphical models that learn the structure in an interpretable and scalable manner. We target two research areas of interest: Gaussian graphical models for tensor- ... ...

    Abstract This thesis focuses on data that has complex spatio-temporal structure and on probabilistic graphical models that learn the structure in an interpretable and scalable manner. We target two research areas of interest: Gaussian graphical models for tensor-variate data and summarization of complex time-varying texts using topic models. This work advances the state-of-the-art in several directions. First, it introduces a new class of tensor-variate Gaussian graphical models via the Sylvester tensor equation. Second, it develops an optimization technique based on a fast-converging proximal alternating linearized minimization method, which scales tensor-variate Gaussian graphical model estimations to modern big-data settings. Third, it connects Kronecker-structured (inverse) covariance models with spatio-temporal partial differential equations (PDEs) and introduces a new framework for ensemble Kalman filtering that is capable of tracking chaotic physical systems. Fourth, it proposes a modular and interpretable framework for unsupervised and weakly-supervised probabilistic topic modeling of time-varying data that combines generative statistical models with computational geometric methods. Throughout, practical applications of the methodology are considered using real datasets. This includes brain-connectivity analysis using EEG data, space weather forecasting using solar imaging data, longitudinal analysis of public opinions using Twitter data, and mining of mental health related issues using TalkLife data. We show in each case that the graphical modeling framework introduced here leads to improved interpretability, accuracy, and scalability.

    Comment: PhD dissertation, University of Michigan. The contents are motsly based on arXiv:2212.01721, arXiv:2112.04322, arXiv:2105.12271, arXiv:2002.00288, and https://doi.org/10.1162/99608f92.b447c07e with extended discussions
    Keywords Computer Science - Machine Learning ; Statistics - Methodology
    Subject code 006
    Publishing date 2023-01-15
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  9. Article ; Online: DOACs versus VKAs were associated with lower odds of all-cause mortality and similar odds of major bleeding?

    Wang, Yu-Wen

    International journal of cardiology

    2022  Volume 371, Page(s) 331

    Language English
    Publishing date 2022-10-14
    Publishing country Netherlands
    Document type Letter
    ZDB-ID 779519-1
    ISSN 1874-1754 ; 0167-5273
    ISSN (online) 1874-1754
    ISSN 0167-5273
    DOI 10.1016/j.ijcard.2022.10.004
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  10. Article ; Online: Can acute exercise be more pleasant? Using audiovisual stimuli: A meta-analysis.

    Wang, Yu-Bu

    Applied psychology. Health and well-being

    2022  Volume 15, Issue 1, Page(s) 354–368

    Abstract: This meta-analytic study aimed to examine the effects of audiovisual stimuli on affective responses during and after exercise and their moderators. A total of 296 effect sizes (Hedge's g) were extracted from 46 independent studies covering 1292 ... ...

    Abstract This meta-analytic study aimed to examine the effects of audiovisual stimuli on affective responses during and after exercise and their moderators. A total of 296 effect sizes (Hedge's g) were extracted from 46 independent studies covering 1292 participants. Meta-analysis was performed using Comprehensive Meta-Analysis Version 3.3, and potential moderating variables were analysed using univariate meta-regression models. Audiovisual stimuli increased affective valence during (g = 0.793, 95% CI [0.666, 0.920]) and after exercise (g = 0.792, 95% CI [0.567, 1.016]), and arousal during (g = 0.920, 95% CI [0.742 1.097]) and after exercise (g = 0.666, 95% CI [0.390, 0.962]). There may be publication bias in the meta-analysis, but the main findings are still valid. The type of audiovisual stimuli (audio-video > audio or video), exercise habits (active > not reported), and exercise intensities (self-selected > imposed) moderated the effects. In conclusion, the application of audiovisual stimuli during exercise can elicit positive affective responses. These results provide a viable intervention strategy for exercise and health practitioners to reduce the number of physically inactive individuals and improve exercise compliance and adherence.
    MeSH term(s) Humans ; Exercise/psychology ; Emotions ; Arousal ; Habits ; Sedentary Behavior
    Language English
    Publishing date 2022-06-17
    Publishing country England
    Document type Meta-Analysis ; Journal Article
    ZDB-ID 2483053-7
    ISSN 1758-0854 ; 1758-0846
    ISSN (online) 1758-0854
    ISSN 1758-0846
    DOI 10.1111/aphw.12383
    Database MEDical Literature Analysis and Retrieval System OnLINE

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