Pub Date : 2023-10-07DOI: 10.1142/s0219519423400997
Kwang-Hee Lee, Mi Yu, Tae-Kyu Kwon
Recently, as modern people’s consumption trends have been concentrated on contactless consumption such as online shopping since the 2019 COVID-19 Pandemic, the delivery industry, which is in charge of physical movement of online consumption activities, has also seen a series of utilization and demand. However, in contrast to the rapidly increasing volume of couriers, the labor environment of courier workers is poor, and the rapid increase in demand for courier service after the 2019 COVID-19 Pandemic has led to the rise in musculoskeletal diseases in courier workers. Various muscle support systems such as wearable robots have been developed to prevent musculoskeletal diseases in industrial sites, but the system is bulky, so the total weight is high, they are inconvenient to wear, and the wearers cannot freely perform activities when power is not supplied. In this study, the disadvantages of hard wearable robot systems, such as weight and power supply, were supplemented through elastic rubber bands and wires. In addition, wearable suits were developed to reduce the load on the body, prevent overwork, verify the effectiveness of work clothes, and prevent musculoskeletal diseases in courier workers. The experiment was conducted to verify whether the wearable suit affects muscle strength assistance by measuring the muscle usage when lifting weight after measuring the Maximum Voluntary Contract (MVC). The lifting types were classified into three types, and the strength assistance effects of the waist and lower extremities according to the wearable suit were compared.
{"title":"Effect on Muscle Strength During Lifting Tasks with Wearable Suit Using Wire and Elastic Bands","authors":"Kwang-Hee Lee, Mi Yu, Tae-Kyu Kwon","doi":"10.1142/s0219519423400997","DOIUrl":"https://doi.org/10.1142/s0219519423400997","url":null,"abstract":"Recently, as modern people’s consumption trends have been concentrated on contactless consumption such as online shopping since the 2019 COVID-19 Pandemic, the delivery industry, which is in charge of physical movement of online consumption activities, has also seen a series of utilization and demand. However, in contrast to the rapidly increasing volume of couriers, the labor environment of courier workers is poor, and the rapid increase in demand for courier service after the 2019 COVID-19 Pandemic has led to the rise in musculoskeletal diseases in courier workers. Various muscle support systems such as wearable robots have been developed to prevent musculoskeletal diseases in industrial sites, but the system is bulky, so the total weight is high, they are inconvenient to wear, and the wearers cannot freely perform activities when power is not supplied. In this study, the disadvantages of hard wearable robot systems, such as weight and power supply, were supplemented through elastic rubber bands and wires. In addition, wearable suits were developed to reduce the load on the body, prevent overwork, verify the effectiveness of work clothes, and prevent musculoskeletal diseases in courier workers. The experiment was conducted to verify whether the wearable suit affects muscle strength assistance by measuring the muscle usage when lifting weight after measuring the Maximum Voluntary Contract (MVC). The lifting types were classified into three types, and the strength assistance effects of the waist and lower extremities according to the wearable suit were compared.","PeriodicalId":50135,"journal":{"name":"Journal of Mechanics in Medicine and Biology","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135253228","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-07DOI: 10.1142/s0219519423400936
Hyeon Seop Lee, Jong Seon Oh, Kyung Jin Lee, Seong-Gil Kim
The objective of this research was to evaluate the effects of biofeedback equipment with a tilt sensor and a neck correction exercise program on balance control ability, proprioception, and craniovertebral angle (CVA) in young adults. Ten students (M/F, 7/3) aged 20–30 years attending Sunmoon University in Asan-si, South Korea, participated in this study. All subjects participated in three sessions. These sessions consisted of a biofeedback session with a tilt sensor, followed by an exercise session, and a combined session involving biofeedback equipment with a tilt sensor and exercise. Each session takes 30[Formula: see text]min. The sessions were conducted with a one-day interval between each one. Before the start of the experiment, physical characteristics were measured, and proprioception, balance control ability, and CVA were evaluated. The exercise program significantly improved the stability index (SI) in the eyes-closed state. The biofeedback program resulted in improvement in left rotation, and the CVA was significantly improved after all exercise sessions. In conclusion, a neck correction exercise program that actively moves muscles may have a potential positive impact on balance control ability. Biofeedback equipment might aid in enhancing proprioception by preventing forward head posture (FHP).
{"title":"Effects of intervention using biofeedback equipment and a neck correction exercise program on balance control ability, proprioception and craniovertebral angle in young adults: a pilot study","authors":"Hyeon Seop Lee, Jong Seon Oh, Kyung Jin Lee, Seong-Gil Kim","doi":"10.1142/s0219519423400936","DOIUrl":"https://doi.org/10.1142/s0219519423400936","url":null,"abstract":"The objective of this research was to evaluate the effects of biofeedback equipment with a tilt sensor and a neck correction exercise program on balance control ability, proprioception, and craniovertebral angle (CVA) in young adults. Ten students (M/F, 7/3) aged 20–30 years attending Sunmoon University in Asan-si, South Korea, participated in this study. All subjects participated in three sessions. These sessions consisted of a biofeedback session with a tilt sensor, followed by an exercise session, and a combined session involving biofeedback equipment with a tilt sensor and exercise. Each session takes 30[Formula: see text]min. The sessions were conducted with a one-day interval between each one. Before the start of the experiment, physical characteristics were measured, and proprioception, balance control ability, and CVA were evaluated. The exercise program significantly improved the stability index (SI) in the eyes-closed state. The biofeedback program resulted in improvement in left rotation, and the CVA was significantly improved after all exercise sessions. In conclusion, a neck correction exercise program that actively moves muscles may have a potential positive impact on balance control ability. Biofeedback equipment might aid in enhancing proprioception by preventing forward head posture (FHP).","PeriodicalId":50135,"journal":{"name":"Journal of Mechanics in Medicine and Biology","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135251913","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-04DOI: 10.1142/s0219519423400961
Minning Zhou, Lin Zhou, Mengjiao Pan, Xiang Chen
One of the design objectives of a product is to create a positive emotional user experience. Through careful design, the product can evoke emotional resonance in users and stimulate their pleasure and satisfaction. Therefore, emotion recognition is crucial for parameterized product design. Considering that emotion recognition based on electroencephalogram (EEG) signals is more objective and accurate compared to methods such as text and surveys, this paper proposes an emotion analysis model based on long short-term memory (LSTM) and EEG and applies it to parameterized design. The main contributions of this paper are as follows. (1) Constructing a high-accuracy emotion recognition model. First, EEG data reflecting the characteristic patterns of brain activities in different emotional states are collected through EEG electrodes. Then, the EEG data are input into the LSTM network for training, enabling it to learn and capture the features associated with emotional states. During the training process, the model learns to extract crucial emotional features from the EEG data for emotion state recognition. This model can automatically learn emotional features, handle long-term dependencies and provide a more accurate and reliable solution for emotion recognition tasks. (2) Creating an EEG dataset specifically for evaluating emotions related to a product and using the trained emotion recognition model to classify this dataset, obtaining emotion classification results. The emotion classification results can be used to determine which parameter designs in product development need to be retained or discarded. These parameter designs can involve aspects such as user experience, functionality, aesthetics, usability and user-friendliness. Decisions can be made based on the emotion classification results to improve the quality and user satisfaction of the product.
{"title":"An emotion recognition model based on long short-term memory networks and EEG signals and its application in parametric design","authors":"Minning Zhou, Lin Zhou, Mengjiao Pan, Xiang Chen","doi":"10.1142/s0219519423400961","DOIUrl":"https://doi.org/10.1142/s0219519423400961","url":null,"abstract":"One of the design objectives of a product is to create a positive emotional user experience. Through careful design, the product can evoke emotional resonance in users and stimulate their pleasure and satisfaction. Therefore, emotion recognition is crucial for parameterized product design. Considering that emotion recognition based on electroencephalogram (EEG) signals is more objective and accurate compared to methods such as text and surveys, this paper proposes an emotion analysis model based on long short-term memory (LSTM) and EEG and applies it to parameterized design. The main contributions of this paper are as follows. (1) Constructing a high-accuracy emotion recognition model. First, EEG data reflecting the characteristic patterns of brain activities in different emotional states are collected through EEG electrodes. Then, the EEG data are input into the LSTM network for training, enabling it to learn and capture the features associated with emotional states. During the training process, the model learns to extract crucial emotional features from the EEG data for emotion state recognition. This model can automatically learn emotional features, handle long-term dependencies and provide a more accurate and reliable solution for emotion recognition tasks. (2) Creating an EEG dataset specifically for evaluating emotions related to a product and using the trained emotion recognition model to classify this dataset, obtaining emotion classification results. The emotion classification results can be used to determine which parameter designs in product development need to be retained or discarded. These parameter designs can involve aspects such as user experience, functionality, aesthetics, usability and user-friendliness. Decisions can be made based on the emotion classification results to improve the quality and user satisfaction of the product.","PeriodicalId":50135,"journal":{"name":"Journal of Mechanics in Medicine and Biology","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135548631","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-04DOI: 10.1142/s0219519423401024
Xuan Dong, Xuetao Mao, Jian Yao
Medical image segmentation holds significant importance for doctors, patients, and the entire health care industry. For doctors, it provides more accurate information about cardiac structures, aiding in improving diagnoses and treatment decisions. For patients, segmentation techniques enable personalized medical care, enhancing treatment outcomes and satisfaction. The entire health care sector benefits from the advancement of this technology, driving the development of medical science and contributing to better health care quality and patient well-being. Additionally, segmentation plays a crucial role in research and education, facilitating the accumulation and dissemination of medical knowledge. In summary, the application of medical image segmentation has profound implications for progress in the medical field and patient welfare. In recent years, with technological advancements and innovative algorithms, medical image quality has greatly improved, with higher resolution and reduced noise and artifacts. Simultaneously, the application of deep learning techniques has made the automatic analysis and diagnosis of medical images more precise and efficient. However, due to the complex structures and diversity often present in medical images, models tend to have limited generalization across different datasets, leading to unstable segmentation performance. Considering the excellent image segmentation performance of the three-dimensional (3D) U-Net model, this study introduces an improved spatial attention mechanism on the basis of the 3D U-Net model to enhance its segmentation performance. The spatial attention mechanism enhances the model’s feature extraction capabilities. The enhanced network can capture dependencies among features across both channel and spatial dimensions in the entire global scope. Additionally, it can strengthen any two correlated features within the input feature vector, thereby enhancing the model’s representational capacity. Through detailed experimental validation, the effectiveness of the proposed model is thoroughly demonstrated. Its superiority in performance and computational efficiency positions it as a significant breakthrough in the medical image segmentation field, providing a strong foundation for future research and clinical practice in medical image processing.
{"title":"A Novel Cardiac Image Segmentation Method Using an Optimized 3D U-Net Model","authors":"Xuan Dong, Xuetao Mao, Jian Yao","doi":"10.1142/s0219519423401024","DOIUrl":"https://doi.org/10.1142/s0219519423401024","url":null,"abstract":"Medical image segmentation holds significant importance for doctors, patients, and the entire health care industry. For doctors, it provides more accurate information about cardiac structures, aiding in improving diagnoses and treatment decisions. For patients, segmentation techniques enable personalized medical care, enhancing treatment outcomes and satisfaction. The entire health care sector benefits from the advancement of this technology, driving the development of medical science and contributing to better health care quality and patient well-being. Additionally, segmentation plays a crucial role in research and education, facilitating the accumulation and dissemination of medical knowledge. In summary, the application of medical image segmentation has profound implications for progress in the medical field and patient welfare. In recent years, with technological advancements and innovative algorithms, medical image quality has greatly improved, with higher resolution and reduced noise and artifacts. Simultaneously, the application of deep learning techniques has made the automatic analysis and diagnosis of medical images more precise and efficient. However, due to the complex structures and diversity often present in medical images, models tend to have limited generalization across different datasets, leading to unstable segmentation performance. Considering the excellent image segmentation performance of the three-dimensional (3D) U-Net model, this study introduces an improved spatial attention mechanism on the basis of the 3D U-Net model to enhance its segmentation performance. The spatial attention mechanism enhances the model’s feature extraction capabilities. The enhanced network can capture dependencies among features across both channel and spatial dimensions in the entire global scope. Additionally, it can strengthen any two correlated features within the input feature vector, thereby enhancing the model’s representational capacity. Through detailed experimental validation, the effectiveness of the proposed model is thoroughly demonstrated. Its superiority in performance and computational efficiency positions it as a significant breakthrough in the medical image segmentation field, providing a strong foundation for future research and clinical practice in medical image processing.","PeriodicalId":50135,"journal":{"name":"Journal of Mechanics in Medicine and Biology","volume":"221 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135548639","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-04DOI: 10.1142/s0219519423401012
Ke Song, Duo Chen
A new nonlinear beamformer named Double-Stage Delay Multiply and Sum (DS-DMAS) has recently been proposed as a variant of the Delay Multiply and Sum (DMAS) algorithm. DS-DMAS expands DMAS into a summation of multiple terms and considers this summation as Delay and Sum (DAS). In order to address the shortage of DAS, DS-DMAS replaced the DAS with DMAS. However, the construction of the new signal in the DS-DMAS algorithm still employs the DAS method. While DAS is a well-established and reliable method, its output is solely dependent on the signal amplitude. Therefore, signal similarity-based methods such as the Coherence Factor (CF) and the Sign Coherence Factor (SCF) have been proposed to weigh the DAS output and optimize its performance. Taking this into consideration, we incorporated the CF and SCF to weigh each newly generated signal in DS-DMAS, resulting in the Coherence Factor-based Double-Stage Delay Multiply and Sum (DS-DMAS-CF) and the Sign Coherence Factor-based Double-Stage Delay Multiply and Sum (DS-DMAS-SCF) approaches. Our focus is primarily on comparing the performance of DS-DMAS-CF and DS-DMAS-SCF. The results indicate that DS-DMAS-SCF exhibits better noise suppression capabilities compared to DS-DMAS-CF.
{"title":"A Comparison of Coherence Factor and Sign Coherence Factor Applied to a Non-Linear Beamformer","authors":"Ke Song, Duo Chen","doi":"10.1142/s0219519423401012","DOIUrl":"https://doi.org/10.1142/s0219519423401012","url":null,"abstract":"A new nonlinear beamformer named Double-Stage Delay Multiply and Sum (DS-DMAS) has recently been proposed as a variant of the Delay Multiply and Sum (DMAS) algorithm. DS-DMAS expands DMAS into a summation of multiple terms and considers this summation as Delay and Sum (DAS). In order to address the shortage of DAS, DS-DMAS replaced the DAS with DMAS. However, the construction of the new signal in the DS-DMAS algorithm still employs the DAS method. While DAS is a well-established and reliable method, its output is solely dependent on the signal amplitude. Therefore, signal similarity-based methods such as the Coherence Factor (CF) and the Sign Coherence Factor (SCF) have been proposed to weigh the DAS output and optimize its performance. Taking this into consideration, we incorporated the CF and SCF to weigh each newly generated signal in DS-DMAS, resulting in the Coherence Factor-based Double-Stage Delay Multiply and Sum (DS-DMAS-CF) and the Sign Coherence Factor-based Double-Stage Delay Multiply and Sum (DS-DMAS-SCF) approaches. Our focus is primarily on comparing the performance of DS-DMAS-CF and DS-DMAS-SCF. The results indicate that DS-DMAS-SCF exhibits better noise suppression capabilities compared to DS-DMAS-CF.","PeriodicalId":50135,"journal":{"name":"Journal of Mechanics in Medicine and Biology","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135548638","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-30DOI: 10.1142/s0219519423020049
Esteban Peña Pitarch, Eddie Y. K. Ng
Journal of Mechanics in Medicine and BiologyOnline Ready No AccessPREFACE — A SPECIAL SELECTION ON RECENT ADVANCES IN BIOMECHANICAL ENGINEERING: PART IIEsteban Peña Pitarch and Eddie Y. K. NgEsteban Peña PitarchUniversitat Politècnica de Catalunya (UPC), Spain and Eddie Y. K. NgNanyang Technological University, Singaporehttps://doi.org/10.1142/S0219519423020049Cited by:0 Next AboutSectionsView articleView Full TextPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack CitationsRecommend to Library ShareShare onFacebookTwitterLinked InRedditEmail View article References 1. Liu F, Ng EYK, Zi Chen, A special section on biological mechanics, J Mech Med Biol 15(6) :1502002-1–1502002-3, 2015. Link, ISI, Google Scholar2. Liu F, Ng EYK, A special section on biological mechanics, J Mech Med Biol 16(8) :1602002-1–1602002-4, 2016. ISI, Google Scholar3. Liu F, Ng EYK, A special section on biomedical imaging in diagnosis and treatment (Part 1), J Med Imag Health Inform 6(5) :1209–1211, 2016. ISI, Google Scholar4. Liu F, Ng EYK, A special section on biomedical imaging in diagnosis and treatment (Part 2), J Med Imag Health Inform 16(7) :1670–1672, 2016. ISI, Google Scholar5. Liu F, Ng EYK, A special section on biomedical imaging in diagnosis and treatment (Part 3), J Med Imag Health Inform 17(1) :126–128, 2017. Google Scholar6. Liu F, Ng EYK, A special section on methods and application in biomedical imaging (Part 1), J Med Imag Health Inform 7(5) :919–921, 2017. ISI, Google Scholar7. Liu F, Ng EYK, A special section on methods and application in biomedical imaging (Part 2), J Med Imag Health Inform 7(7) :1522–1524, 2017. ISI, Google Scholar8. Liu F, Ng EYK, A special section on biological mechanics, J Mech Med Biol 17(7) :1702002-1–1702002-7, 2017. ISI, Google Scholar9. Liu F, Ng EYK, A special section on methods and application in biomedical imaging (Part 3), J Med Imag Health Inform 8(1) :1–4, 2018. ISI, Google Scholar10. Gomez L, Ng EYK, A special section on methods and application in biomedical imaging (Part 1), J Med Imag Health Inform 8(7) :1364–1367, 2018. ISI, Google Scholar11. Gomez L, Ng EYK, A special section on methods and application in biomedical imaging (Part 2), J Med Imag Health Inform 8(8): 1607–1610, 2018. ISI, Google Scholar12. Peña E, Drochon A, Ng EYK, A special selection on biological applications of mechanics, J Mech Med Biol 18(7) :1802001-1–1802001-8, 2018. ISI, Google Scholar13. Peña E, Drochon A, Ng EYK, A special selection on biological applications of mechanics, J Mech Med Biol 18(8) :1802002-1–1802002-8, 2018. ISI, Google Scholar14. Gomez L, Ng EYK, A special section on methods and application in biomedical imaging (Part 3), J Med Imag Health Inform 9(1) :43–46, 2019. ISI, Google Scholar15. Gomez L, Ng EYK, A special section on methods and application in biomedical imaging (Part 1), J Med Imag Health Inform 9(7): 1415–1417, 2019. ISI, Google Scholar16. Gomez L, Ng EYK, A special section on methods and application in biomedical ima
医学和生物学力学杂志在线准备不可访问-生物力学工程最新进展的特别选择:PART IIEsteban Peña Pitarch和Eddie Y. K. NgEsteban Peña PitarchUniversitat politicnica de Catalunya (UPC)， Spain和Eddie Y. K. NgEsteban新加坡杨洋理工大学https://doi.org/10.1142/S0219519423020049Cited by:0下一篇文章章节查看文章查看全文pdf /EPUB工具添加到收藏列表下载CitationsTrack citations推荐到图书馆分享分享在facebook上推特链接在redditemail查看文章参考文献1。刘峰，吴彦耀，子晨，生物力学专题，机械医学与生物学报，15(6):1502002-1-1502002-3,2015。链接，ISI, Google Scholar2。刘峰，吴彦科，生物力学专题，机械医学与生物学报，16(8):1602002-1-1602002-4,2016。ISI, Google Scholar3。刘峰，吴彦凯，生物医学影像在诊断和治疗中的应用(上)，中国医学影像杂志，2016(5):1209-1211。ISI, Google Scholar4。刘峰，吴彦凯，生物医学影像在诊断和治疗中的应用(下)，医学影像与卫生杂志，16(7):1670-1672,2016。ISI, Google Scholar5。刘峰，吴彦凯，生物医学影像在诊断和治疗中的应用(三)，中国医学影像杂志，17(1):126-128,2017。谷歌Scholar6。刘峰，吴彦凯，生物医学成像方法与应用研究(1)，医学影像与健康杂志，7(5):919-921,2017。ISI, Google Scholar7。刘峰，吴彦凯，生物医学成像方法与应用研究(下)，医学影像与健康，2017(7):1522-1524。ISI, Google Scholar8。刘峰，吴彦科，生物力学专题，机械医学与生物学报，17(7):1702002-1-1702002-7,2017。ISI，谷歌搜索。刘峰，吴彦凯，生物医学成像方法及应用研究(三)，中国医学影像杂志，2018(1):1 - 4。ISI, Google Scholar10。王晓明，王晓明，王晓明，生物医学成像技术的研究进展(1)，中国医学杂志，2018(7):1364-1367。ISI，谷歌搜索。王晓明，王晓明，王晓明，生物医学成像技术的研究进展(二)，中国医学杂志，2018,34(8):1070 - 1080。ISI，谷歌搜索。Peña E, Drochon A, Ng EYK，一种特殊选择的力学在生物中的应用，机械医学，18(7):1802001-1 - 1802001- 8,2018。ISI, Google Scholar13。Peña E, Drochon A, Ng EYK，一种特殊的生物力学应用选择，机械医学，18(8):1802002-1-1802002-8,2018。ISI, Google Scholar14。王晓明，吴彦宏，生物医学成像技术的研究进展(第三部分)，中国医学影像杂志，2019,31(1):449 - 456。ISI，谷歌搜索。王晓明，吴彦宏，生物医学成像技术的研究进展(1)，中国医学杂志，2019(7):1415-1417。ISI, Google Scholar16。王志强，吴彦宏，生物医学成像技术的研究进展(二)，中国医学杂志，2019(9):1849-1852。ISI, Google Scholar17。[Peña]王志强，王志强，王志强，生物力学在医学上的应用——(1).中国生物医学工程学报，2019(7):1902003-1 - 1902003- 8,2019。ISI, Google Scholar18。[Peña]王志强，王志强，王志强，生物力学在医学中的应用——(下)，中国医学工程学报，19(8):1902004- 1902004- 8,2019。ISI, Google Scholar19。王志强，吴彦宏，生物医学成像技术的研究进展(3)，中国医学杂志，2010(3):661 - 661,2020。ISI, Google Scholar20。张建军，张建军，张建军，生物医学成像技术的研究进展(1)，中国医学杂志，2010(11):662 - 662,2020。ISI, Google Scholar21。[Peña]王志强，王志强，王志强。机械工程在生物医学中的应用[J] .中国机械工程学报，2016(9):2002001-1-2002001-7,2020。ISI, Google Scholar22。[Peña]王志强，王志强，王志强，机械工程在生物医学中的应用(下)，机械医学与生物医学杂志，20(10):2002002-1-2002002-8,2020.]ISI, Google Scholar23。王晓明，王晓明，王晓明。机器学习在人体健康评估中的应用[J] .中国生物医学工程学报，21(5):591 - 591,2012。谷歌Scholar24。Peña E, Ng EYK，生物力学在医学科学中的特殊应用-第一部分，机械医学，21(9):2102002-1-2102002-6,2021。谷歌Scholar25。Peña E, Ng EYK，生物力学在医学科学中的特殊应用-第二部分，机械医学，21(10):2102003-1 - 2102003- 7,2021。ISI, Google Scholar26。Peña，吴彦勇，吴彦宏，生物力学新技术的选择-第一部分，机械医学，22(3):2202001,1 - 2202001,22,2022。谷歌Scholar27。Peña，吴彦勇，吴彦宏，生物力学新技术的选择-第二部分，机械医学杂志，22(8):2202002-1-2202002-8,2022。谷歌Scholar28。
{"title":"PREFACE — A SPECIAL SELECTION ON RECENT ADVANCES IN BIOMECHANICAL ENGINEERING: PART II","authors":"Esteban Peña Pitarch, Eddie Y. K. Ng","doi":"10.1142/s0219519423020049","DOIUrl":"https://doi.org/10.1142/s0219519423020049","url":null,"abstract":"Journal of Mechanics in Medicine and BiologyOnline Ready No AccessPREFACE — A SPECIAL SELECTION ON RECENT ADVANCES IN BIOMECHANICAL ENGINEERING: PART IIEsteban Peña Pitarch and Eddie Y. K. NgEsteban Peña PitarchUniversitat Politècnica de Catalunya (UPC), Spain and Eddie Y. K. NgNanyang Technological University, Singaporehttps://doi.org/10.1142/S0219519423020049Cited by:0 Next AboutSectionsView articleView Full TextPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack CitationsRecommend to Library ShareShare onFacebookTwitterLinked InRedditEmail View article References 1. Liu F, Ng EYK, Zi Chen, A special section on biological mechanics, J Mech Med Biol 15(6) :1502002-1–1502002-3, 2015. Link, ISI, Google Scholar2. Liu F, Ng EYK, A special section on biological mechanics, J Mech Med Biol 16(8) :1602002-1–1602002-4, 2016. ISI, Google Scholar3. Liu F, Ng EYK, A special section on biomedical imaging in diagnosis and treatment (Part 1), J Med Imag Health Inform 6(5) :1209–1211, 2016. ISI, Google Scholar4. Liu F, Ng EYK, A special section on biomedical imaging in diagnosis and treatment (Part 2), J Med Imag Health Inform 16(7) :1670–1672, 2016. ISI, Google Scholar5. Liu F, Ng EYK, A special section on biomedical imaging in diagnosis and treatment (Part 3), J Med Imag Health Inform 17(1) :126–128, 2017. Google Scholar6. Liu F, Ng EYK, A special section on methods and application in biomedical imaging (Part 1), J Med Imag Health Inform 7(5) :919–921, 2017. ISI, Google Scholar7. Liu F, Ng EYK, A special section on methods and application in biomedical imaging (Part 2), J Med Imag Health Inform 7(7) :1522–1524, 2017. ISI, Google Scholar8. Liu F, Ng EYK, A special section on biological mechanics, J Mech Med Biol 17(7) :1702002-1–1702002-7, 2017. ISI, Google Scholar9. Liu F, Ng EYK, A special section on methods and application in biomedical imaging (Part 3), J Med Imag Health Inform 8(1) :1–4, 2018. ISI, Google Scholar10. Gomez L, Ng EYK, A special section on methods and application in biomedical imaging (Part 1), J Med Imag Health Inform 8(7) :1364–1367, 2018. ISI, Google Scholar11. Gomez L, Ng EYK, A special section on methods and application in biomedical imaging (Part 2), J Med Imag Health Inform 8(8): 1607–1610, 2018. ISI, Google Scholar12. Peña E, Drochon A, Ng EYK, A special selection on biological applications of mechanics, J Mech Med Biol 18(7) :1802001-1–1802001-8, 2018. ISI, Google Scholar13. Peña E, Drochon A, Ng EYK, A special selection on biological applications of mechanics, J Mech Med Biol 18(8) :1802002-1–1802002-8, 2018. ISI, Google Scholar14. Gomez L, Ng EYK, A special section on methods and application in biomedical imaging (Part 3), J Med Imag Health Inform 9(1) :43–46, 2019. ISI, Google Scholar15. Gomez L, Ng EYK, A special section on methods and application in biomedical imaging (Part 1), J Med Imag Health Inform 9(7): 1415–1417, 2019. ISI, Google Scholar16. Gomez L, Ng EYK, A special section on methods and application in biomedical ima","PeriodicalId":50135,"journal":{"name":"Journal of Mechanics in Medicine and Biology","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136341920","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Influence of Femur Length on Asymmetry of Prosthetic Gait Biomechanics in Transfemoral Amputation","authors":"K. Ezhumalai, Arpita Padhi, Rajesh Kumar Mohanty, Rojaleen Pradhan, Patitapaban Mohanty","doi":"10.1142/s0219519423500999","DOIUrl":"https://doi.org/10.1142/s0219519423500999","url":null,"abstract":"","PeriodicalId":50135,"journal":{"name":"Journal of Mechanics in Medicine and Biology","volume":"156 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135247323","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-29DOI: 10.1142/s0219519423500987
Shruti Arora, Sushma Jain, Inderveer Chana
{"title":"Predicting Cardiac Health Using Sub-Component of a Phonocardiogram","authors":"Shruti Arora, Sushma Jain, Inderveer Chana","doi":"10.1142/s0219519423500987","DOIUrl":"https://doi.org/10.1142/s0219519423500987","url":null,"abstract":"","PeriodicalId":50135,"journal":{"name":"Journal of Mechanics in Medicine and Biology","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135247174","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-16DOI: 10.1142/s021951942340105x
Linping Wang, Xi Lin, Zuobing Zhang, Jinrong Lin, Tao Yang, Xiaodong Zhang
{"title":"Mask Classification Segmentation Method Based on Gourped Convolution and Spatial Pyramidal Convolution Model for Thyroid Cancer Identification","authors":"Linping Wang, Xi Lin, Zuobing Zhang, Jinrong Lin, Tao Yang, Xiaodong Zhang","doi":"10.1142/s021951942340105x","DOIUrl":"https://doi.org/10.1142/s021951942340105x","url":null,"abstract":"","PeriodicalId":50135,"journal":{"name":"Journal of Mechanics in Medicine and Biology","volume":"200 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135352490","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-15DOI: 10.1142/s0219519423400948
Sihan Fan, Xiaokun Dai, Xueqin Ji, Xinrong Chen
{"title":"Augmented reality-based nasal endoscope video reconstruction and registration","authors":"Sihan Fan, Xiaokun Dai, Xueqin Ji, Xinrong Chen","doi":"10.1142/s0219519423400948","DOIUrl":"https://doi.org/10.1142/s0219519423400948","url":null,"abstract":"","PeriodicalId":50135,"journal":{"name":"Journal of Mechanics in Medicine and Biology","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135437732","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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