Pub Date : 2023-10-01DOI: 10.1007/s40846-023-00827-7
Shinichi Fukuhara, Masahiro Ikeno, Hisao Oka
{"title":"Basic Characteristics of Submental Mechanomyography and Electromyography Measured Simultaneously During Tongue Lift Using a Novel Muscle Function Measurement Device","authors":"Shinichi Fukuhara, Masahiro Ikeno, Hisao Oka","doi":"10.1007/s40846-023-00827-7","DOIUrl":"https://doi.org/10.1007/s40846-023-00827-7","url":null,"abstract":"","PeriodicalId":50133,"journal":{"name":"Journal of Medical and Biological Engineering","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134935060","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":"Severity of Liver Cirrhosis Evaluated by Digital Subtraction Angiography Using Quantitative Color-Coding Analysis Before Transarterial Embolization","authors":"Lung-Hui Giiang, Chang-Hsien Liu, Chih-Yung Yu, Te-Pao Lin, Hsiang-Cheng Chen, Chun-Jung Juan, Yu-Ching Chou","doi":"10.1007/s40846-023-00826-8","DOIUrl":"https://doi.org/10.1007/s40846-023-00826-8","url":null,"abstract":"","PeriodicalId":50133,"journal":{"name":"Journal of Medical and Biological Engineering","volume":"95 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135809595","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":"Evaluation of the Effect of Cortical Bone Thickness on Stress Distribution in Implant-Supported Fixed Prostheses","authors":"Elifnur Güzelce Sultanoğlu, Zeliha Betül Özsağir, Alanur Çiftçi Şişman, Emre Tokar","doi":"10.1007/s40846-023-00830-y","DOIUrl":"https://doi.org/10.1007/s40846-023-00830-y","url":null,"abstract":"","PeriodicalId":50133,"journal":{"name":"Journal of Medical and Biological Engineering","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135849200","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 : 2023-10-01DOI: 10.1007/s40846-023-00828-6
Parisa Tavana, Mahdi Akraminia, Abbas Koochari, Abolfazl Bagherifard
{"title":"Rethinking U-Net Deep Neural Network for Spine Radiographic Images-Based Spine Vertebrae Segmentation","authors":"Parisa Tavana, Mahdi Akraminia, Abbas Koochari, Abolfazl Bagherifard","doi":"10.1007/s40846-023-00828-6","DOIUrl":"https://doi.org/10.1007/s40846-023-00828-6","url":null,"abstract":"","PeriodicalId":50133,"journal":{"name":"Journal of Medical and Biological Engineering","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135707237","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 : 2023-09-26DOI: 10.1007/s40846-023-00823-x
Michelle Wang, Budhachandra Khundrakpam, Thomas Vaughan
Abstract Purpose Stroke patients may need to undergo rehabilitation therapy to improve their mobility. Electromyography (EMG) can be used to improve the effectiveness of at-home therapy programs, as it can assess recovery progress in the absence of a health professional. In particular, EMG armbands have the advantage of being easy to use compared to other EMG technologies, which could allow patients to complete therapy programs without external assistance. However, it is unclear whether there are drawbacks associated with the fixed electrode placement imposed by current armband designs. This study compared the hand gesture prediction capabilities of an off-the-shelf EMG armband with fixed electrode placement and an EMG setup with flexible electrode positioning. Methods Ten able-bodied participants performed a series of hand and finger gestures with their dominant hand, once with an EMG armband (Untargeted condition) and once with electrodes deliberately placed on specific muscles (Targeted condition). EMG features were extracted from overlapping sliding windows and were used to (1) classify the gestures and (2) predict finger joint positions as measured by a robotic hand exoskeleton. Results For the classification task, a logistic regression model performed significantly better ( $$p < 0.001$$ p<0.001 ) for the Targeted condition ( $$55.8% pm 10.1%$$ 55.8%±10.1% ) compared to the Untargeted condition ( $$47.9% pm 11.6%$$ 47.9%±11.6% ). For the regression task, a k -nearest neighbours model obtained significantly lower ( $$p = 0.007$$ p=0.007 ) mean RMSE values for the Targeted condition ( $$0.260 pm 0.037$$ 0.260±0.037 ) compared to the Untargeted condition ( $$0.270 pm 0.043$$ 0.270±0.043 ). Conclusion We observed a trade-off between predictive accuracy and ease-of-use of the EMG devices used in this study. It is important to consider such a trade-off when developing clinical applications such as at-home stroke rehabilitation therapy programs.
摘要目的脑卒中患者可能需要接受康复治疗以改善其活动能力。肌电图(EMG)可以用来提高家庭治疗方案的有效性，因为它可以在没有健康专业人员的情况下评估康复进展。特别是，与其他肌电图技术相比，肌电臂带具有易于使用的优势，可以使患者在没有外部帮助的情况下完成治疗计划。然而，目前尚不清楚是否存在与当前臂章设计所施加的固定电极放置相关的缺点。本研究比较了固定电极放置的现成肌电臂带和柔性电极定位的肌电臂带的手势预测能力。方法10名身体健全的参与者用惯用手进行一系列手部和手指手势，一次是带肌电臂带(非目标组)，一次是在特定肌肉上放置电极(目标组)。从重叠的滑动窗口中提取肌电特征，并用于(1)对手势进行分类，(2)预测由机器人手外骨骼测量的手指关节位置。结果对于分类任务，逻辑回归模型的表现明显更好($$p < 0.001$$ p ＆lt;0.001)，目标条件($$55.8% pm 10.1%$$ 55.8) % ± 10.1 % ) compared to the Untargeted condition ( $$47.9% pm 11.6%$$ 47.9 % ± 11.6 % ). For the regression task, a k -nearest neighbours model obtained significantly lower ( $$p = 0.007$$ p = 0.007 ) mean RMSE values for the Targeted condition ( $$0.260 pm 0.037$$ 0.260 ± 0.037 ) compared to the Untargeted condition ( $$0.270 pm 0.043$$ 0.270 ± 0.043 ). Conclusion We observed a trade-off between predictive accuracy and ease-of-use of the EMG devices used in this study. It is important to consider such a trade-off when developing clinical applications such as at-home stroke rehabilitation therapy programs.
{"title":"Effects of Electrode Position Targeting in Noninvasive Electromyography Technologies for Finger and Hand Movement Prediction","authors":"Michelle Wang, Budhachandra Khundrakpam, Thomas Vaughan","doi":"10.1007/s40846-023-00823-x","DOIUrl":"https://doi.org/10.1007/s40846-023-00823-x","url":null,"abstract":"Abstract Purpose Stroke patients may need to undergo rehabilitation therapy to improve their mobility. Electromyography (EMG) can be used to improve the effectiveness of at-home therapy programs, as it can assess recovery progress in the absence of a health professional. In particular, EMG armbands have the advantage of being easy to use compared to other EMG technologies, which could allow patients to complete therapy programs without external assistance. However, it is unclear whether there are drawbacks associated with the fixed electrode placement imposed by current armband designs. This study compared the hand gesture prediction capabilities of an off-the-shelf EMG armband with fixed electrode placement and an EMG setup with flexible electrode positioning. Methods Ten able-bodied participants performed a series of hand and finger gestures with their dominant hand, once with an EMG armband (Untargeted condition) and once with electrodes deliberately placed on specific muscles (Targeted condition). EMG features were extracted from overlapping sliding windows and were used to (1) classify the gestures and (2) predict finger joint positions as measured by a robotic hand exoskeleton. Results For the classification task, a logistic regression model performed significantly better ( $$p < 0.001$$ <mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"> <mml:mrow> <mml:mi>p</mml:mi> <mml:mo><</mml:mo> <mml:mn>0.001</mml:mn> </mml:mrow> </mml:math> ) for the Targeted condition ( $$55.8% pm 10.1%$$ <mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"> <mml:mrow> <mml:mn>55.8</mml:mn> <mml:mo>%</mml:mo> <mml:mo>±</mml:mo> <mml:mn>10.1</mml:mn> <mml:mo>%</mml:mo> </mml:mrow> </mml:math> ) compared to the Untargeted condition ( $$47.9% pm 11.6%$$ <mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"> <mml:mrow> <mml:mn>47.9</mml:mn> <mml:mo>%</mml:mo> <mml:mo>±</mml:mo> <mml:mn>11.6</mml:mn> <mml:mo>%</mml:mo> </mml:mrow> </mml:math> ). For the regression task, a k -nearest neighbours model obtained significantly lower ( $$p = 0.007$$ <mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"> <mml:mrow> <mml:mi>p</mml:mi> <mml:mo>=</mml:mo> <mml:mn>0.007</mml:mn> </mml:mrow> </mml:math> ) mean RMSE values for the Targeted condition ( $$0.260 pm 0.037$$ <mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"> <mml:mrow> <mml:mn>0.260</mml:mn> <mml:mo>±</mml:mo> <mml:mn>0.037</mml:mn> </mml:mrow> </mml:math> ) compared to the Untargeted condition ( $$0.270 pm 0.043$$ <mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"> <mml:mrow> <mml:mn>0.270</mml:mn> <mml:mo>±</mml:mo> <mml:mn>0.043</mml:mn> </mml:mrow> </mml:math> ). Conclusion We observed a trade-off between predictive accuracy and ease-of-use of the EMG devices used in this study. It is important to consider such a trade-off when developing clinical applications such as at-home stroke rehabilitation therapy programs.","PeriodicalId":50133,"journal":{"name":"Journal of Medical and Biological Engineering","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134886089","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 : 2023-09-26DOI: 10.1007/s40846-023-00824-w
Jessica Cantillo-Negrete, Ruben I. Carino-Escobar, Ismael Leyva-Martinez, Aida Barrera-Ortiz, Marlene A. Rodriguez-Barragan, Omar Mendoza-Montoya, Javier M. Antelis
{"title":"Upper Limb Recovery in Cervical Spinal Cord Injury After a Brain-Computer Interface Controlled Functional Electrical Stimulation Intervention","authors":"Jessica Cantillo-Negrete, Ruben I. Carino-Escobar, Ismael Leyva-Martinez, Aida Barrera-Ortiz, Marlene A. Rodriguez-Barragan, Omar Mendoza-Montoya, Javier M. Antelis","doi":"10.1007/s40846-023-00824-w","DOIUrl":"https://doi.org/10.1007/s40846-023-00824-w","url":null,"abstract":"","PeriodicalId":50133,"journal":{"name":"Journal of Medical and Biological Engineering","volume":"88 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134903918","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 : 2023-09-21DOI: 10.1007/s40846-023-00817-9
Lina Van Lint, Lynn Christiaens, Valerie Stroo, Michel Bila, Robin Willaert, Yi Sun, Jeroen Van Dessel
{"title":"Accuracy Comparison of 3D Face Scans Obtained by Portable Stereophotogrammetry and Smartphone Applications","authors":"Lina Van Lint, Lynn Christiaens, Valerie Stroo, Michel Bila, Robin Willaert, Yi Sun, Jeroen Van Dessel","doi":"10.1007/s40846-023-00817-9","DOIUrl":"https://doi.org/10.1007/s40846-023-00817-9","url":null,"abstract":"","PeriodicalId":50133,"journal":{"name":"Journal of Medical and Biological Engineering","volume":"80 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136154577","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 : 2023-09-21DOI: 10.1007/s40846-023-00825-9
Winniecia Dkhar, Rajagopal Kadavigere, Suresh Sukumar, Abhimanyu Pradhan, S Sharath
Abstract Purpose Medical technology has gone a long way in diagnosis and characterization of breast tumors. Diffusion-weighted MR imaging is the state of the art for breast screening and diagnosing. The aim of this meta-analysis is to evaluate the diagnostic performances of diffusion-weighted MR imaging in characterization of breast lesions with different b value in 1.5 T MRI. Method An extensive search on Scopus, Embase, and PubMed databases were performed on studies published between January 2000 and 2020. The systematic seek initially yielded 2467 studies, out of which 27 research were covered on this meta-evaluation. The included studies for meta-analysis utilized different b value and noted that the ADC value was highly influenced by the b value, for differential diagnosis of breast tumors. Results The current meta-analysis has shown the ADC values was lower for malignant breast lesions as compared with benign lesions. The recommended mean threshold ADC was 1.25 ± 0.17 × 10 –3 mm 2 /s range from 0.93 to 1.60 × 10 –3 mm 2 /s for differential diagnosis of breast tumors. Sub-group analysis on the bases of b value showed statistically significant differences in the ADC value of benign and malignant breast tumors. Conclusion In conclusion, we noted that b value has a significant effect in calculating the ADC value of the breast lesions as well as ADC threshold value but lacks standardization. The ADC value measurement has a potential for differentiation between benign and malignant breast lesions.
{"title":"Diagnostic Performances of ADC Value in Diffusion-Weighted MR Imaging for Differential Diagnosis of Breast Lesions in 1.5 T: A Systematic Review and Meta-analysis","authors":"Winniecia Dkhar, Rajagopal Kadavigere, Suresh Sukumar, Abhimanyu Pradhan, S Sharath","doi":"10.1007/s40846-023-00825-9","DOIUrl":"https://doi.org/10.1007/s40846-023-00825-9","url":null,"abstract":"Abstract Purpose Medical technology has gone a long way in diagnosis and characterization of breast tumors. Diffusion-weighted MR imaging is the state of the art for breast screening and diagnosing. The aim of this meta-analysis is to evaluate the diagnostic performances of diffusion-weighted MR imaging in characterization of breast lesions with different b value in 1.5 T MRI. Method An extensive search on Scopus, Embase, and PubMed databases were performed on studies published between January 2000 and 2020. The systematic seek initially yielded 2467 studies, out of which 27 research were covered on this meta-evaluation. The included studies for meta-analysis utilized different b value and noted that the ADC value was highly influenced by the b value, for differential diagnosis of breast tumors. Results The current meta-analysis has shown the ADC values was lower for malignant breast lesions as compared with benign lesions. The recommended mean threshold ADC was 1.25 ± 0.17 × 10 –3 mm 2 /s range from 0.93 to 1.60 × 10 –3 mm 2 /s for differential diagnosis of breast tumors. Sub-group analysis on the bases of b value showed statistically significant differences in the ADC value of benign and malignant breast tumors. Conclusion In conclusion, we noted that b value has a significant effect in calculating the ADC value of the breast lesions as well as ADC threshold value but lacks standardization. The ADC value measurement has a potential for differentiation between benign and malignant breast lesions.","PeriodicalId":50133,"journal":{"name":"Journal of Medical and Biological Engineering","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136129683","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 : 2023-09-07DOI: 10.1007/s40846-023-00818-8
Joonas Liedes, Henri Hellström, O. Rainio, Sarita Murtojärvi, Simona Malaspina, J. Hirvonen, R. Klén, Jukka Kemppainen
{"title":"Automatic Segmentation of Head and Neck Cancer from PET-MRI Data Using Deep Learning","authors":"Joonas Liedes, Henri Hellström, O. Rainio, Sarita Murtojärvi, Simona Malaspina, J. Hirvonen, R. Klén, Jukka Kemppainen","doi":"10.1007/s40846-023-00818-8","DOIUrl":"https://doi.org/10.1007/s40846-023-00818-8","url":null,"abstract":"","PeriodicalId":50133,"journal":{"name":"Journal of Medical and Biological Engineering","volume":" ","pages":""},"PeriodicalIF":2.0,"publicationDate":"2023-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48186648","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 : 2023-09-04DOI: 10.1007/s40846-023-00814-y
Ali Achak, Mohammadreza Hedyehzadeh
{"title":"Determining the Differentiation of Benign and Malignant NME Lesions in Contrast-Enhanced Spectral Mammography Images Based on Convolutional Neural Networks","authors":"Ali Achak, Mohammadreza Hedyehzadeh","doi":"10.1007/s40846-023-00814-y","DOIUrl":"https://doi.org/10.1007/s40846-023-00814-y","url":null,"abstract":"","PeriodicalId":50133,"journal":{"name":"Journal of Medical and Biological Engineering","volume":" ","pages":""},"PeriodicalIF":2.0,"publicationDate":"2023-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45762647","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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