Pub Date : 2024-02-14DOI: 10.3991/ijoe.v20i02.44627
Yazeed Suleiman Al-Rbeihat, Omar M. Hasan
The current paper explores the impact of misalignment between transceivers (referred to as pointing error (PE)) on the performance of transdermal optical wireless (TOW) technology, as indicated by average signal-to-noise ratio (SNR), outage probability (OP), outage rate (OR), and average ergodic capacity (AEC). This study was inspired by the effectiveness of differential phase shift keying (DPSK) in enhancing the reliability of the link in free-space optical communications (FSO). Furthermore, this enhancement was studied and analyzed in consideration of the impact of pointing errors. In particular, this paper presents a mathematical analysis that considers certain characteristics of the channel, limitations within the body, the pointing errors (PEs) between the transceivers, and other specific aspects of the optical unit. The results demonstrate the significant impact of PEs on the reliability of the TOW link and highlight the improvement provided by the DPSK technique. i.e., 3 dB better performance compared to the on-off keying (OOK) modulation technique. Finally, this research demonstrates the practical application of wireless optical technology in the medical field within the wavelength range of 800–1300 nm, with optimal performance observed around 1100 nm.
{"title":"The Impact of Using DPSK Modulation on the Performance of Transdermal Optical Wireless Communications under Pointing Errors","authors":"Yazeed Suleiman Al-Rbeihat, Omar M. Hasan","doi":"10.3991/ijoe.v20i02.44627","DOIUrl":"https://doi.org/10.3991/ijoe.v20i02.44627","url":null,"abstract":"The current paper explores the impact of misalignment between transceivers (referred to as pointing error (PE)) on the performance of transdermal optical wireless (TOW) technology, as indicated by average signal-to-noise ratio (SNR), outage probability (OP), outage rate (OR), and average ergodic capacity (AEC). This study was inspired by the effectiveness of differential phase shift keying (DPSK) in enhancing the reliability of the link in free-space optical communications (FSO). Furthermore, this enhancement was studied and analyzed in consideration of the impact of pointing errors. In particular, this paper presents a mathematical analysis that considers certain characteristics of the channel, limitations within the body, the pointing errors (PEs) between the transceivers, and other specific aspects of the optical unit. The results demonstrate the significant impact of PEs on the reliability of the TOW link and highlight the improvement provided by the DPSK technique. i.e., 3 dB better performance compared to the on-off keying (OOK) modulation technique. Finally, this research demonstrates the practical application of wireless optical technology in the medical field within the wavelength range of 800–1300 nm, with optimal performance observed around 1100 nm.","PeriodicalId":507997,"journal":{"name":"International Journal of Online and Biomedical Engineering (iJOE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139837795","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-14DOI: 10.3991/ijoe.v20i02.42883
Arturo Gago, Jean Marko Aguirre, Lenis Wong
Breast cancer is one of the most significant global health challenges. Effective diagnosis and prognosis prediction are crucial for improving patient outcomes in the case of this disease. As machine learning (ML) has significantly improved prediction models in many disciplines, the goal of this study is to develop a ML system for medical specialists that can accurately predict tumor diagnosis and patient survival for breast cancer patients. For the training of diagnosis and survival prediction, five algorithmic models—decision tree (DT), random forest (RF), naive bayes (NB), support vector machines (SVMs), and gradient boosting—were trained with 569 records from the Breast Cancer Wisconsin dataset and 1,980 records from the Breast Cancer Gene Expression Profiles dataset. The results showed that the NB model exhibited better performance for tumor diagnosis, achieving an accuracy of 95.0%, while RF presented the best results for patient survival, with an accuracy of 76.0%. A survey of medical experts’ experience with the resulting system showed high scores in reliability, performance, satisfaction, usability, and efficiency, confirming that ML systems have the potential to improve breast cancer patient outcomes.
乳腺癌是全球健康面临的最重大挑战之一。有效的诊断和预后预测对于改善这种疾病的患者预后至关重要。由于机器学习（ML）在许多学科中都极大地改进了预测模型，因此本研究的目标是为医学专家开发一种 ML 系统，以准确预测乳腺癌患者的肿瘤诊断和生存期。在诊断和生存预测的训练中，使用了五种算法模型--决策树（DT）、随机森林（RF）、奈夫贝叶斯（NB）、支持向量机（SVM）和梯度提升--对威斯康星乳腺癌数据集的 569 条记录和乳腺癌基因表达谱数据集的 1,980 条记录进行了训练。结果表明，NB 模型在肿瘤诊断方面表现更佳，准确率达到 95.0%，而 RF 模型在患者存活率方面表现最佳，准确率达到 76.0%。对医学专家使用该系统的经验进行的调查显示，该系统在可靠性、性能、满意度、可用性和效率方面都获得了很高的分数，这证实了 ML 系统具有改善乳腺癌患者预后的潜力。
{"title":"Machine Learning System for the Effective Diagnosis and Survival Prediction of Breast Cancer Patients","authors":"Arturo Gago, Jean Marko Aguirre, Lenis Wong","doi":"10.3991/ijoe.v20i02.42883","DOIUrl":"https://doi.org/10.3991/ijoe.v20i02.42883","url":null,"abstract":"Breast cancer is one of the most significant global health challenges. Effective diagnosis and prognosis prediction are crucial for improving patient outcomes in the case of this disease. As machine learning (ML) has significantly improved prediction models in many disciplines, the goal of this study is to develop a ML system for medical specialists that can accurately predict tumor diagnosis and patient survival for breast cancer patients. For the training of diagnosis and survival prediction, five algorithmic models—decision tree (DT), random forest (RF), naive bayes (NB), support vector machines (SVMs), and gradient boosting—were trained with 569 records from the Breast Cancer Wisconsin dataset and 1,980 records from the Breast Cancer Gene Expression Profiles dataset. The results showed that the NB model exhibited better performance for tumor diagnosis, achieving an accuracy of 95.0%, while RF presented the best results for patient survival, with an accuracy of 76.0%. A survey of medical experts’ experience with the resulting system showed high scores in reliability, performance, satisfaction, usability, and efficiency, confirming that ML systems have the potential to improve breast cancer patient outcomes.","PeriodicalId":507997,"journal":{"name":"International Journal of Online and Biomedical Engineering (iJOE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139839329","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-14DOI: 10.3991/ijoe.v20i02.45693
A. Samala, Soha Rawas
The adoption of cloud-based electronic health record (EHR) systems and blockchain technology in healthcare is gaining attention for enhancing data security and interoperability. This research focuses on designing and implementing a blockchain-based cloud EHR system. It explores selecting suitable blockchain technology, cloud infrastructure, and data management methods to ensure patient data confidentiality, integrity, and availability. The architecture and components of the system, including the blockchain network, cloud storage layer, and user interface, are thoroughly discussed. A pilot study evaluates the system’s feasibility and performance, showcasing improved data protection, sharing, and management compared to traditional EHR systems. The potential benefits, drawbacks, and barriers to adoption of a blockchain-based cloud EHR system are examined. This research provides valuable insights and recommendations for healthcare institutions considering the implementation of such systems, addressing the challenges, and offering guidance for successful adoption.
{"title":"Transforming Healthcare Data Management: A Blockchain-Based Cloud EHR System for Enhanced Security and Interoperability","authors":"A. Samala, Soha Rawas","doi":"10.3991/ijoe.v20i02.45693","DOIUrl":"https://doi.org/10.3991/ijoe.v20i02.45693","url":null,"abstract":"The adoption of cloud-based electronic health record (EHR) systems and blockchain technology in healthcare is gaining attention for enhancing data security and interoperability. This research focuses on designing and implementing a blockchain-based cloud EHR system. It explores selecting suitable blockchain technology, cloud infrastructure, and data management methods to ensure patient data confidentiality, integrity, and availability. The architecture and components of the system, including the blockchain network, cloud storage layer, and user interface, are thoroughly discussed. A pilot study evaluates the system’s feasibility and performance, showcasing improved data protection, sharing, and management compared to traditional EHR systems. The potential benefits, drawbacks, and barriers to adoption of a blockchain-based cloud EHR system are examined. This research provides valuable insights and recommendations for healthcare institutions considering the implementation of such systems, addressing the challenges, and offering guidance for successful adoption.","PeriodicalId":507997,"journal":{"name":"International Journal of Online and Biomedical Engineering (iJOE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139777546","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-14DOI: 10.3991/ijoe.v20i02.46817
José L. Serna-Landivar, Madelaine Violeta Risco Sernaqué, Ana Beatriz Rivas Moreano, William C. Algoner, Daniela M. Anticona-Valderrama, Walter Enrique Zúñiga Porras, Carlos Oliva Guevara
Crossed spherical gearing is used in the joints of robotic arm prostheses and allows mobility in 3 degrees of freedom. This paper aims to evaluate the design of a cross-spherical gear with three different materials, PEEK, AISI 304L, and Ti-6Al-4V, for a robotic arm prosthesis by finite element analysis. ANSYS mechanical software (version 2021 R1) was used to perform the static analysis and evaluate the deformations and stresses, modal analysis of natural frequencies and vibration modes, and high cycle fatigue analysis to determine fatigue resistance. The results obtained in the static analysis show that the maximum stresses are in the same zones for the three materials and have similar values. However, the Ti-6Al-4V and ASI 304L materials have a higher safety factor than PEEK, with a value of 5.17. In conclusion, the crossed spherical gearing is numerically validated using the finite element analysis so that the prototype can be later manufactured at an experimental level, and the values obtained for the crossed spherical gearing of the robotic arm prosthesis can be verified.
{"title":"Static, Dynamic, and High Cycle Fatigue Analysis of Crossed Spherical Gearing for Robotic Arm Ball Joint: A Finite Element Analysis Approach","authors":"José L. Serna-Landivar, Madelaine Violeta Risco Sernaqué, Ana Beatriz Rivas Moreano, William C. Algoner, Daniela M. Anticona-Valderrama, Walter Enrique Zúñiga Porras, Carlos Oliva Guevara","doi":"10.3991/ijoe.v20i02.46817","DOIUrl":"https://doi.org/10.3991/ijoe.v20i02.46817","url":null,"abstract":"Crossed spherical gearing is used in the joints of robotic arm prostheses and allows mobility in 3 degrees of freedom. This paper aims to evaluate the design of a cross-spherical gear with three different materials, PEEK, AISI 304L, and Ti-6Al-4V, for a robotic arm prosthesis by finite element analysis. ANSYS mechanical software (version 2021 R1) was used to perform the static analysis and evaluate the deformations and stresses, modal analysis of natural frequencies and vibration modes, and high cycle fatigue analysis to determine fatigue resistance. The results obtained in the static analysis show that the maximum stresses are in the same zones for the three materials and have similar values. However, the Ti-6Al-4V and ASI 304L materials have a higher safety factor than PEEK, with a value of 5.17. In conclusion, the crossed spherical gearing is numerically validated using the finite element analysis so that the prototype can be later manufactured at an experimental level, and the values obtained for the crossed spherical gearing of the robotic arm prosthesis can be verified.","PeriodicalId":507997,"journal":{"name":"International Journal of Online and Biomedical Engineering (iJOE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139778752","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-14DOI: 10.3991/ijoe.v20i02.43099
Eduardo Arias Navarro, Cesar Nahuel Moya, Fiorella Lizano-Sánchez, Carlos Arguedas-Matarrita, César Eduardo Mora Ley, Ignacio Idoyaga
This article presents the results of the educational use of an ultra-concurrent laboratory during the second semester of 2022, in the Cisale Chair of the Common Cycle of the University of Buenos Aires in order to strengthen the experimental scenarios and quality of the process in the teaching of physics. For this purpose, a quantitative descriptive study in which 68 students participated was carried out. This allowed establishing a significant scenario with the implementation of the ultra-concurrent free-fall laboratory to enhance experimental development in physics teaching processes. It is concluded that remote laboratories are promising technologies for teaching physics at the university level. However, it should be clarified that the impact of an educational innovation does not only depend on the technology used, but also on the didactic design with which it is approached.
{"title":"Study of Free Fall Using an Ultra-Concurrent Laboratory at the University","authors":"Eduardo Arias Navarro, Cesar Nahuel Moya, Fiorella Lizano-Sánchez, Carlos Arguedas-Matarrita, César Eduardo Mora Ley, Ignacio Idoyaga","doi":"10.3991/ijoe.v20i02.43099","DOIUrl":"https://doi.org/10.3991/ijoe.v20i02.43099","url":null,"abstract":"This article presents the results of the educational use of an ultra-concurrent laboratory during the second semester of 2022, in the Cisale Chair of the Common Cycle of the University of Buenos Aires in order to strengthen the experimental scenarios and quality of the process in the teaching of physics. For this purpose, a quantitative descriptive study in which 68 students participated was carried out. This allowed establishing a significant scenario with the implementation of the ultra-concurrent free-fall laboratory to enhance experimental development in physics teaching processes. It is concluded that remote laboratories are promising technologies for teaching physics at the university level. However, it should be clarified that the impact of an educational innovation does not only depend on the technology used, but also on the didactic design with which it is approached.","PeriodicalId":507997,"journal":{"name":"International Journal of Online and Biomedical Engineering (iJOE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139838681","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-14DOI: 10.3991/ijoe.v20i02.44627
Yazeed Suleiman Al-Rbeihat, Omar M. Hasan
The current paper explores the impact of misalignment between transceivers (referred to as pointing error (PE)) on the performance of transdermal optical wireless (TOW) technology, as indicated by average signal-to-noise ratio (SNR), outage probability (OP), outage rate (OR), and average ergodic capacity (AEC). This study was inspired by the effectiveness of differential phase shift keying (DPSK) in enhancing the reliability of the link in free-space optical communications (FSO). Furthermore, this enhancement was studied and analyzed in consideration of the impact of pointing errors. In particular, this paper presents a mathematical analysis that considers certain characteristics of the channel, limitations within the body, the pointing errors (PEs) between the transceivers, and other specific aspects of the optical unit. The results demonstrate the significant impact of PEs on the reliability of the TOW link and highlight the improvement provided by the DPSK technique. i.e., 3 dB better performance compared to the on-off keying (OOK) modulation technique. Finally, this research demonstrates the practical application of wireless optical technology in the medical field within the wavelength range of 800–1300 nm, with optimal performance observed around 1100 nm.
{"title":"The Impact of Using DPSK Modulation on the Performance of Transdermal Optical Wireless Communications under Pointing Errors","authors":"Yazeed Suleiman Al-Rbeihat, Omar M. Hasan","doi":"10.3991/ijoe.v20i02.44627","DOIUrl":"https://doi.org/10.3991/ijoe.v20i02.44627","url":null,"abstract":"The current paper explores the impact of misalignment between transceivers (referred to as pointing error (PE)) on the performance of transdermal optical wireless (TOW) technology, as indicated by average signal-to-noise ratio (SNR), outage probability (OP), outage rate (OR), and average ergodic capacity (AEC). This study was inspired by the effectiveness of differential phase shift keying (DPSK) in enhancing the reliability of the link in free-space optical communications (FSO). Furthermore, this enhancement was studied and analyzed in consideration of the impact of pointing errors. In particular, this paper presents a mathematical analysis that considers certain characteristics of the channel, limitations within the body, the pointing errors (PEs) between the transceivers, and other specific aspects of the optical unit. The results demonstrate the significant impact of PEs on the reliability of the TOW link and highlight the improvement provided by the DPSK technique. i.e., 3 dB better performance compared to the on-off keying (OOK) modulation technique. Finally, this research demonstrates the practical application of wireless optical technology in the medical field within the wavelength range of 800–1300 nm, with optimal performance observed around 1100 nm.","PeriodicalId":507997,"journal":{"name":"International Journal of Online and Biomedical Engineering (iJOE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139778069","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-14DOI: 10.3991/ijoe.v20i02.44845
Wafae Abbaoui, Sara Retal, Soumia Ziti, Brahim El Bhiri, Hassan Moussif
This study presents a comprehensive exploration of deep learning models for precise brain ischemic stroke classification using medical data from Morocco. Following the OSEMN approach, our methodology leverages transfer learning with the VGG-16 architecture and employs data augmentation techniques to enhance model performance. Our developed model achieved a remarkable validation accuracy of 90%, surpassing alternative state-of-theart models (ResNet50: 87.0%, InceptionV3: 82.0%, VGG-19: 81.0%). Notably, all models were rigorously evaluated on the same meticulously curated dataset, ensuring fair and consistent comparisons. The investigation underscores VGG-16’s superior performance in distinguishing stroke cases, highlighting its potential as a robust tool for accurate diagnosis. Comparative analyses among popular deep learning architectures not only demonstrate our model’s efficacy but also emphasize the importance of selecting the right architecture for medical image classification tasks. These findings contribute to the growing evidence supporting advanced deep learning techniques in medical imaging. Achieving a validation accuracy of 90%, our model holds significant promise for real-world healthcare applications, showcasing the critical role of cutting-edge technologies in advancing diagnostic accuracy and the transformative potential of deep learning in the medical field.
{"title":"Ischemic Stroke Classification Using VGG-16 Convolutional Neural Networks: A Study on Moroccan MRI Scans","authors":"Wafae Abbaoui, Sara Retal, Soumia Ziti, Brahim El Bhiri, Hassan Moussif","doi":"10.3991/ijoe.v20i02.44845","DOIUrl":"https://doi.org/10.3991/ijoe.v20i02.44845","url":null,"abstract":"This study presents a comprehensive exploration of deep learning models for precise brain ischemic stroke classification using medical data from Morocco. Following the OSEMN approach, our methodology leverages transfer learning with the VGG-16 architecture and employs data augmentation techniques to enhance model performance. Our developed model achieved a remarkable validation accuracy of 90%, surpassing alternative state-of-theart models (ResNet50: 87.0%, InceptionV3: 82.0%, VGG-19: 81.0%). Notably, all models were rigorously evaluated on the same meticulously curated dataset, ensuring fair and consistent comparisons. The investigation underscores VGG-16’s superior performance in distinguishing stroke cases, highlighting its potential as a robust tool for accurate diagnosis. Comparative analyses among popular deep learning architectures not only demonstrate our model’s efficacy but also emphasize the importance of selecting the right architecture for medical image classification tasks. These findings contribute to the growing evidence supporting advanced deep learning techniques in medical imaging. Achieving a validation accuracy of 90%, our model holds significant promise for real-world healthcare applications, showcasing the critical role of cutting-edge technologies in advancing diagnostic accuracy and the transformative potential of deep learning in the medical field.","PeriodicalId":507997,"journal":{"name":"International Journal of Online and Biomedical Engineering (iJOE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139838257","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-14DOI: 10.3991/ijoe.v20i02.45377
L. Andrade-Arenas, Cesar Yactayo-Arias, Félix Pucuhuayla-Revatta
In the context of advancing technological development, chatbots have emerged as an innovative tool in the field of mental health, offering new possibilities to provide therapy and emotional support in an accessible and convenient manner. The aim of this study was to develop and evaluate a chatbot implemented in a web application designed to provide emotional support to an adult population, specifically targeting young people and adults over the age of 18. The research focused on user satisfaction with the chatbot experience. Using a qualitative approach and non-random convenience sampling, we collected feedback on the chatbot’s performance from 15 users through an online questionnaire. The results showed a positive assessment, with an average satisfaction score of 4.09 on a scale of 1 to 5. The participants expressed their approval of the emotional support provided by the chatbot, emphasizing the sense of understanding and trust generated by the therapeutic interventions and emotional support. In conclusion, this study successfully assessed user satisfaction with the emotional support chatbot, emphasizing its significance in the realm of digital mental health. The scope of this study was solely focused on user satisfaction. For future research, it is recommended to expand the scope to investigate the correlation between user satisfaction and therapeutic outcomes. Additionally, there is a need to tailor these systems to meet the specific emotional requirements of diverse user groups and enhance the efficacy of mental health patient care.
{"title":"Therapy and Emotional Support through a Chatbot","authors":"L. Andrade-Arenas, Cesar Yactayo-Arias, Félix Pucuhuayla-Revatta","doi":"10.3991/ijoe.v20i02.45377","DOIUrl":"https://doi.org/10.3991/ijoe.v20i02.45377","url":null,"abstract":"In the context of advancing technological development, chatbots have emerged as an innovative tool in the field of mental health, offering new possibilities to provide therapy and emotional support in an accessible and convenient manner. The aim of this study was to develop and evaluate a chatbot implemented in a web application designed to provide emotional support to an adult population, specifically targeting young people and adults over the age of 18. The research focused on user satisfaction with the chatbot experience. Using a qualitative approach and non-random convenience sampling, we collected feedback on the chatbot’s performance from 15 users through an online questionnaire. The results showed a positive assessment, with an average satisfaction score of 4.09 on a scale of 1 to 5. The participants expressed their approval of the emotional support provided by the chatbot, emphasizing the sense of understanding and trust generated by the therapeutic interventions and emotional support. In conclusion, this study successfully assessed user satisfaction with the emotional support chatbot, emphasizing its significance in the realm of digital mental health. The scope of this study was solely focused on user satisfaction. For future research, it is recommended to expand the scope to investigate the correlation between user satisfaction and therapeutic outcomes. Additionally, there is a need to tailor these systems to meet the specific emotional requirements of diverse user groups and enhance the efficacy of mental health patient care.","PeriodicalId":507997,"journal":{"name":"International Journal of Online and Biomedical Engineering (iJOE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139777381","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-14DOI: 10.3991/ijoe.v20i02.45693
A. Samala, Soha Rawas
The adoption of cloud-based electronic health record (EHR) systems and blockchain technology in healthcare is gaining attention for enhancing data security and interoperability. This research focuses on designing and implementing a blockchain-based cloud EHR system. It explores selecting suitable blockchain technology, cloud infrastructure, and data management methods to ensure patient data confidentiality, integrity, and availability. The architecture and components of the system, including the blockchain network, cloud storage layer, and user interface, are thoroughly discussed. A pilot study evaluates the system’s feasibility and performance, showcasing improved data protection, sharing, and management compared to traditional EHR systems. The potential benefits, drawbacks, and barriers to adoption of a blockchain-based cloud EHR system are examined. This research provides valuable insights and recommendations for healthcare institutions considering the implementation of such systems, addressing the challenges, and offering guidance for successful adoption.
{"title":"Transforming Healthcare Data Management: A Blockchain-Based Cloud EHR System for Enhanced Security and Interoperability","authors":"A. Samala, Soha Rawas","doi":"10.3991/ijoe.v20i02.45693","DOIUrl":"https://doi.org/10.3991/ijoe.v20i02.45693","url":null,"abstract":"The adoption of cloud-based electronic health record (EHR) systems and blockchain technology in healthcare is gaining attention for enhancing data security and interoperability. This research focuses on designing and implementing a blockchain-based cloud EHR system. It explores selecting suitable blockchain technology, cloud infrastructure, and data management methods to ensure patient data confidentiality, integrity, and availability. The architecture and components of the system, including the blockchain network, cloud storage layer, and user interface, are thoroughly discussed. A pilot study evaluates the system’s feasibility and performance, showcasing improved data protection, sharing, and management compared to traditional EHR systems. The potential benefits, drawbacks, and barriers to adoption of a blockchain-based cloud EHR system are examined. This research provides valuable insights and recommendations for healthcare institutions considering the implementation of such systems, addressing the challenges, and offering guidance for successful adoption.","PeriodicalId":507997,"journal":{"name":"International Journal of Online and Biomedical Engineering (iJOE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139837252","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-14DOI: 10.3991/ijoe.v20i02.45981
Mohammed Waly, Fahad Alshammari, Maryam E. Alshammari, Mohammed Algahtany
The subjective visual vertical (SVV) is a potential indicator of vestibular dysfunction as it assesses an individual’s perception of a vertical line. Despite this, and as a result of specific logistical impediments, SVV has not entered standard clinical practice. Dizziness is the third most common clinical complaint by patients (20%) in outpatient offices. It adversely affects the patient’s life and is often accompanied by intensive healthcare. This study aims to determine whether the bucket test and mobile phone app are as reliable as the Virtual SVV system in assessing the SVV. This study involves four types of investigation to determine the relationship or difference among three tests, including their performance comparison, descriptive analysis, one-way ANOVA test, receiver operating characteristic (ROC) curve, and correlation analysis. After organizing the raw data from 207 healthy volunteer participants for 8 trials, it was found that 59% were female and 41% were male. The data was analyzed utilizing the SPSS program. The test performance is measured using the ROC curve, and the results indicate that the bucket with the highest ROC coefficient is 0.72.
{"title":"Assessing Subjective Visual Vertical Reliability: A Comparison of the “Bucket Test,” a Mobile App, and a Virtual System","authors":"Mohammed Waly, Fahad Alshammari, Maryam E. Alshammari, Mohammed Algahtany","doi":"10.3991/ijoe.v20i02.45981","DOIUrl":"https://doi.org/10.3991/ijoe.v20i02.45981","url":null,"abstract":"The subjective visual vertical (SVV) is a potential indicator of vestibular dysfunction as it assesses an individual’s perception of a vertical line. Despite this, and as a result of specific logistical impediments, SVV has not entered standard clinical practice. Dizziness is the third most common clinical complaint by patients (20%) in outpatient offices. It adversely affects the patient’s life and is often accompanied by intensive healthcare. This study aims to determine whether the bucket test and mobile phone app are as reliable as the Virtual SVV system in assessing the SVV. This study involves four types of investigation to determine the relationship or difference among three tests, including their performance comparison, descriptive analysis, one-way ANOVA test, receiver operating characteristic (ROC) curve, and correlation analysis. After organizing the raw data from 207 healthy volunteer participants for 8 trials, it was found that 59% were female and 41% were male. The data was analyzed utilizing the SPSS program. The test performance is measured using the ROC curve, and the results indicate that the bucket with the highest ROC coefficient is 0.72.","PeriodicalId":507997,"journal":{"name":"International Journal of Online and Biomedical Engineering (iJOE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139839272","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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