Huiqi Y. Lu;Xiaorong Ding;Jane E. Hirst;Yang Yang;Jenny Yang;Lucy Mackillop;David A. Clifton
{"title":"Digital Health and Machine Learning Technologies for Blood Glucose Monitoring and Management of Gestational Diabetes","authors":"Huiqi Y. Lu;Xiaorong Ding;Jane E. Hirst;Yang Yang;Jenny Yang;Lucy Mackillop;David A. Clifton","doi":"10.1109/RBME.2023.3242261","DOIUrl":"10.1109/RBME.2023.3242261","url":null,"abstract":"Innovations in digital health and machine learning are changing the path of clinical health and care. People from different geographical locations and cultural backgrounds can benefit from the mobility of wearable devices and smartphones to monitor their health ubiquitously. This paper focuses on reviewing the digital health and machine learning technologies used in gestational diabetes – a subtype of diabetes that occurs during pregnancy. This paper reviews sensor technologies used in blood glucose monitoring devices, digital health innovations and machine learning models for gestational diabetes monitoring and management, in clinical and commercial settings, and discusses future directions. Despite one in six mothers having gestational diabetes, digital health applications were underdeveloped, especially the techniques that can be deployed in clinical practice. There is an urgent need to (1) develop clinically interpretable machine learning methods for patients with gestational diabetes, assisting health professionals with treatment, monitoring, and risk stratification before, during and after their pregnancies; (2) adapt and develop clinically-proven devices for patient self-management of health and well-being at home settings (“virtual ward” and virtual consultation), thereby improving clinical outcomes by facilitating timely intervention; and (3) ensure innovations are affordable and sustainable for all women with different socioeconomic backgrounds and clinical resources.","PeriodicalId":39235,"journal":{"name":"IEEE Reviews in Biomedical Engineering","volume":"17 ","pages":"98-117"},"PeriodicalIF":17.6,"publicationDate":"2023-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10492955","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"IEEE Engineering in Medicine and Biology Society Information","authors":"","doi":"10.1109/RBME.2022.3228083","DOIUrl":"https://doi.org/10.1109/RBME.2022.3228083","url":null,"abstract":"Presents a listing of the editorial board, board of governors, current staff, committee members, and/or society editors for this issue of the publication.","PeriodicalId":39235,"journal":{"name":"IEEE Reviews in Biomedical Engineering","volume":"16 ","pages":"C2-C2"},"PeriodicalIF":17.6,"publicationDate":"2023-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/4664312/10007429/10007531.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67744159","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"IEEE Reviews in Biomedical Engineering (R-BME) Information","authors":"","doi":"10.1109/RBME.2022.3228079","DOIUrl":"https://doi.org/10.1109/RBME.2022.3228079","url":null,"abstract":"These instructions give guidelines for preparing papers for this publication. Presents information for authors publishing in this journal.","PeriodicalId":39235,"journal":{"name":"IEEE Reviews in Biomedical Engineering","volume":"16 ","pages":"C3-C3"},"PeriodicalIF":17.6,"publicationDate":"2023-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/4664312/10007429/10007529.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67744158","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Chang-Hoon Choi;Jörg Felder;Christoph Lerche;N. Jon Shah
{"title":"MRI Coil Development Strategies for Hybrid MR-PET Systems: A Review","authors":"Chang-Hoon Choi;Jörg Felder;Christoph Lerche;N. Jon Shah","doi":"10.1109/RBME.2022.3227337","DOIUrl":"10.1109/RBME.2022.3227337","url":null,"abstract":"Simultaneously operating MR-PET systems have the potential to provide synergetic multi-parametric information, and, as such, interest surrounding their use and development is increasing. However, despite the potential advantages offered by fully combined MR-PET systems, implementing this hybrid integration is technically laborious, and any factors degrading the quality of either modality must be circumvented to ensure optimal performance. In order to attain the best possible quality from both systems, most full MR-PET integrations tend to place the shielded PET system inside the MRI system, close to the target volume of the subject. The radiofrequency (RF) coil used in MRI systems is a key factor in determining the quality of the MR images, and, in simultaneous acquisition, it is generally positioned inside the PET system and PET imaging region, potentially resulting in attenuation and artefacts in the PET images. Therefore, when designing hybrid MR-PET systems, it is imperative that consideration be given to the RF coils inside the PET system. In this review, we present current state-of-the-art RF coil designs used for hybrid MR-PET experiments and discuss various design strategies for constructing PET transparent RF coils.","PeriodicalId":39235,"journal":{"name":"IEEE Reviews in Biomedical Engineering","volume":"17 ","pages":"342-350"},"PeriodicalIF":17.6,"publicationDate":"2022-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9247689","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Editorial A Message From the New Editor-in-Chief","authors":"Bin He","doi":"10.1109/RBME.2022.3221366","DOIUrl":"10.1109/RBME.2022.3221366","url":null,"abstract":"Presents the introductory editorial for this issue of the publication.","PeriodicalId":39235,"journal":{"name":"IEEE Reviews in Biomedical Engineering","volume":"16 ","pages":"4-4"},"PeriodicalIF":17.6,"publicationDate":"2022-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/4664312/10007429/09944964.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9244831","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Spectral Analysis of Heart Rate Variability in Time-Varying Conditions and in the Presence of Confounding Factors","authors":"Leif Sörnmo;Raquel Bailón;Pablo Laguna","doi":"10.1109/RBME.2022.3220636","DOIUrl":"10.1109/RBME.2022.3220636","url":null,"abstract":"The tools for spectrally analyzing heart rate variability (HRV) has in recent years grown considerably, with emphasis on the handling of time-varying conditions and confounding factors. Time–frequency analysis holds since long an important position in HRV analysis, however, this technique cannot alone handle a mean heart rate or a respiratory frequency which vary over time. Overlapping frequency bands represents another critical condition which needs to be dealt with to produce accurate spectral measurements. The present survey offers a comprehensive account of techniques designed to handle such conditions and factors by providing a brief description of the main principles of the different methods. Several methods derive from a mathematical/statistical model, suggesting that the model can be used to simulate data used for performance evaluation. The inclusion of a respiratory signal, whether measured or derived, is another feature of many recent methods, e.g., used to guide the decomposition of the HRV signal so that signals related as well as unrelated to respiration can be analyzed. It is concluded that the development of new approaches to handling time-varying scenarios are warranted, as is benchmarking of performance evaluated in technical as well as in physiological/clinical terms.","PeriodicalId":39235,"journal":{"name":"IEEE Reviews in Biomedical Engineering","volume":"17 ","pages":"322-341"},"PeriodicalIF":17.6,"publicationDate":"2022-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40451706","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A Review in On-Body Compression Using Soft Actuators and Sensors: Applications, Mechanisms, and Challenges","authors":"Alireza Golgouneh;Lucy E. Dunne","doi":"10.1109/RBME.2022.3220505","DOIUrl":"10.1109/RBME.2022.3220505","url":null,"abstract":"Body compression through a garment or inflatable pneumatic mechanism has various applications in aesthetic, athletic, robotics, haptics, astronautics, and especially medical fields for treatment of various disorders such as varicose veins, lymphedema, deep vein thrombosis, and orthostatic intolerance. Traditionally, compression has been done through under-sized (e.g. elastic) or size-adjustable (e.g. inflatable) compression garments. Such systems are designed to apply substantially uniform pressure on the body. However, due to reasons such as anatomical variations and body posture change, different levels of compression may be applied to the body. Further, a high level of discomfort and non-compliance is reported among patients due to donning difficulties. Therefore, there have been some efforts to make compression garments smart by employing advanced functional soft materials and actuators (such as Shape Memory Alloy (SMA), Shape Memory Polymer (SMP), Electroactive polymer (EAP), etc.) as well as soft force-pressure sensors so that the compression level could be controlled and regulated for each person or specific tasks. However, despite these advances, there are still challenges to accurately controlling the on-body compression level that are mainly due to the inherent characteristics of the soft actuators or sensors and the sophisticated human body conditions. In this paper, we will first investigate the soft actuators and sensors that have the potential to be used for on-body compression applications. Then, integrated soft sensing-actuation systems for interfacial compression purposes are studied. Finally, the challenges that might be associated with this work are introduced.","PeriodicalId":39235,"journal":{"name":"IEEE Reviews in Biomedical Engineering","volume":"17 ","pages":"166-179"},"PeriodicalIF":17.6,"publicationDate":"2022-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40451707","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Emerging Technologies Used in Health Management and Efficiency Improvement During Different Contact Tracing Phases Against COVID-19 Pandemic","authors":"Maggie Ezzat Gaber Gendy;Mehmet Rasit Yuce","doi":"10.1109/RBME.2022.3219433","DOIUrl":"10.1109/RBME.2022.3219433","url":null,"abstract":"Confronted with the COVID-19 health crisis, the year 2020 represented a turning point for the entire world. It paved the way for health-care systems to reaffirm their foundations by using different technologies such as sensors, wearables, mobile applications, drones, robots, Artificial Intelligence (AI), Machine Learning (ML) and the Internet of Things (IoT). A lot of domains have been renovated such as diagnosis, treatment, and monitoring, as well as previously unprecedented domains such as contact tracing. Contact tracing, in conjunction with the emergence, spread, and public compliance for vaccines, was a critical step for controlling and limiting the spread of the pandemic. Traditional contact tracing is usually dependent on individuals ability to recall their interactions, which is challenging and yet not effective. Consequently, further development and usage of automated, privacy-preserving, digital contact-tracing was required. As the pandemic is coming to an end, it is vital to collect and learn the effective used technologies that aided in fighting the virus in order to be prepared for any future pandemics and to be aware of any literature gaps that must be filled. This paper surveys state-of-the-art architectures, platforms, and applications combating COVID-19 at each phase of the five basic contact tracing phases, including case identification, contacts identification and rapid exposure notification, surveillance, regular follow up and prevention. In addition, there is a phase of preparation and post-pandemic services for current and needed future technology that will aid in the fight against any incoming infectious diseases.","PeriodicalId":39235,"journal":{"name":"IEEE Reviews in Biomedical Engineering","volume":"16 ","pages":"38-52"},"PeriodicalIF":17.6,"publicationDate":"2022-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9359277","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
David Choy Buentello;Mariana García-Corral;Grissel Trujillo-de Santiago;Mario Moisés Alvarez
{"title":"Neuron(s)-on-a-Chip: A Review of the Design and Use of Microfluidic Systems for Neural Tissue Culture","authors":"David Choy Buentello;Mariana García-Corral;Grissel Trujillo-de Santiago;Mario Moisés Alvarez","doi":"10.1109/RBME.2022.3217486","DOIUrl":"10.1109/RBME.2022.3217486","url":null,"abstract":"Neuron-on-chip (NoC) systems—microfluidic devices in which neurons are cultured—have become a promising alternative to replace or minimize the use of animal models and have greatly facilitated in vitro research. Here, we review and discuss current developments in neuron-on-chip platforms, with a particular emphasis on existing biological models, culturing techniques, biomaterials, and topologies. We also discuss how the architecture, flow, and gradients affect neuronal growth, differentiation, and development. Finally, we discuss some of the most recent applications of NoCs in fundamental research (i.e., studies on the effects of electrical, mechanical/topological, or chemical stimuli) and in disease modeling.","PeriodicalId":39235,"journal":{"name":"IEEE Reviews in Biomedical Engineering","volume":"17 ","pages":"243-263"},"PeriodicalIF":17.6,"publicationDate":"2022-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9255690","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Monica Isgut;Logan Gloster;Katherine Choi;Janani Venugopalan;May D. Wang
{"title":"Systematic Review of Advanced AI Methods for Improving Healthcare Data Quality in Post COVID-19 Era","authors":"Monica Isgut;Logan Gloster;Katherine Choi;Janani Venugopalan;May D. Wang","doi":"10.1109/RBME.2022.3216531","DOIUrl":"10.1109/RBME.2022.3216531","url":null,"abstract":"At the beginning of the COVID-19 pandemic, there was significant hype about the potential impact of artificial intelligence (AI) tools in combatting COVID-19 on diagnosis, prognosis, or surveillance. However, AI tools have not yet been widely successful. One of the key reason is the COVID-19 pandemic has demanded faster real-time development of AI-driven clinical and health support tools, including rapid data collection, algorithm development, validation, and deployment. However, there was not enough time for proper data quality control. Learning from the hard lessons in COVID-19, we summarize the important health data quality challenges during COVID-19 pandemic such as lack of data standardization, missing data, tabulation errors, and noise and artifact. Then we conduct a systematic investigation of computational methods that address these issues, including emerging novel advanced AI data quality control methods that achieve better data quality outcomes and, in some cases, simplify or automate the data cleaning process. We hope this article can assist healthcare community to improve health data quality going forward with novel AI development.","PeriodicalId":39235,"journal":{"name":"IEEE Reviews in Biomedical Engineering","volume":"16 ","pages":"53-69"},"PeriodicalIF":17.6,"publicationDate":"2022-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/4664312/10007429/09926151.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9728920","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}