Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a pandemic since early 2020. The coronavirus disease 2019 (COVID-19) has already caused more than three million deaths worldwide and affected people's physical and mental health. COVID-19 patients with mild symptoms are generally required to self-isolate and monitor for symptoms at least for 14 days in the case the disease turns towards severe complications. In this work, we overviewed the impact of COVID-19 on the patients' general health with a focus on their cardiovascular, respiratory and mental health, and investigated several existing patient monitoring systems. We addressed the limitations of these systems and proposed a wearable telehealth solution for monitoring a set of physiological parameters that are critical for COVID-19 patients such as body temperature, heart rate, heart rate variability, blood oxygen saturation, respiratory rate, blood pressure, and cough. This physiological information can be further combined to potentially estimate the lung function using artificial intelligence (AI) and sensor fusion techniques. The prototype, which includes the hardware and a smartphone app, showed promising results with performance comparable to or better than similar commercial devices, thus potentially making the proposed system an ideal wearable solution for long-term monitoring of COVID-19 patients and other chronic diseases.
{"title":"A Wearable Tele-Health System towards Monitoring COVID-19 and Chronic Diseases","authors":"Wei Jiang;Sumit Majumder;Samarth Kumar;Sophini Subramaniam;Xiaohe Li;Ridha Khedri;Tapas Mondal;Mansour Abolghasemian;Imran Satia;M. Jamal Deen","doi":"10.1109/RBME.2021.3069815","DOIUrl":"10.1109/RBME.2021.3069815","url":null,"abstract":"Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a pandemic since early 2020. The coronavirus disease 2019 (COVID-19) has already caused more than three million deaths worldwide and affected people's physical and mental health. COVID-19 patients with mild symptoms are generally required to self-isolate and monitor for symptoms at least for 14 days in the case the disease turns towards severe complications. In this work, we overviewed the impact of COVID-19 on the patients' general health with a focus on their cardiovascular, respiratory and mental health, and investigated several existing patient monitoring systems. We addressed the limitations of these systems and proposed a wearable telehealth solution for monitoring a set of physiological parameters that are critical for COVID-19 patients such as body temperature, heart rate, heart rate variability, blood oxygen saturation, respiratory rate, blood pressure, and cough. This physiological information can be further combined to potentially estimate the lung function using artificial intelligence (AI) and sensor fusion techniques. The prototype, which includes the hardware and a smartphone app, showed promising results with performance comparable to or better than similar commercial devices, thus potentially making the proposed system an ideal wearable solution for long-term monitoring of COVID-19 patients and other chronic diseases.","PeriodicalId":39235,"journal":{"name":"IEEE Reviews in Biomedical Engineering","volume":"15 ","pages":"61-84"},"PeriodicalIF":17.6,"publicationDate":"2021-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/RBME.2021.3069815","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"25532097","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}
Pub Date : 2021-03-26DOI: 10.1109/RBME.2021.3069213
J. Christopher Clement;VijayaKumar Ponnusamy;K.C. Sriharipriya;R. Nandakumar
COVID-19 is a life threatening disease which has a enormous global impact. As the cause of the disease is a novel coronavirus whose gene information is unknown, drugs and vaccines are yet to be found. For the present situation, disease spread analysis and prediction with the help of mathematical and data driven model will be of great help to initiate prevention and control action, namely lockdown and qurantine. There are various mathematical and machine-learning models proposed for analyzing the spread and prediction. Each model has its own limitations and advantages for a particluar scenario. This article reviews the state-of-the art mathematical models for COVID-19, including compartment models, statistical models and machine learning models to provide more insight, so that an appropriate model can be well adopted for the disease spread analysis. Furthermore, accurate diagnose of COVID-19 is another essential process to identify the infected person and control further spreading. As the spreading is fast, there is a need for quick auotomated diagnosis mechanism to handle large population. Deep-learning and machine-learning based diagnostic mechanism will be more appropriate for this purpose. In this aspect, a comprehensive review on the deep learning models for the diagnosis of the disease is also provided in this article.
{"title":"A Survey on Mathematical, Machine Learning and Deep Learning Models for COVID-19 Transmission and Diagnosis","authors":"J. Christopher Clement;VijayaKumar Ponnusamy;K.C. Sriharipriya;R. Nandakumar","doi":"10.1109/RBME.2021.3069213","DOIUrl":"10.1109/RBME.2021.3069213","url":null,"abstract":"COVID-19 is a life threatening disease which has a enormous global impact. As the cause of the disease is a novel coronavirus whose gene information is unknown, drugs and vaccines are yet to be found. For the present situation, disease spread analysis and prediction with the help of mathematical and data driven model will be of great help to initiate prevention and control action, namely lockdown and qurantine. There are various mathematical and machine-learning models proposed for analyzing the spread and prediction. Each model has its own limitations and advantages for a particluar scenario. This article reviews the state-of-the art mathematical models for COVID-19, including compartment models, statistical models and machine learning models to provide more insight, so that an appropriate model can be well adopted for the disease spread analysis. Furthermore, accurate diagnose of COVID-19 is another essential process to identify the infected person and control further spreading. As the spreading is fast, there is a need for quick auotomated diagnosis mechanism to handle large population. Deep-learning and machine-learning based diagnostic mechanism will be more appropriate for this purpose. In this aspect, a comprehensive review on the deep learning models for the diagnosis of the disease is also provided in this article.","PeriodicalId":39235,"journal":{"name":"IEEE Reviews in Biomedical Engineering","volume":"15 ","pages":"325-340"},"PeriodicalIF":17.6,"publicationDate":"2021-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/RBME.2021.3069213","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"25519227","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}
Pub Date : 2021-03-18DOI: 10.1109/RBME.2021.3081180
Jingjing Luo;Zhengrong Yan;Shijie Guo;Wei Chen
Atherosclerosis screening helps the medical model transform from therapeutic medicine to preventive medicine by assessing degree of atherosclerosis prior to the occurrence of fatal vascular events. Pervasive screening emphasizes atherosclerotic monitoring with easy access, quick process, and advanced computing. In this work, we introduced five cutting-edge pervasive technologies including imaging photoplethysmography (iPPG), laser Doppler, radio frequency (RF), thermal imaging (TI), optical fiber sensing and piezoelectric sensor. IPPG measures physiological parameters by using video images that record the subtle skin color changes consistent with cardiac-synchronous blood volume changes in subcutaneous arteries and capillaries. Laser Doppler obtained the information on blood flow by analyzing the spectral components of backscattered light from the illuminated tissues’ surface. RF is based on Doppler shift caused by the periodic movement of the chest wall induced by respiration and heartbeat. TI measures vital signs by detecting electromagnetic radiation emitted by blood flow. The working principle of optical fiber sensor is to detect the change of light properties caused by the interaction between the measured physiological parameter and the entering light. Piezoelectric sensors are based on the piezoelectric effect of dielectrics. All these pervasive technologies are noninvasive, mobile, and can detect physiological parameters related to atherosclerosis screening.
{"title":"Recent Advances in Atherosclerotic Disease Screening Using Pervasive Healthcare","authors":"Jingjing Luo;Zhengrong Yan;Shijie Guo;Wei Chen","doi":"10.1109/RBME.2021.3081180","DOIUrl":"10.1109/RBME.2021.3081180","url":null,"abstract":"Atherosclerosis screening helps the medical model transform from therapeutic medicine to preventive medicine by assessing degree of atherosclerosis prior to the occurrence of fatal vascular events. Pervasive screening emphasizes atherosclerotic monitoring with easy access, quick process, and advanced computing. In this work, we introduced five cutting-edge pervasive technologies including imaging photoplethysmography (iPPG), laser Doppler, radio frequency (RF), thermal imaging (TI), optical fiber sensing and piezoelectric sensor. IPPG measures physiological parameters by using video images that record the subtle skin color changes consistent with cardiac-synchronous blood volume changes in subcutaneous arteries and capillaries. Laser Doppler obtained the information on blood flow by analyzing the spectral components of backscattered light from the illuminated tissues’ surface. RF is based on Doppler shift caused by the periodic movement of the chest wall induced by respiration and heartbeat. TI measures vital signs by detecting electromagnetic radiation emitted by blood flow. The working principle of optical fiber sensor is to detect the change of light properties caused by the interaction between the measured physiological parameter and the entering light. Piezoelectric sensors are based on the piezoelectric effect of dielectrics. All these pervasive technologies are noninvasive, mobile, and can detect physiological parameters related to atherosclerosis screening.","PeriodicalId":39235,"journal":{"name":"IEEE Reviews in Biomedical Engineering","volume":"15 ","pages":"293-308"},"PeriodicalIF":17.6,"publicationDate":"2021-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/RBME.2021.3081180","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38912242","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}
Pub Date : 2021-03-17DOI: 10.1109/RBME.2021.3066072
Vasileios Skaramagkas;Giorgos Giannakakis;Emmanouil Ktistakis;Dimitris Manousos;Ioannis Karatzanis;Nikolaos S. Tachos;Evanthia Tripoliti;Kostas Marias;Dimitrios I. Fotiadis;Manolis Tsiknakis
Eye behaviour provides valuable information revealing one’s higher cognitive functions and state of affect. Although eye tracking is gaining ground in the research community, it is not yet a popular approach for the detection of emotional and cognitive states. In this paper, we present a review of eye and pupil tracking related metrics (such as gaze, fixations, saccades, blinks, pupil size variation, etc.) utilized towards the detection of emotional and cognitive processes, focusing on visual attention, emotional arousal and cognitive workload. Besides, we investigate their involvement as well as the computational recognition methods employed for the reliable emotional and cognitive assessment. The publicly available datasets employed in relevant research efforts were collected and their specifications and other pertinent details are described. The multimodal approaches which combine eye-tracking features with other modalities (e.g. biosignals), along with artificial intelligence and machine learning techniques were also surveyed in terms of their recognition/classification accuracy. The limitations, current open research problems and prospective future research directions were discussed for the usage of eye-tracking as the primary sensor modality. This study aims to comprehensively present the most robust and significant eye/pupil metrics based on available literature towards the development of a robust emotional or cognitive computational model.
{"title":"Review of Eye Tracking Metrics Involved in Emotional and Cognitive Processes","authors":"Vasileios Skaramagkas;Giorgos Giannakakis;Emmanouil Ktistakis;Dimitris Manousos;Ioannis Karatzanis;Nikolaos S. Tachos;Evanthia Tripoliti;Kostas Marias;Dimitrios I. Fotiadis;Manolis Tsiknakis","doi":"10.1109/RBME.2021.3066072","DOIUrl":"10.1109/RBME.2021.3066072","url":null,"abstract":"Eye behaviour provides valuable information revealing one’s higher cognitive functions and state of affect. Although eye tracking is gaining ground in the research community, it is not yet a popular approach for the detection of emotional and cognitive states. In this paper, we present a review of eye and pupil tracking related metrics (such as gaze, fixations, saccades, blinks, pupil size variation, etc.) utilized towards the detection of emotional and cognitive processes, focusing on visual attention, emotional arousal and cognitive workload. Besides, we investigate their involvement as well as the computational recognition methods employed for the reliable emotional and cognitive assessment. The publicly available datasets employed in relevant research efforts were collected and their specifications and other pertinent details are described. The multimodal approaches which combine eye-tracking features with other modalities (e.g. biosignals), along with artificial intelligence and machine learning techniques were also surveyed in terms of their recognition/classification accuracy. The limitations, current open research problems and prospective future research directions were discussed for the usage of eye-tracking as the primary sensor modality. This study aims to comprehensively present the most robust and significant eye/pupil metrics based on available literature towards the development of a robust emotional or cognitive computational model.","PeriodicalId":39235,"journal":{"name":"IEEE Reviews in Biomedical Engineering","volume":"16 ","pages":"260-277"},"PeriodicalIF":17.6,"publicationDate":"2021-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/RBME.2021.3066072","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9359411","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}
Pub Date : 2021-03-13DOI: 10.1109/RBME.2021.3080087
Banafsaj Jaafar;Jeff Neasham;Patrick Degenaar
Modern Active Medical Implantable Devices require communications to transmit information to the outside world or other implantable sub-systems. This can include physiological data, diagnostics, and parameters to optimise the therapeutic protocol. The available options are to use optical, radiofrequency, or ultrasonic communications. However, in all cases, transmission becomes more difficult with deeper transmission through tissue. Challenges include absorption and scattering by tissue, and the need to ensure there are no undesirable heating effects. As such, this paper aims to review research progress in using ultrasound as an alternative for deep tissue communications. We provide an empirical review of the technology and communication protocols that different groups have used, as well as comparing the implications in terms of penetration depth, implant size, and data rate. We conclude that this technique has promise for deeper implants and for intrabody communications between implantable devices (intrabody networks).
{"title":"What Ultrasound Can and Cannot Do in Implantable Medical Device Communications","authors":"Banafsaj Jaafar;Jeff Neasham;Patrick Degenaar","doi":"10.1109/RBME.2021.3080087","DOIUrl":"10.1109/RBME.2021.3080087","url":null,"abstract":"Modern Active Medical Implantable Devices require communications to transmit information to the outside world or other implantable sub-systems. This can include physiological data, diagnostics, and parameters to optimise the therapeutic protocol. The available options are to use optical, radiofrequency, or ultrasonic communications. However, in all cases, transmission becomes more difficult with deeper transmission through tissue. Challenges include absorption and scattering by tissue, and the need to ensure there are no undesirable heating effects. As such, this paper aims to review research progress in using ultrasound as an alternative for deep tissue communications. We provide an empirical review of the technology and communication protocols that different groups have used, as well as comparing the implications in terms of penetration depth, implant size, and data rate. We conclude that this technique has promise for deeper implants and for intrabody communications between implantable devices (intrabody networks).","PeriodicalId":39235,"journal":{"name":"IEEE Reviews in Biomedical Engineering","volume":"16 ","pages":"357-370"},"PeriodicalIF":17.6,"publicationDate":"2021-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/RBME.2021.3080087","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9415917","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}
Pub Date : 2021-03-07DOI: 10.1109/RBME.2021.3078190
Shuo Jiang;Peiqi Kang;Xinyu Song;Benny P.L. Lo;Peter B. Shull
Hands are vital in a wide range of fundamental daily activities, and neurological diseases that impede hand function can significantly affect quality of life. Wearable hand gesture interfaces hold promise to restore and assist hand function and to enhance human-human and human-computer communication. The purpose of this review is to synthesize current novel sensing interfaces and algorithms for hand gesture recognition, and the scope of applications covers rehabilitation, prosthesis control, exoskeletons for augmentation, sign language recognition, human-computer interaction, and user authentication. Results showed that electrical, mechanical, acoustical/vibratory, and optical sensing were the primary input modalities in gesture recognition interfaces. Two categories of algorithms were identified: 1) classification algorithms for predefined, fixed hand poses and 2) regression algorithms for continuous finger and wrist joint angles. Conventional machine learning algorithms, including linear discriminant analysis, support vector machines, random forests, and non-negative matrix factorization, have been widely used for a variety of gesture recognition applications, and deep learning algorithms have more recently been applied to further facilitate the complex relationship between sensor signals and multi-articulated hand postures. Future research should focus on increasing recognition accuracy with larger hand gesture datasets, improving reliability and robustness for daily use outside of the laboratory, and developing softer, less obtrusive interfaces.
{"title":"Emerging Wearable Interfaces and Algorithms for Hand Gesture Recognition: A Survey","authors":"Shuo Jiang;Peiqi Kang;Xinyu Song;Benny P.L. Lo;Peter B. Shull","doi":"10.1109/RBME.2021.3078190","DOIUrl":"10.1109/RBME.2021.3078190","url":null,"abstract":"Hands are vital in a wide range of fundamental daily activities, and neurological diseases that impede hand function can significantly affect quality of life. Wearable hand gesture interfaces hold promise to restore and assist hand function and to enhance human-human and human-computer communication. The purpose of this review is to synthesize current novel sensing interfaces and algorithms for hand gesture recognition, and the scope of applications covers rehabilitation, prosthesis control, exoskeletons for augmentation, sign language recognition, human-computer interaction, and user authentication. Results showed that electrical, mechanical, acoustical/vibratory, and optical sensing were the primary input modalities in gesture recognition interfaces. Two categories of algorithms were identified: 1) classification algorithms for predefined, fixed hand poses and 2) regression algorithms for continuous finger and wrist joint angles. Conventional machine learning algorithms, including linear discriminant analysis, support vector machines, random forests, and non-negative matrix factorization, have been widely used for a variety of gesture recognition applications, and deep learning algorithms have more recently been applied to further facilitate the complex relationship between sensor signals and multi-articulated hand postures. Future research should focus on increasing recognition accuracy with larger hand gesture datasets, improving reliability and robustness for daily use outside of the laboratory, and developing softer, less obtrusive interfaces.","PeriodicalId":39235,"journal":{"name":"IEEE Reviews in Biomedical Engineering","volume":"15 ","pages":"85-102"},"PeriodicalIF":17.6,"publicationDate":"2021-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/RBME.2021.3078190","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38960132","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}
Pub Date : 2021-03-07DOI: 10.1109/RBME.2021.3078001
Alberto Plaza;Mar Hernandez;Gonzalo Puyuelo;Elena Garces;Elena Garcia
Medical and rehabilitation exoskeletons are being increasingly considered by therapists when choosing a treatment for individuals affected by lower limb impairments. Although all such exoskeletons seem to provide similar features and performance, there are, in practice, significant differences among them in terms of maximum walking speed, maximum torque, weight, autonomy, interaction with the user, or even the way to use it. In this review, the state of the art of the main commercial exoskeletons is described, while analyzing their properties, advantages, and disadvantages. Three groups are considered: complete exoskeletons, partial exoskeletons and open lines of research. A comparative analysis between them is performed while considering the main scientific and technical aspects to be improved. In conclusion to this analysis, the balance between feasibility and innovation in exoskeletons development is a design challenge. Commercial exoskeletons must fulfil standards whilst ensuring their safety and robustness. However, achieving a new generation of exoskeletons means a need to implement new hardware paradigms, and to enhance control strategies focused on assist-as-needed scheme. Finally, some aspects to improve current designs of the exoskeleton are presented.
{"title":"Lower-Limb Medical and Rehabilitation Exoskeletons: A Review of the Current Designs","authors":"Alberto Plaza;Mar Hernandez;Gonzalo Puyuelo;Elena Garces;Elena Garcia","doi":"10.1109/RBME.2021.3078001","DOIUrl":"10.1109/RBME.2021.3078001","url":null,"abstract":"Medical and rehabilitation exoskeletons are being increasingly considered by therapists when choosing a treatment for individuals affected by lower limb impairments. Although all such exoskeletons seem to provide similar features and performance, there are, in practice, significant differences among them in terms of maximum walking speed, maximum torque, weight, autonomy, interaction with the user, or even the way to use it. In this review, the state of the art of the main commercial exoskeletons is described, while analyzing their properties, advantages, and disadvantages. Three groups are considered: complete exoskeletons, partial exoskeletons and open lines of research. A comparative analysis between them is performed while considering the main scientific and technical aspects to be improved. In conclusion to this analysis, the balance between feasibility and innovation in exoskeletons development is a design challenge. Commercial exoskeletons must fulfil standards whilst ensuring their safety and robustness. However, achieving a new generation of exoskeletons means a need to implement new hardware paradigms, and to enhance control strategies focused on assist-as-needed scheme. Finally, some aspects to improve current designs of the exoskeleton are presented.","PeriodicalId":39235,"journal":{"name":"IEEE Reviews in Biomedical Engineering","volume":"16 ","pages":"278-291"},"PeriodicalIF":17.6,"publicationDate":"2021-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/RBME.2021.3078001","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9415912","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}
Pub Date : 2021-03-05DOI: 10.1109/RBME.2021.3061839
This index covers all technical items - papers, correspondence, reviews, etc. - that appeared in this periodical during the year, and items from previous years that were commented upon or corrected in this year. Departments and other items may also be covered if they have been judged to have archival value. The Author Index contains the primary entry for each item, listed under the first author's name. The primary entry includes the co-authors' names, the title of the paper or other item, and its location, specified by the publication abbreviation, year, month, and inclusive pagination. The Subject Index contains entries describing the item under all appropriate subject headings, plus the first author's name, the publication abbreviation, month, and year, and inclusive pages. Note that the item title is found only under the primary entry in the Author Index.
{"title":"2021 Index IEEE Reviews in Biomedical Engineering Vol. 14","authors":"","doi":"10.1109/RBME.2021.3061839","DOIUrl":"https://doi.org/10.1109/RBME.2021.3061839","url":null,"abstract":"This index covers all technical items - papers, correspondence, reviews, etc. - that appeared in this periodical during the year, and items from previous years that were commented upon or corrected in this year. Departments and other items may also be covered if they have been judged to have archival value. The Author Index contains the primary entry for each item, listed under the first author's name. The primary entry includes the co-authors' names, the title of the paper or other item, and its location, specified by the publication abbreviation, year, month, and inclusive pagination. The Subject Index contains entries describing the item under all appropriate subject headings, plus the first author's name, the publication abbreviation, month, and year, and inclusive pages. Note that the item title is found only under the primary entry in the Author Index.","PeriodicalId":39235,"journal":{"name":"IEEE Reviews in Biomedical Engineering","volume":"14 ","pages":"357-363"},"PeriodicalIF":17.6,"publicationDate":"2021-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/RBME.2021.3061839","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67755450","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}
Pub Date : 2021-02-08DOI: 10.1109/RBME.2021.3057673
Fredrik Olsson;Kjartan Halvorsen;Anna Cristina Åberg
Objective quantification of the balancing mechanisms in humans is strongly needed in health care of older people, yet is largely missing among current clinical balance assessment methods. Hence, the main goal of this literature review is to identify methods that have the potential to meet that need. We searched in the PubMed and IEEE Xplore databases using predefined criteria, screened 1064 articles, and systematically reviewed and categorized methods from 73 studies that deal with identification of neuromuscular controller models of human upright standing from empirical data. These studies were then analyzed with the particular aim to understand to what degree such methods would be useful solutions for assessing the balance of older individuals aged above 60 years. The 16 studies that included an older subject population were especially examined with this in mind. The majority of the reviewed articles focused on research questions related to the general function of human balance control rather than clinical applicability. Further efforts need to be made to adapt these methods for more accessible and mobile technologies and to ensure that the outcomes are valid for balance assessment of a general older population.
{"title":"Neuromuscular Controller Models for Quantifying Standing Balance in Older People: A Systematic Review","authors":"Fredrik Olsson;Kjartan Halvorsen;Anna Cristina Åberg","doi":"10.1109/RBME.2021.3057673","DOIUrl":"10.1109/RBME.2021.3057673","url":null,"abstract":"Objective quantification of the balancing mechanisms in humans is strongly needed in health care of older people, yet is largely missing among current clinical balance assessment methods. Hence, the main goal of this literature review is to identify methods that have the potential to meet that need. We searched in the PubMed and IEEE Xplore databases using predefined criteria, screened 1064 articles, and systematically reviewed and categorized methods from 73 studies that deal with identification of neuromuscular controller models of human upright standing from empirical data. These studies were then analyzed with the particular aim to understand to what degree such methods would be useful solutions for assessing the balance of older individuals aged above 60 years. The 16 studies that included an older subject population were especially examined with this in mind. The majority of the reviewed articles focused on research questions related to the general function of human balance control rather than clinical applicability. Further efforts need to be made to adapt these methods for more accessible and mobile technologies and to ensure that the outcomes are valid for balance assessment of a general older population.","PeriodicalId":39235,"journal":{"name":"IEEE Reviews in Biomedical Engineering","volume":"16 ","pages":"560-578"},"PeriodicalIF":17.6,"publicationDate":"2021-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/RBME.2021.3057673","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9365575","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}
Pub Date : 2021-02-02DOI: 10.1109/RBME.2021.3056455
Ozgur B. Akan;Hamideh Ramezani;Meltem Civas;Oktay Cetinkaya;Bilgesu A. Bilgin;Naveed A. Abbasi
Among the various key networks in the human body, the nervous system occupies central importance. The debilitating effects of spinal cord injuries (SCI) impact a significant number of people throughout the world, and to date, there is no satisfactory method to treat them. In this paper, we review the major treatment techniques for SCI that include promising solutions based on information and communication technology (ICT) and identify the key characteristics of such systems. We then introduce two novel ICT-based treatment approaches for SCI. The first proposal is based on neural interface systems (NIS) with enhanced feedback, where the external machines are interfaced with the brain and the spinal cord such that the brain signals are directly routed to the limbs for movement. The second proposal relates to the design of self-organizing artificial neurons (ANs) that can be used to replace the injured or dead biological neurons. Apart from SCI treatment, the proposed methods may also be utilized as enabling technologies for neural interface applications by acting as bio-cyber interfaces between the nervous system and machines. Furthermore, under the framework of Internet of Bio-Nano Things (IoBNT), experience gained from SCI treatment techniques can be transferred to nano communication research.
{"title":"Information and Communication Theoretical Understanding and Treatment of Spinal Cord Injuries: State-of-The-Art and Research Challenges","authors":"Ozgur B. Akan;Hamideh Ramezani;Meltem Civas;Oktay Cetinkaya;Bilgesu A. Bilgin;Naveed A. Abbasi","doi":"10.1109/RBME.2021.3056455","DOIUrl":"10.1109/RBME.2021.3056455","url":null,"abstract":"Among the various key networks in the human body, the nervous system occupies central importance. The debilitating effects of spinal cord injuries (SCI) impact a significant number of people throughout the world, and to date, there is no satisfactory method to treat them. In this paper, we review the major treatment techniques for SCI that include promising solutions based on information and communication technology (ICT) and identify the key characteristics of such systems. We then introduce two novel ICT-based treatment approaches for SCI. The first proposal is based on neural interface systems (NIS) with enhanced feedback, where the external machines are interfaced with the brain and the spinal cord such that the brain signals are directly routed to the limbs for movement. The second proposal relates to the design of self-organizing artificial neurons (ANs) that can be used to replace the injured or dead biological neurons. Apart from SCI treatment, the proposed methods may also be utilized as enabling technologies for neural interface applications by acting as bio-cyber interfaces between the nervous system and machines. Furthermore, under the framework of Internet of Bio-Nano Things (IoBNT), experience gained from SCI treatment techniques can be transferred to nano communication research.","PeriodicalId":39235,"journal":{"name":"IEEE Reviews in Biomedical Engineering","volume":"16 ","pages":"332-347"},"PeriodicalIF":17.6,"publicationDate":"2021-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/RBME.2021.3056455","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9358744","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}
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