Pub Date : 2022-10-01DOI: 10.1097/jce.0000000000000553
M. Levin-Epstein
{"title":"March Medical Touts Better Way to Source Medical Device Components","authors":"M. Levin-Epstein","doi":"10.1097/jce.0000000000000553","DOIUrl":"https://doi.org/10.1097/jce.0000000000000553","url":null,"abstract":"","PeriodicalId":77198,"journal":{"name":"Journal of clinical engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45324052","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 : 2022-10-01DOI: 10.1097/JCE.0000000000000548
Rania Elsadig Elmahdi, Samer Elhag, Abubaker Abdalmunim, Abdelslam Abdelrsoul, Z. A. Mustafa, B. A. Ibraheem
Motor imagery (MI) based on electroencephalography (EEG) is one of the methods that the brain-computer interface (BCI) system uses to identify the expected behavior through brain signals. In this study, we aimed to develop an algorithm that is capable of differentiating between 4 MI movements. To achieve this, the Data Set IIa A from BCI competition IV was used to test the algorithm. We used independent component analysis (ICA) to preprocess the signal and wavelet technique to decompose the obtained signal into the desired frequency bands. We then inserted these as common spatial pattern (CSP) input, maximizing the variance between 2 classes using the 1-versus-1 (OVO) technique. Afterward, the support vector machine (SVM) classifier is used to obtain the best possible separation between the 2 classes. The obtained result shows improvement in some significant subjects compared with a previous study of these techniques.
{"title":"Discrimination of Multiclass Motor Imagery-Based Brain-Computer Interface","authors":"Rania Elsadig Elmahdi, Samer Elhag, Abubaker Abdalmunim, Abdelslam Abdelrsoul, Z. A. Mustafa, B. A. Ibraheem","doi":"10.1097/JCE.0000000000000548","DOIUrl":"https://doi.org/10.1097/JCE.0000000000000548","url":null,"abstract":"Motor imagery (MI) based on electroencephalography (EEG) is one of the methods that the brain-computer interface (BCI) system uses to identify the expected behavior through brain signals. In this study, we aimed to develop an algorithm that is capable of differentiating between 4 MI movements. To achieve this, the Data Set IIa A from BCI competition IV was used to test the algorithm. We used independent component analysis (ICA) to preprocess the signal and wavelet technique to decompose the obtained signal into the desired frequency bands. We then inserted these as common spatial pattern (CSP) input, maximizing the variance between 2 classes using the 1-versus-1 (OVO) technique. Afterward, the support vector machine (SVM) classifier is used to obtain the best possible separation between the 2 classes. The obtained result shows improvement in some significant subjects compared with a previous study of these techniques.","PeriodicalId":77198,"journal":{"name":"Journal of clinical engineering","volume":"47 1","pages":"201 - 206"},"PeriodicalIF":0.0,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47229183","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 : 2022-10-01DOI: 10.1097/JCE.0000000000000546
J. Contreras
Large medical centers go through an extensive process for several key service departments to acquire imaging modalities. One such project involved the evaluation, planning, implementation, and go-live of a new mobile magnetic resonance imaging (MRI) for a newly built outpatient clinic. My role in this project was to lead the full procurement and installation process of the mobile MRI. The customer for this project was the radiology service at the new outpatient clinic. The radiology staff hopes to use the new mobile MRI to increase their overall patient caseload over the next several years and provide a much-needed service to a highly populated patient area. This should increase overall patient satisfaction while decreasing community-of-care costs for the hospital. The technology of an MRI is quite complicated, which made the acquisition of one that would meet the needs of the clinical staff that are more imperative for the biomedical engineering department to handle. The overall timeline for this project was about year and a half, and it had been planned extensively while also dealing with a few obstacles along the way. The technology assessment and procurement phases of this project brought new levels of education on the technology and the intense process that the medical center goes through to acquire imaging modalities. The medical center is currently waiting on the final vendor selection to proceed with the implementation of the mobile MRI. In the meantime, leading a separate fixed MRI replacement project at another outpatient facility has prepared me well for the mobile MRI project. Some of the challenges faced during this project included managing a team of different stakeholders, dealing with timeline issues, and understanding the different processes and procedures to accomplish certain tasks. The biggest learning opportunity was leading and managing both the procurement of the modality and its eventual installation. This project looks to improve the patient care and safety of the unique patient population at the new outpatient center.
{"title":"Acquiring and Implementing High-Cost and Complex Imaging Modalities","authors":"J. Contreras","doi":"10.1097/JCE.0000000000000546","DOIUrl":"https://doi.org/10.1097/JCE.0000000000000546","url":null,"abstract":"Large medical centers go through an extensive process for several key service departments to acquire imaging modalities. One such project involved the evaluation, planning, implementation, and go-live of a new mobile magnetic resonance imaging (MRI) for a newly built outpatient clinic. My role in this project was to lead the full procurement and installation process of the mobile MRI. The customer for this project was the radiology service at the new outpatient clinic. The radiology staff hopes to use the new mobile MRI to increase their overall patient caseload over the next several years and provide a much-needed service to a highly populated patient area. This should increase overall patient satisfaction while decreasing community-of-care costs for the hospital. The technology of an MRI is quite complicated, which made the acquisition of one that would meet the needs of the clinical staff that are more imperative for the biomedical engineering department to handle. The overall timeline for this project was about year and a half, and it had been planned extensively while also dealing with a few obstacles along the way. The technology assessment and procurement phases of this project brought new levels of education on the technology and the intense process that the medical center goes through to acquire imaging modalities. The medical center is currently waiting on the final vendor selection to proceed with the implementation of the mobile MRI. In the meantime, leading a separate fixed MRI replacement project at another outpatient facility has prepared me well for the mobile MRI project. Some of the challenges faced during this project included managing a team of different stakeholders, dealing with timeline issues, and understanding the different processes and procedures to accomplish certain tasks. The biggest learning opportunity was leading and managing both the procurement of the modality and its eventual installation. This project looks to improve the patient care and safety of the unique patient population at the new outpatient center.","PeriodicalId":77198,"journal":{"name":"Journal of clinical engineering","volume":"47 1","pages":"195 - 200"},"PeriodicalIF":0.0,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46871028","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 : 2022-10-01DOI: 10.1097/jce.0000000000000552
{"title":"Philips Releases Update on June 2021 Recall","authors":"","doi":"10.1097/jce.0000000000000552","DOIUrl":"https://doi.org/10.1097/jce.0000000000000552","url":null,"abstract":"","PeriodicalId":77198,"journal":{"name":"Journal of clinical engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44521408","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 : 2022-10-01DOI: 10.1097/jce.0000000000000549
M. Abdullah, A. Hamza, H. Barakat, Mohamed O. Khider
{"title":"Computed Tomography Diagnostic Reference Levels for Brain, Chest, and Abdominal/Pelvis Examinations","authors":"M. Abdullah, A. Hamza, H. Barakat, Mohamed O. Khider","doi":"10.1097/jce.0000000000000549","DOIUrl":"https://doi.org/10.1097/jce.0000000000000549","url":null,"abstract":"","PeriodicalId":77198,"journal":{"name":"Journal of clinical engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43218092","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 : 2022-10-01DOI: 10.1097/jce.0000000000000551
{"title":"BMB's New Primer in Its Bonevolent Line of Technology Granted Patent in China","authors":"","doi":"10.1097/jce.0000000000000551","DOIUrl":"https://doi.org/10.1097/jce.0000000000000551","url":null,"abstract":"","PeriodicalId":77198,"journal":{"name":"Journal of clinical engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42246870","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 : 2022-10-01DOI: 10.1097/jce.0000000000000556
O. Keil
{"title":"Where Did Fun Go to Die?","authors":"O. Keil","doi":"10.1097/jce.0000000000000556","DOIUrl":"https://doi.org/10.1097/jce.0000000000000556","url":null,"abstract":"","PeriodicalId":77198,"journal":{"name":"Journal of clinical engineering","volume":"47 1","pages":"175 - 175"},"PeriodicalIF":0.0,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48528234","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 : 2022-10-01DOI: 10.1097/jce.0000000000000543
J. Geller
{"title":"Food and Drug Administration Proposes Several New Medical Device Classifications","authors":"J. Geller","doi":"10.1097/jce.0000000000000543","DOIUrl":"https://doi.org/10.1097/jce.0000000000000543","url":null,"abstract":"","PeriodicalId":77198,"journal":{"name":"Journal of clinical engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43504697","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 : 2022-10-01DOI: 10.1097/JCE.0000000000000554
Avinash Konkani, S. Waheed
Healthcare technology management professionals play a role in assisting hospital leadership teams to make informed decisions related to the purchase, maintenance, and management of medical devices and other healthcare technologies. To do so, they use various resources both internal and external to their organization. One such external source is the US Food and Drug Administration databases. The intent of this article is to provide an overview of US Food and Drug Administration's medical device databases that may be relevant to healthcare technology management professionals and an explanation of how healthcare technology management professionals can leverage this information during their day-to-day operations.
{"title":"Overview of the US Food and Drug Administration's Medical Device Databases and Applications for Healthcare Technology Management Professionals","authors":"Avinash Konkani, S. Waheed","doi":"10.1097/JCE.0000000000000554","DOIUrl":"https://doi.org/10.1097/JCE.0000000000000554","url":null,"abstract":"Healthcare technology management professionals play a role in assisting hospital leadership teams to make informed decisions related to the purchase, maintenance, and management of medical devices and other healthcare technologies. To do so, they use various resources both internal and external to their organization. One such external source is the US Food and Drug Administration databases. The intent of this article is to provide an overview of US Food and Drug Administration's medical device databases that may be relevant to healthcare technology management professionals and an explanation of how healthcare technology management professionals can leverage this information during their day-to-day operations.","PeriodicalId":77198,"journal":{"name":"Journal of clinical engineering","volume":"47 1","pages":"183 - 188"},"PeriodicalIF":0.0,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47483965","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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