Example of IEEE Transactions on Biomedical Engineering format
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Example of IEEE Transactions on Biomedical Engineering format Example of IEEE Transactions on Biomedical Engineering format Example of IEEE Transactions on Biomedical Engineering format Example of IEEE Transactions on Biomedical Engineering format Example of IEEE Transactions on Biomedical Engineering format Example of IEEE Transactions on Biomedical Engineering format Example of IEEE Transactions on Biomedical Engineering format
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Example of IEEE Transactions on Biomedical Engineering format Example of IEEE Transactions on Biomedical Engineering format Example of IEEE Transactions on Biomedical Engineering format Example of IEEE Transactions on Biomedical Engineering format Example of IEEE Transactions on Biomedical Engineering format Example of IEEE Transactions on Biomedical Engineering format Example of IEEE Transactions on Biomedical Engineering format
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open access Open Access ISSN: 189294 e-ISSN: 15582531
recommended Recommended

IEEE Transactions on Biomedical Engineering — Template for authors

Publisher: IEEE
Categories Rank Trend in last 3 yrs
Biomedical Engineering #23 of 229 down down by 1 rank
journal-quality-icon Journal quality:
High
calendar-icon Last 4 years overview: 1253 Published Papers | 11783 Citations
indexed-in-icon Indexed in: Scopus
last-updated-icon Last updated: 16/07/2020
Insights & related journals
General info
Top papers
Popular templates
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FAQ

Journal Performance & Insights

  • Impact Factor
  • CiteRatio
  • SJR
  • SNIP

Impact factor determines the importance of a journal by taking a measure of frequency with which the average article in a journal has been cited in a particular year.

4.424

1% from 2018

Impact factor for IEEE Transactions on Biomedical Engineering from 2016 - 2019
Year Value
2019 4.424
2018 4.491
2017 4.288
2016 3.577
graph view Graph view
table view Table view

insights Insights

  • Impact factor of this journal has decreased by 1% in last year.
  • This journal’s impact factor is in the top 10 percentile category.

CiteRatio is a measure of average citations received per peer-reviewed paper published in the journal.

9.4

3% from 2019

CiteRatio for IEEE Transactions on Biomedical Engineering from 2016 - 2020
Year Value
2020 9.4
2019 9.1
2018 8.8
2017 8.4
2016 7.8
graph view Graph view
table view Table view

insights Insights

  • CiteRatio of this journal has increased by 3% in last years.
  • This journal’s CiteRatio is in the top 10 percentile category.

SCImago Journal Rank (SJR) measures weighted citations received by the journal. Citation weighting depends on the categories and prestige of the citing journal.

1.148

19% from 2019

SJR for IEEE Transactions on Biomedical Engineering from 2016 - 2020
Year Value
2020 1.148
2019 1.41
2018 1.256
2017 1.267
2016 1.141
graph view Graph view
table view Table view

insights Insights

  • SJR of this journal has decreased by 19% in last years.
  • This journal’s SJR is in the top 10 percentile category.

Source Normalized Impact per Paper (SNIP) measures actual citations received relative to citations expected for the journal's category.

2.029

18% from 2019

SNIP for IEEE Transactions on Biomedical Engineering from 2016 - 2020
Year Value
2020 2.029
2019 2.463
2018 2.318
2017 2.135
2016 2.049
graph view Graph view
table view Table view

insights Insights

  • SNIP of this journal has decreased by 18% in last years.
  • This journal’s SNIP is in the top 10 percentile category.

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IEEE Transactions on Biomedical Engineering

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IEEE

IEEE Transactions on Biomedical Engineering

Basic and applied papers dealing with biomedical engineering and applied biophysics. Papers range from practical/clinical applications through experimental science and technological development toformalized mathematical theory.... Read More

Engineering

i
Last updated on
15 Jul 2020
i
ISSN
0018-9294
i
Impact Factor
High - 1.996
i
Open Access
Yes
i
Sherpa RoMEO Archiving Policy
Green faq
i
Plagiarism Check
Available via Turnitin
i
Endnote Style
Download Available
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Bibliography Name
IEEEtran
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Citation Type
Numbered
[25]
i
Bibliography Example
C. W. J. Beenakker, “Specular andreev reflection in graphene,” Phys. Rev. Lett., vol. 97, no. 6, p.

Top papers written in this journal

Journal Article DOI: 10.1109/TBME.1985.325532
A Real-Time QRS Detection Algorithm
Jiapu Pan, Willis J. Tompkins1

Abstract:

We have developed a real-time algorithm for detection of the QRS complexes of ECG signals. It reliably recognizes QRS complexes based upon digital analyses of slope, amplitude, and width. A special digital bandpass filter reduces false detections caused by the various types of interference present in ECG signals. This filteri... We have developed a real-time algorithm for detection of the QRS complexes of ECG signals. It reliably recognizes QRS complexes based upon digital analyses of slope, amplitude, and width. A special digital bandpass filter reduces false detections caused by the various types of interference present in ECG signals. This filtering permits use of low thresholds, thereby increasing detection sensitivity. The algorithm automatically adjusts thresholds and parameters periodically to adapt to such ECG changes as QRS morphology and heart rate. For the standard 24 h MIT/BIH arrhythmia database, this algorithm correctly detects 99.3 percent of the QRS complexes. read more read less

Topics:

QRS complex (52%)52% related to the paper, Beat detection (51%)51% related to the paper
View PDF
5,782 Citations
open accessOpen access Journal Article DOI: 10.1109/TBME.2007.901024
OpenSim: Open-Source Software to Create and Analyze Dynamic Simulations of Movement

Abstract:

Dynamic simulations of movement allow one to study neuromuscular coordination, analyze athletic performance, and estimate internal loading of the musculoskeletal system. Simulations can also be used to identify the sources of pathological movement and establish a scientific basis for treatment planning. We have developed a fr... Dynamic simulations of movement allow one to study neuromuscular coordination, analyze athletic performance, and estimate internal loading of the musculoskeletal system. Simulations can also be used to identify the sources of pathological movement and establish a scientific basis for treatment planning. We have developed a freely available, open-source software system (OpenSim) that lets users develop models of musculoskeletal structures and create dynamic simulations of a wide variety of movements. We are using this system to simulate the dynamics of individuals with pathological gait and to explore the biomechanical effects of treatments. OpenSim provides a platform on which the biomechanics community can build a library of simulations that can be exchanged, tested, analyzed, and improved through a multi-institutional collaboration. Developing software that enables a concerted effort from many investigators poses technical and sociological challenges. Meeting those challenges will accelerate the discovery of principles that govern movement control and improve treatments for individuals with movement pathologies. read more read less

Topics:

Software system (51%)51% related to the paper
View PDF
2,897 Citations
Journal Article DOI: 10.1109/TBME.2004.827072
BCI2000: a general-purpose brain-computer interface (BCI) system
Gerwin Schalk1, Dennis J. McFarland1, Thilo Hinterberger2, Niels Birbaumer2, Jonathan R. Wolpaw1

Abstract:

Many laboratories have begun to develop brain-computer interface (BCI) systems that provide communication and control capabilities to people with severe motor disabilities. Further progress and realization of practical applications depends on systematic evaluations and comparisons of different brain signals, recording methods... Many laboratories have begun to develop brain-computer interface (BCI) systems that provide communication and control capabilities to people with severe motor disabilities. Further progress and realization of practical applications depends on systematic evaluations and comparisons of different brain signals, recording methods, processing algorithms, output formats, and operating protocols. However, the typical BCI system is designed specifically for one particular BCI method and is, therefore, not suited to the systematic studies that are essential for continued progress. In response to this problem, we have developed a documented general-purpose BCI research and development platform called BCI2000. BCI2000 can incorporate alone or in combination any brain signals, signal processing methods, output devices, and operating protocols. This report is intended to describe to investigators, biomedical engineers, and computer scientists the concepts that the BCI2000 system is based upon and gives examples of successful BCI implementations using this system. To date, we have used BCI2000 to create BCI systems for a variety of brain signals, processing methods, and applications. The data show that these systems function well in online operation and that BCI2000 satisfies the stringent real-time requirements of BCI systems. By substantially reducing labor and cost, BCI2000 facilitates the implementation of different BCI systems and other psychophysiological experiments. It is available with full documentation and free of charge for research or educational purposes and is currently being used in a variety of studies by many research groups. read more read less

Topics:

Interface (computing) (51%)51% related to the paper, Output device (50%)50% related to the paper
View PDF
2,200 Citations
Journal Article DOI: 10.1109/10.623056
Localization of brain electrical activity via linearly constrained minimum variance spatial filtering
B.D. Van Veen1, W. van Drongelen, M. Yuchtman, A. Suzuki

Abstract:

A spatial filtering method for localizing sources of brain electrical activity from surface recordings is described and analyzed. The spatial filters are implemented as a weighted sum of the data recorded at different sites. The weights are chosen to minimize the filter output power subject to a linear constraint. The linear ... A spatial filtering method for localizing sources of brain electrical activity from surface recordings is described and analyzed. The spatial filters are implemented as a weighted sum of the data recorded at different sites. The weights are chosen to minimize the filter output power subject to a linear constraint. The linear constraint forces the filter to pass brain electrical activity from a specified location, while the power minimization attenuates activity originating at other locations. The estimated output power as a function of location is normalized by the estimated noise power as a function of location to obtain a neural activity index map. Locations of source activity correspond to maxima in the neural activity index map. The method does not require any prior assumptions about the number of active sources of their geometry because it exploits the spatial covariance of the source electrical activity. This paper presents a development and analysis of the method and explores its sensitivity to deviations between actual and assumed data models. The effect on the algorithm of covariance matrix estimation, correlation between sources, and choice of reference is discussed. Simulated and measured data is used to illustrate the efficacy of the approach. read more read less

Topics:

Covariance function (56%)56% related to the paper, Covariance matrix (54%)54% related to the paper, Spatial filter (54%)54% related to the paper, Filter (signal processing) (53%)53% related to the paper, Noise power (51%)51% related to the paper
1,999 Citations
Journal Article DOI: 10.1109/10.102791
An interactive graphics-based model of the lower extremity to study orthopaedic surgical procedures

Abstract:

A model is developed of the human lower extremity to study how changes in musculoskeletal geometry and musculotendon parameters affect muscle force and its moment about the joints. The lines of action of 43 musculotendon actuators were defined based on their anatomical relationships to three-dimensional bone surface represent... A model is developed of the human lower extremity to study how changes in musculoskeletal geometry and musculotendon parameters affect muscle force and its moment about the joints. The lines of action of 43 musculotendon actuators were defined based on their anatomical relationships to three-dimensional bone surface representations. A model for each actuator was formulated to compute its isometric force-length relation. The kinematics of the lower extremity were defined by modeling the hip, knee, ankle, subtalar, and metatarsophalangeal joints. Thus, the force and joint moment that each musculotendon actuator develops can be computed for any body position. The joint moments calculated with the model compare well with experimentally measured isometric joint moments. A graphical interface to the model has also been developed. It allows the user to visualize the musculoskeletal geometry and to manipulate the model parameters to study the biomechanical consequences of orthopaedic surgical procedures. For example, tendon transfer and lengthening procedures can be simulated by adjusting the model parameters according to various surgical techniques. Results of the simulated surgeries can be analyzed quickly in terms of postsurgery muscle forces and other biomechanical variables. > read more read less

Topics:

Body movement (52%)52% related to the paper
1,720 Citations
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IEEE Transactions on Biomedical Engineering format uses IEEEtran citation style.

Automatically format and order your citations and bibliography in a click.

SciSpace allows imports from all reference managers like Mendeley, Zotero, Endnote, Google Scholar etc.

Frequently asked questions

Absolutely not! With our tool, you can freely write without having to focus on LaTeX. You can write your entire paper as per the IEEE Transactions on Biomedical Engineering guidelines and autoformat it.

Yes. The template is fully compliant as per the guidelines of this journal. Our experts at SciSpace ensure that. Also, if there's any update in the journal format guidelines, we take care of it and include that in our algorithm.

Sure. We support all the top citation styles like APA style, MLA style, Vancouver style, Harvard style, Chicago style, etc. For example, in case of this journal, when you write your paper and hit autoformat, it will automatically update your article as per the IEEE Transactions on Biomedical Engineering citation style.

You can avail our Free Trial for 7 days. I'm sure you'll find our features very helpful. Plus, it's quite inexpensive.

Yup. You can choose the right template, copy-paste the contents from the word doc and click on auto-format. You'll have a publish-ready paper that you can download at the end.

A matter of seconds. Besides that, our intuitive editor saves a load of your time in writing and formating your manuscript.

One little Google search can get you the Word template for any journal. However, why do you need a Word template when you can write your entire manuscript on SciSpace, autoformat it as per IEEE Transactions on Biomedical Engineering's guidelines and download the same in Word, PDF and LaTeX formats? Try us out!.

Absolutely! You can do it using our intuitive editor. It's very easy. If you need help, you can always contact our support team.

SciSpace is an online tool for now. We'll soon release a desktop version. You can also request (or upvote) any feature that you think might be helpful for you and the research community in the feature request section once you sign-up with us.

Sure. You can request any template and we'll have it up and running within a matter of 3 working days. You can find the request box in the Journal Gallery on the right sidebar under the heading, "Couldn't find the format you were looking for?".

After you have written and autoformatted your paper, you can download it in multiple formats, viz., PDF, Docx and LaTeX.

To be honest, the answer is NO. The impact factor is one of the many elements that determine the quality of a journal. Few of those factors the review board, rejection rates, frequency of inclusion in indexes, Eigenfactor, etc. You must assess all the factors and then take the final call.

SHERPA/RoMEO Database

We have extracted this data from Sherpa Romeo to help our researchers understand the access level of this journal. The following table indicates the level of access a journal has as per Sherpa Romeo Archiving Policy.

RoMEO Colour Archiving policy
Green Can archive pre-print and post-print or publisher's version/PDF
Blue Can archive post-print (ie final draft post-refereeing) or publisher's version/PDF
Yellow Can archive pre-print (ie pre-refereeing)
White Archiving not formally supported
FYI:
  1. Pre-prints as being the version of the paper before peer review and
  2. Post-prints as being the version of the paper after peer-review, with revisions having been made.

The 5 most common citation types in order of usage are:.

S. No. Citation Style Type
1. Author Year
2. Numbered
3. Numbered (Superscripted)
4. Author Year (Cited Pages)
5. Footnote

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After uploading your paper on SciSpace, you would see a button to request a journal submission service for IEEE Transactions on Biomedical Engineering.

Each submission service is completed within 4 - 5 working days.

Yes. SciSpace provides this functionality.

After signing up, you would need to import your existing references from Word or .bib file.

SciSpace would allow download of your references in IEEE Transactions on Biomedical Engineering Endnote style, according to ieee guidelines.

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