Example of Physiological Measurement format
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Example of Physiological Measurement format Example of Physiological Measurement format Example of Physiological Measurement format Example of Physiological Measurement format Example of Physiological Measurement format Example of Physiological Measurement format Example of Physiological Measurement format Example of Physiological Measurement format Example of Physiological Measurement format Example of Physiological Measurement format Example of Physiological Measurement format Example of Physiological Measurement format Example of Physiological Measurement format Example of Physiological Measurement format Example of Physiological Measurement format Example of Physiological Measurement format
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Example of Physiological Measurement format Example of Physiological Measurement format Example of Physiological Measurement format Example of Physiological Measurement format Example of Physiological Measurement format Example of Physiological Measurement format Example of Physiological Measurement format Example of Physiological Measurement format Example of Physiological Measurement format Example of Physiological Measurement format Example of Physiological Measurement format Example of Physiological Measurement format Example of Physiological Measurement format Example of Physiological Measurement format Example of Physiological Measurement format Example of Physiological Measurement format
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open access Open Access

Physiological Measurement — Template for authors

Publisher: IOP Publishing
Categories Rank Trend in last 3 yrs
Biophysics #35 of 131 -
Biomedical Engineering #81 of 229 down down by 21 ranks
Physiology (medical) #35 of 98 up up by 5 ranks
Physiology #68 of 169 up up by 9 ranks
journal-quality-icon Journal quality:
Good
calendar-icon Last 4 years overview: 738 Published Papers | 3666 Citations
indexed-in-icon Indexed in: Scopus
last-updated-icon Last updated: 22/06/2020
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Related Journals

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Quality:  
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CiteRatio: 7.3
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Springer

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CiteRatio: 17.2
SJR: 1.596
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Journal Performance & Insights

Impact Factor

CiteRatio

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.

A measure of average citations received per peer-reviewed paper published in the journal.

2.309

3% from 2018

Impact factor for Physiological Measurement from 2016 - 2019
Year Value
2019 2.309
2018 2.246
2017 2.006
2016 2.058
graph view Graph view
table view Table view

5.0

11% from 2019

CiteRatio for Physiological Measurement from 2016 - 2020
Year Value
2020 5.0
2019 4.5
2018 3.9
2017 4.3
2016 3.8
graph view Graph view
table view Table view

insights Insights

  • Impact factor of this journal has increased by 3% in last year.
  • This journal’s impact factor is in the top 10 percentile category.

insights Insights

  • CiteRatio of this journal has increased by 11% in last years.
  • This journal’s CiteRatio is in the top 10 percentile category.

SCImago Journal Rank (SJR)

Source Normalized Impact per Paper (SNIP)

Measures weighted citations received by the journal. Citation weighting depends on the categories and prestige of the citing journal.

Measures actual citations received relative to citations expected for the journal's category.

0.674

4% from 2019

SJR for Physiological Measurement from 2016 - 2020
Year Value
2020 0.674
2019 0.702
2018 0.609
2017 0.731
2016 0.689
graph view Graph view
table view Table view

1.216

3% from 2019

SNIP for Physiological Measurement from 2016 - 2020
Year Value
2020 1.216
2019 1.253
2018 1.279
2017 1.236
2016 1.069
graph view Graph view
table view Table view

insights Insights

  • SJR of this journal has decreased by 4% in last years.
  • This journal’s SJR is in the top 10 percentile category.

insights Insights

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

Physiological Measurement

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IOP Publishing

Physiological Measurement

Approved by publishing and review experts on SciSpace, this template is built as per for Physiological Measurement formatting guidelines as mentioned in IOP Publishing author instructions. The current version was created on 22 Jun 2020 and has been used by 517 authors to write and format their manuscripts to this journal.

Engineering

i
Last updated on
22 Jun 2020
i
ISSN
0967-3334
i
Impact Factor
High - 1.507
i
Acceptance Rate
Not provided
i
Frequency
Not provided
i
Open Access
No
i
Sherpa RoMEO Archiving Policy
Green faq
i
Plagiarism Check
Available via Turnitin
i
Endnote Style
Download Available
i
Bibliography Name
iopart-num
i
Citation Type
Numbered
[25]
i
Bibliography Example
Beenakker C W J 2006 Phys. Rev. Lett. 97 067007 URL 10.1103/PhysRevLett.97.067007

Top papers written in this journal

Journal Article DOI: 10.1088/0967-3334/28/3/R01
Photoplethysmography and its application in clinical physiological measurement.
John F. Allen1

Abstract:

Photoplethysmography (PPG) is a simple and low-cost optical technique that can be used to detect blood volume changes in the microvascular bed of tissue. It is often used non-invasively to make measurements at the skin surface. The PPG waveform comprises a pulsatile ('AC') physiological waveform attributed to cardiac synchron... Photoplethysmography (PPG) is a simple and low-cost optical technique that can be used to detect blood volume changes in the microvascular bed of tissue. It is often used non-invasively to make measurements at the skin surface. The PPG waveform comprises a pulsatile ('AC') physiological waveform attributed to cardiac synchronous changes in the blood volume with each heart beat, and is superimposed on a slowly varying ('DC') baseline with various lower frequency components attributed to respiration, sympathetic nervous system activity and thermoregulation. Although the origins of the components of the PPG signal are not fully understood, it is generally accepted that they can provide valuable information about the cardiovascular system. There has been a resurgence of interest in the technique in recent years, driven by the demand for low cost, simple and portable technology for the primary care and community based clinical settings, the wide availability of low cost and small semiconductor components, and the advancement of computer-based pulse wave analysis techniques. The PPG technology has been used in a wide range of commercially available medical devices for measuring oxygen saturation, blood pressure and cardiac output, assessing autonomic function and also detecting peripheral vascular disease. The introductory sections of the topical review describe the basic principle of operation and interaction of light with tissue, early and recent history of PPG, instrumentation, measurement protocol, and pulse wave analysis. The review then focuses on the applications of PPG in clinical physiological measurements, including clinical physiological monitoring, vascular assessment and autonomic function. read more read less

Topics:

Photoplethysmogram (54%)54% related to the paper
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2,836 Citations
Journal Article DOI: 10.1088/0967-3334/25/4/010
Nonlinear model predictive control of glucose concentration in subjects with type 1 diabetes

Abstract:

A nonlinear model predictive controller has been developed to maintain normoglycemia in subjects with type 1 diabetes during fasting conditions such as during overnight fast. The controller employs a compartment model, which represents the glucoregulatory system and includes submodels representing absorption of subcutaneously... A nonlinear model predictive controller has been developed to maintain normoglycemia in subjects with type 1 diabetes during fasting conditions such as during overnight fast. The controller employs a compartment model, which represents the glucoregulatory system and includes submodels representing absorption of subcutaneously administered short-acting insulin Lispro and gut absorption. The controller uses Bayesian parameter estimation to determine time-varying model parameters. Moving target trajectory facilitates slow, controlled normalization of elevated glucose levels and faster normalization of low glucose values. The predictive capabilities of the model have been evaluated using data from 15 clinical experiments in subjects with type 1 diabetes. The experiments employed intravenous glucose sampling (every 15 min) and subcutaneous infusion of insulin Lispro by insulin pump (modified also every 15 min). The model gave glucose predictions with a mean square error proportionally related to the prediction horizon with the value of 0.2 mmol L(-1) per 15 min. The assessment of clinical utility of model-based glucose predictions using Clarke error grid analysis gave 95% of values in zone A and the remaining 5% of values in zone B for glucose predictions up to 60 min (n = 1674). In conclusion, adaptive nonlinear model predictive control is promising for the control of glucose concentration during fasting conditions in subjects with type 1 diabetes. read more read less

Topics:

Insulin lispro (54%)54% related to the paper, Insulin pump (52%)52% related to the paper, Artificial pancreas (51%)51% related to the paper
View PDF
1,164 Citations
Journal Article DOI: 10.1088/0967-3334/26/5/R01
Wavelet transforms and the ECG: a review.

Abstract:

The wavelet transform has emerged over recent years as a powerful time-frequency analysis and signal coding tool favoured for the interrogation of complex nonstationary signals. Its application to biosignal processing has been at the forefront of these developments where it has been found particularly useful in the study of t... The wavelet transform has emerged over recent years as a powerful time-frequency analysis and signal coding tool favoured for the interrogation of complex nonstationary signals. Its application to biosignal processing has been at the forefront of these developments where it has been found particularly useful in the study of these, often problematic, signals: none more so than the ECG. In this review, the emerging role of the wavelet transform in the interrogation of the ECG is discussed in detail, where both the continuous and the discrete transform are considered in turn. read more read less

Topics:

Wavelet (63%)63% related to the paper, Discrete wavelet transform (63%)63% related to the paper, Wavelet packet decomposition (62%)62% related to the paper, Second-generation wavelet transform (62%)62% related to the paper, Wavelet transform (61%)61% related to the paper
View PDF
794 Citations
Journal Article DOI: 10.1088/0967-3334/33/3/R33
Infrared thermal imaging in medicine
E. F. J. Ring1, Kurt Ammer1

Abstract:

This review describes the features of modern infrared imaging technology and the standardization protocols for thermal imaging in medicine. The technique essentially uses naturally emitted infrared radiation from the skin surface. Recent studies have investigated the influence of equipment and the methods of image recording. ... This review describes the features of modern infrared imaging technology and the standardization protocols for thermal imaging in medicine. The technique essentially uses naturally emitted infrared radiation from the skin surface. Recent studies have investigated the influence of equipment and the methods of image recording. The credibility and acceptance of thermal imaging in medicine is subject to critical use of the technology and proper understanding of thermal physiology. Finally, we review established and evolving medical applications for thermal imaging, including inflammatory diseases, complex regional pain syndrome and Raynaud's phenomenon. Recent interest in the potential applications for fever screening is described, and some other areas of medicine where some research papers have included thermal imaging as an assessment modality. In certain applications thermal imaging is shown to provide objective measurement of temperature changes that are clinically significant. read more read less

Topics:

Imaging technology (57%)57% related to the paper, Medical imaging (55%)55% related to the paper, Thermography (51%)51% related to the paper
View PDF
740 Citations
Journal Article DOI: 10.1088/0967-3334/25/2/R01
Accelerometry: providing an integrated, practical method for long-term, ambulatory monitoring of human movement.
M. Mathie1, Adelle C.F. Coster1, Nigel H. Lovell1, Branko G. Celler1

Abstract:

Accelerometry offers a practical and low cost method of objectively monitoring human movements, and has particular applicability to the monitoring of free-living subjects. Accelerometers have been used to monitor a range of different movements, including gait, sit-to-stand transfers, postural sway and falls. They have also be... Accelerometry offers a practical and low cost method of objectively monitoring human movements, and has particular applicability to the monitoring of free-living subjects. Accelerometers have been used to monitor a range of different movements, including gait, sit-to-stand transfers, postural sway and falls. They have also been used to measure physical activity levels and to identify and classify movements performed by subjects. This paper reviews the use of accelerometer-based systems in each of these areas. The scope and applicability of such systems in unsupervised monitoring of human movement are considered. The different systems and monitoring techniques can be integrated to provide a more comprehensive system that is suitable for measuring a range of different parameters in an unsupervised monitoring context with free-living subjects. An integrated approach is described in which a single, waist-mounted accelerometry system is used to monitor a range of different parameters of human movement in an unsupervised setting. read more read less

Topics:

Gait (human) (51%)51% related to the paper
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735 Citations
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Physiological Measurement format uses iopart-num citation style.

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Frequently asked questions

1. Can I write Physiological Measurement in LaTeX?

Absolutely not! Our tool has been designed to help you focus on writing. You can write your entire paper as per the Physiological Measurement guidelines and auto format it.

2. Do you follow the Physiological Measurement guidelines?

Yes, the template is compliant with the Physiological Measurement guidelines. Our experts at SciSpace ensure that. If there are any changes to the journal's guidelines, we'll change our algorithm accordingly.

3. Can I cite my article in multiple styles in Physiological Measurement?

Of course! We support all the top citation styles, such as APA style, MLA style, Vancouver style, Harvard style, and Chicago style. For example, when you write your paper and hit autoformat, our system will automatically update your article as per the Physiological Measurement citation style.

4. Can I use the Physiological Measurement templates for free?

Sign up for our free trial, and you'll be able to use all our features for seven days. You'll see how helpful they are and how inexpensive they are compared to other options, Especially for Physiological Measurement.

5. Can I use a manuscript in Physiological Measurement that I have written in MS Word?

Yes. You can choose the right template, copy-paste the contents from the word document, and click on auto-format. Once you're done, you'll have a publish-ready paper Physiological Measurement that you can download at the end.

6. How long does it usually take you to format my papers in Physiological Measurement?

It only takes a matter of seconds to edit your manuscript. Besides that, our intuitive editor saves you from writing and formatting it in Physiological Measurement.

7. Where can I find the template for the Physiological Measurement?

It is possible to find the Word template for any journal on Google. However, why use a template when you can write your entire manuscript on SciSpace , auto format it as per Physiological Measurement's guidelines and download the same in Word, PDF and LaTeX formats? Give us a try!.

8. Can I reformat my paper to fit the Physiological Measurement's guidelines?

Of course! You can do this using our intuitive editor. It's very easy. If you need help, our support team is always ready to assist you.

9. Physiological Measurement an online tool or is there a desktop version?

SciSpace's Physiological Measurement is currently available as an online tool. We're developing a desktop version, too. You can request (or upvote) any features that you think would be helpful for you and other researchers in the "feature request" section of your account once you've signed up with us.

10. I cannot find my template in your gallery. Can you create it for me like Physiological Measurement?

Sure. You can request any template and we'll have it setup within a few days. You can find the request box in Journal Gallery on the right side bar under the heading, "Couldn't find the format you were looking for like Physiological Measurement?”

11. What is the output that I would get after using Physiological Measurement?

After writing your paper autoformatting in Physiological Measurement, you can download it in multiple formats, viz., PDF, Docx, and LaTeX.

12. Is Physiological Measurement's impact factor high enough that I should try publishing my article there?

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 these factors include review board, rejection rates, frequency of inclusion in indexes, and Eigenfactor. You need to assess all these factors before you make your final call.

13. What is Sherpa RoMEO Archiving Policy for Physiological Measurement?

SHERPA/RoMEO Database

We extracted this data from Sherpa Romeo to help researchers understand the access level of this journal in accordance with the Sherpa Romeo Archiving Policy for Physiological Measurement. The table below indicates the level of access a journal has as per Sherpa Romeo's 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.

14. What are the most common citation types In Physiological Measurement?

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

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

15. How do I submit my article to the Physiological Measurement?

It is possible to find the Word template for any journal on Google. However, why use a template when you can write your entire manuscript on SciSpace , auto format it as per Physiological Measurement's guidelines and download the same in Word, PDF and LaTeX formats? Give us a try!.

16. Can I download Physiological Measurement in Endnote format?

Yes, SciSpace provides this functionality. After signing up, you would need to import your existing references from Word or Bib file to SciSpace. Then SciSpace would allow you to download your references in Physiological Measurement Endnote style according to Elsevier guidelines.

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I spent hours with MS word for reformatting. It was frustrating - plain and simple. With SciSpace, I can draft my manuscripts and once it is finished I can just submit. In case, I have to submit to another journal it is really just a button click instead of an afternoon of reformatting.

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