IEEE Transactions on Neural Systems and Rehabilitation Engineering

Top Research Topics at IEEE Transactions on Neural Systems and Rehabilitation Engineering?

The journal primarily focuses on research topics in Artificial intelligence, Neuroscience, Pattern recognition, Rehabilitation engineering and Human–computer interaction. Finger movement, Robotics and Neural engineering studies in the realm of Artificial intelligence interact with fields like Decoding methods. While Robotics is the key highlight in IEEE Transactions on Neural Systems and Rehabilitation Engineering, it also covered some subjects on Rehabilitation robotics and Physical medicine and rehabilitation.

The concepts on Neuroscience presented in it can also apply to other research fields, including Repetitive movements and Theme (narrative). The featured Pattern recognition research zeroes in on concepts in Discriminative model but also tackles themes under Bayesian filtering, Surface (mathematics), Nonlinear dimensionality reduction and Movement (music). The journal focuses on Rehabilitation engineering but the discussions also offer insight into other areas such as Neural system and Robot.

The studies in Neural system featured incorporate elements of Software engineering and Internet privacy. IEEE Transactions on Neural Systems and Rehabilitation Engineering focuses on Robot but sometimes tackles the closely related topic of Emerging technologies which is concerned with Multimedia. Human–computer interaction research featured in IEEE Transactions on Neural Systems and Rehabilitation Engineering incorporates concerns from various other topics such as Brain–computer interface and Biomedical engineering.

• Artificial intelligence (15.71%)
• Neuroscience (7.14%)
• Pattern recognition (5.71%)

What are the most cited papers published in the journal?

• Guest editorial brain-computer interface technology: a review of the second international meeting (255 citations)
• Electrical Stimulation of the Rectus Femoris During Pre-swing Diminishes Hip and Knee Flexion During the Swing Phase of Normal Gait (10 citations)
• Guest Editorial Special Theme on Virtual Rehabilitation (9 citations)

Research areas of the most cited articles at IEEE Transactions on Neural Systems and Rehabilitation Engineering:

The published papers investigate areas of study like Human–computer interaction, Brain–computer interface, Application software, Electroencephalography and Computer network. The journal papers with studies in Human–computer interaction featured incorporate elements of Rehabilitation and Multimedia. Computer network study tackled in the journal papers is connected to the field of Electrical engineering.

What topics the last edition of the journal is best known for?

• Artificial intelligence
• Neuroscience
• Robotics

The previous edition focused in particular on these issues:

IEEE Transactions on Neural Systems and Rehabilitation Engineering was organized to reinforce research efforts on Rehabilitation engineering, Ambulatory, Machine learning, Artificial intelligence and Neural system. Rehabilitation engineering research presented in IEEE Transactions on Neural Systems and Rehabilitation Engineering encompasses a variety of subjects, including Robot, Wearable robot, Multimedia and Focus (computing). Aside from research in Neural system, it also discusses Ability to pay studies.

The most cited articles from the last journal are:

• Corrections to “Accurate Ambulatory Gait Analysis in Walking and Running Using Machine Learning Models” (1 citations)
• Special Issue on Wearable Robotics and Assistive Technology (0 citations)
• TNSRE Is Flipping to Full Open Access (0 citations)

Papers citation over time

A key indicator for each journal is its effectiveness in reaching other researchers with the papers published at that venue.

The chart below presents the interquartile range (first quartile 25%, median 50% and third quartile 75%) of the number of citations of articles over time.

Top authors and change over time

The top authors publishing in IEEE Transactions on Neural Systems and Rehabilitation Engineering (based on the number of publications) are:

• Ning Jiang (5 papers) absent at the last edition,
• Nitish V. Thakor (4 papers) absent at the last edition,
• Dario Farina (3 papers) absent at the last edition,
• Daniel P. Ferris (3 papers) published 2 papers at the last edition, 1 more than at the previous edition,
• Kara Mcarthur (3 papers) published 2 papers at the last edition, 1 more than at the previous edition.

The overall trend for top authors publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top authors.

Top affiliations and change over time

Only papers with recognized affiliations are considered

The top affiliations publishing in IEEE Transactions on Neural Systems and Rehabilitation Engineering (based on the number of publications) are:

• Sant'Anna School of Advanced Studies (2 papers) absent at the last edition,
• Johns Hopkins University (2 papers) absent at the last edition,
• New York State Department of Health (1 papers) absent at the last edition,
• École Polytechnique Fédérale de Lausanne (1 papers) absent at the last edition,
• Polytechnic University of Milan (1 papers) absent at the last edition.

The overall trend for top affiliations publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top affiliations.

Publication chance based on affiliation

The publication chance index shows the ratio of articles published by the best research institutions in the journal edition to all articles published within that journal. The best research institutions were selected based on the largest number of articles published during all editions of the journal.

The chart below presents the percentage ratio of articles from top institutions (based on their ranking of total papers).Top affiliations were grouped by their rank into the following tiers: top 1-10, top 11-20, top 21-50, and top 51+. Only articles with a recognized affiliation are considered.

During the most recent 2020 edition, 66.67% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 0.00% were posted by at least one author from the top 10 institutions publishing in the journal. Another 0.00% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 100.00% of all publications and 0.00% were from other institutions.

Returning Authors Index

A very common phenomenon observed among researchers publishing scientific articles is the intentional selection of journals they have already attended in the past. In particular, it is worth analyzing the case when the authors participate in the same journal from year to year.

The Returning Authors Index presented below illustrates the ratio of authors who participated in both a given as well as the previous edition of the journal in relation to all participants in a given year.

Returning Institution Index

The graph below shows the Returning Institution Index, illustrating the ratio of institutions that participated in both a given and the previous edition of the conference in relation to all affiliations present in a given year.

The experience to innovation index

Our experience to innovation index was created to show a cross-section of the experience level of authors publishing in a journal. The index includes the authors publishing at the last edition of a journal, grouped by total number of publications throughout their academic career (P) and the total number of citations of these publications ever received (C).

The group intervals were selected empirically to best show the diversity of the authors' experiences, their labels were selected as a convenience, not as judgment. The authors were divided into the following groups:

• Novice - P < 5 or C < 25 (the number of publications less than 5 or the number of citations less than 25),
• Competent - P < 10 or C < 100 (the number of publications less than 10 or the number of citations less than 100),
• Experienced - P < 25 or C < 625 (the number of publications less than 25 or the number of citations less than 625),
• Master - P < 50 or C < 2500 (the number of publications less than 50 or the number of citations less than 2500),
• Star - P ≥ 50 and C ≥ 2500 (both the number of publications greater than 50 and the number of citations greater than 2500).

The chart below illustrates experience levels of first authors in cases of publications with multiple authors.

Career Opportunities in Neural Systems and Rehabilitation Engineering

If you are inspired by the research topics covered in IEEE Transactions on Neural Systems and Rehabilitation Engineering and considering a career in a related field, it is essential to understand the various opportunities available. Working in the realm of Neural systems, Rehabilitation engineering, and Human-computer interaction offers a range of diverse roles, one of them being a preschool teacher assistant. In this position, you can utilize your understanding of neuroscience and artificial intelligence to aid early child development effectively.

In Florida, becoming a preschool teacher assistant requires specific qualifications and training. If you are interested in pursuing this career path, you can refer to our comprehensive guide on preschool teacher assistant requirements in Florida to familiarize yourself with the necessary steps. This guide provides information on the required education, certifications, and skills needed to thrive in this rewarding position.

There are various other roles within the Neural Systems and Rehabilitation Engineering field apart from a preschool teacher assistant, offering opportunities to contribute in different areas such as Research, Medical Rehabilitation, and Robotics. By exploring these opportunities, you can identify a career path that aligns with your interests and expertise.