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Special Issue "Recent Advances in Motion Analysis"
Deadline for manuscript submissions: 30 June 2020.
Interests: EMG signal processing (filtering, feature extraction, pattern recognition, time–frequency analysis) and interpretation (physiology, clinics, sport); gait analysis; static and perturbed posturography; machine learning applications in motion analysis
Interests: stereophotogrammetry; linear and nonlinear filtering; joint kinematics; analysis and identification of postural control; static and perturbed posturography; gait analysis; dynamic electromyography; wearable devices for motion analysis
The advances in the technology and methodology for human movement capture and analysis have been remarkable over the last decade. Besides acknowledged approaches for kinematic, dynamic, and EMG analysis carried out in the laboratory, more recently developed devices, such as wearables, inertial measurement units, ambient sensors, and cameras or depth sensors, have been adopted on a wide scale. Thus, the synergy of classic instrumentation and novel smart devices has created unique capabilities in the continuous monitoring of motor behaviors in different fields, such as clinics, sports, and ergonomics. However, real-time sensing, signal processing, recognition, characterization, and interpretation of motion metrics and behaviors from sensor data are representing a challenging problem, not only in laboratories, but also at home and in the community.
This Special Issue is designed to comprehensively cover the open research issues related to the improvement of classic approaches and the development of novel technologies and techniques in the domain of motion analysis in all the various fields of application (clinics, sports, ergonomics, etc.). Computational intelligence (CI) methods, such as artificial neural networks, have recently emerged as promising tools for the development and application of intelligent systems in motion analysis. Thus, contributions in this field are also welcome. This Special Issue will consider original research, reviews, and applications in clinics, sports, and ergonomics. Areas of interest include, but are not limited to, the following:
- Recent advances in kinematic and dynamic analysis;
- Recent advances in EMG signal processing;
- Recent advances in static and dynamic posturography;
- Recent advances in gait analysis;
- Wearables and inertial measurement units in motion analysis;
- Artificial neural networks for motion analysis.
Dr. Francesco Di Nardo
Prof. Dr. Sandro Fioretti
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Electronics is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
- Motion analysis
- Movement biomechanics
- Electromyography (EMG)
- Inertial measurement units (IMU)
- Gait analysis
- Static and perturbed posture
- Machine learning applications in motion analysis