Special Issue "EMG Sensors and Applications"
Deadline for manuscript submissions: 1 December 2019
The electromyogram (EMG) signal is a biological signal produced by muscles throughout the human body when contracted and represents neuromuscular activity. Impressive advancements have been made in EMG signal processing and pattern recognition over the past several decades. This has greatly increased the number of potential applications for the use of EMG, including but not limited to, powered upper-limb prostheses, electric power wheelchairs, human-computer-interactions, and diagnoses in clinical applications.
In early works, a common approach to measuring EMG signals, known as sparse multi-channel surface EMG, required placing electrodes precisely over specific muscles. To facilitate EMG-based interfaces for everyday use, however, their use should be simple and non-invasive, such as a watch, an armband, jewellery, or concealed beneath clothing. More recently, EMG sensors have been positioned more generally, such as radially around the circumference of a flexible band (e.g., EMG armbands and high-density surface EMG grids (HD-EMG)). Due to the recent development of these sensors, together with advances in wireless communication and embedded computing technologies, EMG data can indeed now be obtained unobtrusively using wearable EMG devices.
EMG data collected from these different classes of surface EMG sensors have been analysed in both the temporal and spatial domains, leading to advances based on novel signal processing and machine learning techniques. For example, HD-EMG can be viewed as an EMG image, and thus can be analysed using image processing techniques and deep learning (as exemplified by a convolutional neural network) approaches.
The aim of this Special Issue is to bring together leading active researchers in the development of EMG sensors and their applications. Works on innovative EMG signal processing and machine learning algorithms aimed at addressing critical issues related to this new generation of EMG sensors are also encouraged.
Dr. Erik Scheme
Dr. Angkoon Phinyomark
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. Sensors is an international peer-reviewed open access semimonthly 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 1800 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.
- Electromyography (EMG)
- Surface electromyogram (sEMG)
- High-density surface EMG (HD-EMG)
- Wearable sensors
- EMG feature extraction
- EMG pattern recognition
- Gesture recognition
- Muscle-computer interface
- Myoelectric control