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Human Behavior Monitoring and Gesture Recognition: Applications for Human-Robot Interaction and Autonomous Systems

This special issue belongs to the section “Wearables“.

Special Issue Information

Dear Colleagues,

This Special Issue (SI) solicits contributions to the design, control, and evaluation of behavior monitoring and recognition systems. In this SI, we welcome contributions that explore monitoring human behaviors and recognizing gestures in applications for human–robot interaction and autonomous systems. Prospective authors are cordially invited to submit their original contributions related to these aspects.

It is important to employ multiple sensory channels for natural human interactions with robots and autonomous systems. Human gestures could be integrated with other modalities of interaction for more natural interactions. A system that is able to extract task-relevant information from the human partners’ gestures and intentions could act accordingly which can be helpful for collaboration and cooperation tasks. A robot or an autonomous system that can assess the activity state of the person and take the action accordingly can lead to a more comfortable and safer HRI.

We especially welcome studies presenting trials, and studies adopting a participatory research design. We encourage submissions of research that advances the practical application of these technologies as well as work on experimental methods, models of human behavior, and design challenges. The submissions that present new datasets are also welcome. The purpose of this SI is to gather a collection of articles reflecting the latest developments in the design of human-behavior monitoring and action recognition.

Topics of interest include, but are not limited to:

  1. Human behavior monitoring systems
  2. Gesture recognition systems
  3. Action recognition systems
  4. Multisensor data fusion for human behavior monitoring
  5. Explainable and interpretable models
  6. Datasets for action/gesture recognition systems
  7. Recognition and prediction of user’s intent
  8. Performance metrics for action/gesture recognition systems
  9. Architectures for action/gesture recognition systems
  10. Solutions to privacy issues in behavior monitoring
  11. Multimodal data integration and visualization
  12. Behavioral coding and analysis for HRI
  13. Behavior interpretation
  14. Behavior tracking systems for smart environments
  15. Social, ethical, and legal implications of recognition systems

Dr. Annica Kristoffersson
Dr. Neziha Akalin
Prof. Dr. Ondrej Krejcar
Guest Editors

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 submissions that pass pre-check are 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 250 words) can be sent to the Editorial Office for assessment.

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 2600 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.

Keywords

  • intelligent sensor systems
  • data acquisition
  • physiological data
  • datasets
  • machine learning
  • multi-sensor data fusion
  • real-time data processing

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Sensors - ISSN 1424-8220