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Special Issue "Multi-Modal Sensors for Human Behavior Monitoring"
Deadline for manuscript submissions: closed (30 September 2019).
Interests: affective and physiological computing; computational vision; intelligent systems; Bayesian modelling; machine learning
Interests: computer vision and image analysis; intelligent systems; deep learning; machine learning; biomedical signal processing; wearable devices
in everyday life we are surrounded by various sensors, wearable and not, that explicitly or implicitly record information on our behavior either visible and hidden (e.g. physiological activity).
Such sensors are of different nature: accelerometer, gyroscope, camera, electrodermal activity sensor, heart rate monitor, breath rate monitor and others.
Most important, the multimodal nature of data is apt to sense and understand the many facets of human daily-life behavior from physical, voluntary activities to social signaling and lifestyle choices influenced by affect, personal traits, age and social context.
The intelligent sensing community is able to exploit the data acquired with these sensors in order to develop machine-learning-based techniques, which can help in improving predictive models of human behavior.
The purpose of this special issue is to gather the latest research in the field of human behavior monitoring, both at the sensing and the understanding levels, by using multimodal data sources.
Applications of interest can relate to domotics, healthcare, transport, education, safety aid, entertainment, sports and others.
Given the need for data in this field of research, scientific works that present data collections are also welcome.
Therefore, contributions to this Special Issue may include, but are not limited to:
- Novel sensing techniques for the non-invasive measurement of physiological signals
- Internet-of-Things based architecture for multimodal monitoring of human behaviour
- Learning and inference from multimodal sensory data
- Real-time multimodal activity recognition
- Semantic interpretation of multimodal sensory data
- Multimodal sensors fusion techniques
- Multimodal databases and benchmarks for behavior monitoring and understanding.
Prof. Giuseppe Boccignone
Dr. Paolo Napoletano
Prof. Raimondo Schettini
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.
- Activity monitoring
- Emotion prediction
- Stress detection
- Fatigue detection
- Fall detection
- Sport-related activity monitoring
- Health monitoring
- Pervasive healthcare
- IoT based monitoring systems
- Machine learning
- Physiological sensors
- Wearable sensors