Special Issue "Wearable Sensors and Artificial Intelligence for Ergonomics—2nd Edition"

Dear Colleagues,

Ergonomics can contribute to maximizing human wellbeing and the efficiency of a working system safeguarding workers’ health. The development of wearable sensors, which are able to collect a wide variety of relevant physiological and environmental parameters, allows for acquiring signals related to the workers in a nonintrusive, automatic and continuous way. Data can be acquired through both custom-made devices (namely, ad hoc ones developed by scientific researchers) and commercial wearable devices. The availability of instruments (such as wearable motion trackers, inertial measurement units, pressure sensors, eye- and face-expression-tracking devices and smart sensors for temperature, breathing, electrocardiography, electroencephalography, electromyography and electrodermal activity) offers a wide perspective for novel solutions in the ergonomic field.

On the other hand, the number of proposed techniques for data processing and analysis increases every day. Newer approaches using deep-learning and classical machine-learning techniques to assess the potential biomechanical risk to which workers are exposed during their work activities are also gaining significant interest in the ergonomic field.

Consequently, this Special Issue (“Wearable Sensors and Artificial Intelligence for Ergonomics—Volume 2”) aims to both highlight several of the latest developments in the ergonomic/occupational medicine fields and gather proposals which can help delineate a novel emerging branch which considers wearable sensors a tool for biomechanical risk assessment and injury prevention—even through the help of artificial intelligence—during work-, home-, sport- and leisure-related activities. Both research papers and review articles will be considered for publication. We welcome submissions spanning topics across the design of novel sensors and commercial wearable technologies and the development of any novel methodology which aims to integrate quantitative physiological and environmental information—with and without the use of artificial intelligence—as those are the main goals of ergonomics.

Topics of interest include, but are not limited to, the following application fields for machine learning:

• Ergonomics and occupational medicine
• Wearable sensors, motion sensors, force/pressure sensors, EMG sensors for ergonomics
• Sensors for wellbeing
• Smart clothes and e-textiles for ergonomic applications
• Activity-monitoring devices and systems
• Machine learning and deep learning for wearable data analysis
• Biomechanical risk assessment
• Health monitoring in working environments
• Work-related musculoskeletal disorders
• Novel design approaches for ergonomic assessment
• mHealth and/or eHealth solutions for ergonomics
• Data processing applied to risk assessments

Dr. Leandro Donisi
Dr. Carlo Ricciardi
Dr. Alfonso Maria Ponsiglione
Dr. Giuseppe Cesarelli
Guest Editors

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• medical diagnosis
• ergonomics
• occupational medicine
• biomedical signal processing
• biomechanics
• human-activity recognition
• inertial measurement units and sensors for IoT
• feature extraction
• lifting
• machine learning
• modeling and simulation
• neural networks