Decision Support Systems for Well-Being: Multisensory, Cognitive and Autonomic Perspectives
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".
Deadline for manuscript submissions: 20 February 2027 | Viewed by 304
Editors
2. Department of Mathematical Science, Graduate School of Engineering Science, The University of Osaka, Osaka 565-0871, Japan
Interests: modeling; social medical systems; medical decision-making and evaluation; empirical research; patient safety; health care services; nursing engineering; innovative healthcare
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Enhancing individual well-being and optimizing human performance have emerged as critical research topics in modern society. Achieving these goals requires systems that go beyond passive state monitoring to actively intervene and support users by regulating their environment based on their real-time state.
This Special Issue focuses on Decision Support Systems utilizing controllable stimuli (actuators) —including vibration, olfaction, vision and audition—aimed at supporting human performance with a focus on well-being.
Unlike traditional approaches, we conceptualize the DSS here as a “sense–infer–decide–act” closed-loop system. This loop integrates state sensing and estimation based on multimodal sensing with decision-making processes and active stimulus presentation (parameter adjustment).
Examples of controllable actuators include vibrotactile stimulation, vibroacoustic/air vibration, fluid stimulation (airflow or water flow) and airflow modulation (either standalone or combined with visual cues).
We welcome experimental studies investigating the relationship between stimulus parameters (timing, intensity, frequency components, spatial patterns, etc.) and objective physiological indices, including autonomic markers (e.g., ECG/HRV, respiration, perspiration, EEG/ERP, peripheral circulation). Studies linking these factors to attention, stress/arousal regulation, learning and task performance are particularly encouraged.
Furthermore, we seek research that integrates behavioral measurement and environmental sensing into a “Sensing-to-Action Pipeline”, capable of recommending personalized stimulus settings or adaptive control policies in real time.
Prof. Dr. Yuko Ohno
Prof. Dr. Mitsuo Tonoike
Guest Editors
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Keywords
- “sense–infer–decide–act” closed-loop system
- enhancing individual well-being
- multi-sensory
- vibrotactile stimulation
- decision support system
- physiological indices
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