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Sensor-Based Approaches to Understanding Human Behavior

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Biomedical Sensors".

Deadline for manuscript submissions: closed (20 December 2023) | Viewed by 2279

Special Issue Editor


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Guest Editor
Department of Mechanical and Electrical Engineering, University of Southern Denmark, 5230 Sonderborg, Denmark
Interests: speech prosody; speech perception; speech technology

Special Issue Information

Dear Colleagues,

Research is currently at a point at which the development of cheap and powerful sensor technology coincides with the increasingly complex multimodal analysis of human behavior. In other words, we are at a point where the application of existing sensor technology as well as the development of new sensor technology can significantly advance our understanding of human behavior. Our special issue takes up this momentum and is intended to bring together for the first time strongly cross-disciplinary research under one roof – so that the individual disciplines can inform, inspire, and stimulate each other. Accordingly, human behavior is meant in a very broad sense and supposed to include, besides speech behavior, the expression of emotions and moods, body language, body movements (including sports), pain, stress, and health issues related to behavior or behavior changes, behavior towards robots or machines in general, etc. Examples of relevant sensor technologies are EEG, EMG, SCR (skin-conductance response), Heart Rate, Breathing, EGG (Electroglottogram), tactile/pressure sensors, gyroscopes, MoCap sensors and/or accelerometers capturing body movements, VR/AR-related sensor technologies, etc. Besides empirical contributions addressing current questions, outlines of future trends, review articles, applications of AI to sensor technology, and presentations of new pieces of sensor technology are very welcome too.

Dr. Oliver Niebuhr
Guest Editor

Manuscript Submission Information

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Published Papers (2 papers)

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Research

16 pages, 1371 KiB  
Article
Quantifying the Impact of Motions on Human Aiming Performance: Evidence from Eye Tracking and Bio-Signals
by Yuzhang Li, Xinming Li, Peter R. Grant and Bin Zheng
Sensors 2024, 24(5), 1518; https://doi.org/10.3390/s24051518 - 26 Feb 2024
Viewed by 552
Abstract
Working on a moving platform can significantly impede human performance. Previous studies on moving vehicles have often focused on the overall impact on general task performance, whereas our study’s emphasis is on precise hand movements, exploring the interaction between body motion and the [...] Read more.
Working on a moving platform can significantly impede human performance. Previous studies on moving vehicles have often focused on the overall impact on general task performance, whereas our study’s emphasis is on precise hand movements, exploring the interaction between body motion and the escalation of task difficulty. We recruited 28 participants to engage in reciprocal aiming tasks, following Paul Fitts’s setting, under both in-motion and stationary conditions. The task index of difficulty (ID) was manipulated by varying the width of the targets and the distance between the targets. We measured participants’ movement time (MT), performance errors, and monitored their eye movements using an eye-tracking device, heart rate (HR), and respiration rate (RR) during the tasks. The measured parameters were compared across two experimental conditions and three ID levels. Compared to the stationary conditions, the in-motion conditions degraded human aiming performance, resulting in significantly prolonged MT, increased errors, and longer durations of eye fixations and saccades. Furthermore, HR and RR increased under the in-motion conditions. Linear relationships between MT and ID exhibited steeper slopes under the in-motion conditions compared to the stationary conditions. This study builds a foundation for us to explore the control mechanisms of individuals working in dynamic and demanding environments, such as pilots in airplanes and paramedics in ambulances. Full article
(This article belongs to the Special Issue Sensor-Based Approaches to Understanding Human Behavior)
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12 pages, 1564 KiB  
Article
Remote Spectral Light Sensing in the Home Environment: Further Development of the TWLITE Study Concept
by Christina L. Reynolds, Aylmer Tan, Jonathan E. Elliott, Carolyn E. Tinsley, Rachel Wall, Jeffrey A. Kaye, Lisa C. Silbert and Miranda M. Lim
Sensors 2023, 23(8), 4134; https://doi.org/10.3390/s23084134 - 20 Apr 2023
Cited by 1 | Viewed by 1209
Abstract
Aging is a significant contributor to changes in sleep patterns, which has compounding consequences on cognitive health. A modifiable factor contributing to poor sleep is inadequate and/or mistimed light exposure. However, methods to reliably and continuously collect light levels long-term in the home, [...] Read more.
Aging is a significant contributor to changes in sleep patterns, which has compounding consequences on cognitive health. A modifiable factor contributing to poor sleep is inadequate and/or mistimed light exposure. However, methods to reliably and continuously collect light levels long-term in the home, a necessity for informing clinical guidance, are not well established. We explored the feasibility and acceptability of remote deployment and the fidelity of long-term data collection for both light levels and sleep within participants’ homes. The original TWLITE study utilized a whole-home tunable lighting system, while the current project is an observational study of the light environment already existing in the home. This was a longitudinal, observational, prospective pilot study involving light sensors remotely deployed in the homes of healthy adults (n = 16, mean age: 71.7 years, standard deviation: 5.0 years) who were co-enrolled in the existing Collaborative Aging (in Place) Research Using Technology (CART) sub-study within the Oregon Center for Aging and Technology (ORCATECH). For 12 weeks, light levels were recorded via light sensors (ActiWatch Spectrum), nightly sleep metrics were recorded via mattress-based sensors, and daily activity was recorded via wrist-based actigraphy. Feasibility and acceptability outcomes indicated that participants found the equipment easy to use and unobtrusive. This proof-of-concept, feasibility/acceptability study provides evidence that light sensors can be remotely deployed to assess relationships between light exposure and sleep among older adults, paving the way for measurement of light levels in future studies examining lighting interventions to improve sleep. Full article
(This article belongs to the Special Issue Sensor-Based Approaches to Understanding Human Behavior)
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