This brief paper sets out arguments for the introduction of new technologies into telecare and lifestyle monitoring that can detect and monitor the emotive state of patients. The significantly increased use of computers by older people will enable the elements of emotive computing to be integrated with features such as keyboards and webcams, to provide additional information on emotional state. When this is combined with other data, there will be significant opportunities for system enhancement and the identification of changes in user status, and hence of need. The ubiquity of home computing makes the keyboard a very attractive, economic and non-intrusive means of data collection and analysis.
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http://dx.doi.org/10.1258/jtt.2011.011001 | DOI Listing |
Psychophysiology
January 2025
Fudan Institute on Ageing, Fudan University, Shanghai, China.
It is common to make risky decisions under time pressure. However, there are ongoing debates regarding the interpretation of the intrinsic mechanisms through which time pressure influences risky decision-making. The current study, combining a sequential risk-taking task, behavioral modeling, and time-resolved multivariate pattern analysis on electroencephalography signals, explored the intrinsic mechanisms underlying the influence of time pressure on risky decision-making.
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December 2024
MediaTek Inc, Beijing, 10016, China.
The phenomenon that the depression risk among doctoral students is higher than that of other groups should not be ignored. Despite this, studies specifically addressing depression risk in doctoral students are relatively scarce, and existing findings are not universally applicable. Using neural network feature extraction technology, this study aims to investigate the factors contributing to the high depression risk of doctoral students and effectively identify doctoral students at depression risk, so as to propose corresponding improvement strategies to prevent and intervene doctoral students with depression risk for universities.
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December 2024
Potsdam University of Applied Sciences, Kiepenheuerallee 5, 14469, Potsdam, Germany.
Persuasive appeals frequently prove ineffective or produce unintended outcomes, due to the presence of motivated reasoning. Using the example of electric cars adoption, this research delves into the impact of emotional content, message valence, and the coherence of pre-existing attitudes on biased information evaluation. By conducting a factorial survey (N = 480) and incorporating a computational model of attitude formation, we aim to gain a deeper insight into the cognitive-affective mechanisms driving motivated reasoning.
View Article and Find Full Text PDFNat Commun
December 2024
Department of Psychology, Cornell University, Ithaca, NY, USA.
Subjective feelings are thought to arise from conceptual and bodily states. We examine whether the valence of feelings may also be decoded directly from objective ecological statistics of the visual environment. We train a visual valence (VV) machine learning model of low-level image statistics on nearly 8000 emotionally charged photographs.
View Article and Find Full Text PDFTransl Psychiatry
December 2024
School of Computer Science and Technology (School of Data Science), Taiyuan University of Technology, Taiyuan, 030024, China.
Bipolar disorder (BD) is a neuropsychiatric disorder characterized by severe disturbance and fluctuation in mood. Dynamic functional connectivity (dFC) has the potential to more accurately capture the evolving processes of emotion and cognition in BD. Nevertheless, prior investigations of dFC typically centered on larger time scales, limiting the sensitivity to transient changes.
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