Zobrazeno 1 - 10
of 2 757
pro vyhledávání: '"physiological signals"'
Publikováno v:
Journal of Services Marketing, 2024, Vol. 38, Issue 9, pp. 1117-1131.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/JSM-06-2024-0299
Publikováno v:
Frontiers in Public Health, Vol 12 (2024)
IntroductionAn increasing prevalence of psychological stress and emotional issues among higher education teachers necessitates innovative approaches to promote their wellbeing. Emotion recognition technology, integrated into educational human–compu
Externí odkaz:
https://doaj.org/article/32b233da405e4b54b41ed90058ade5db
Autor:
George Datseris, Jacob S. Zelko
Publikováno v:
Frontiers in Network Physiology, Vol 4 (2024)
In this mini review, we propose the use of the Julia programming language and its software as a strong candidate for reproducible, efficient, and sustainable physiological signal analysis. First, we highlight available software and Julia communities
Externí odkaz:
https://doaj.org/article/dbc8c84fa7694d7fbfa07b6190fe4ad9
Publikováno v:
Frontiers in Medical Engineering, Vol 2 (2024)
Stress has been recognized as a pivotal indicator which can lead to severe mental disorders. Persistent exposure to stress will increase the risk for various physical and mental health problems. Early and reliable detection of stress-related status i
Externí odkaz:
https://doaj.org/article/86c0309145ee4fac8fd4cc1d71ba1827
Publikováno v:
Frontiers in Neurorobotics, Vol 18 (2024)
Physiological signal recognition is crucial in emotion recognition, and recent advancements in multi-modal fusion have enabled the integration of various physiological signals for improved recognition tasks. However, current models for emotion recogn
Externí odkaz:
https://doaj.org/article/d4f2cf6c93c34f06a49c1072be8adff6
Autor:
Jiapu Chai, Yan Li
Publikováno v:
Medicine in Novel Technology and Devices, Vol 24, Iss , Pp 100340- (2024)
MATB (Multi-Attribute Task Battery), developed by NASA, simulates real-world task demands and work environments. It assesses human cognitive and executive abilities in high-load, complex task settings, as well as their adaptive capacity for task swit
Externí odkaz:
https://doaj.org/article/42af5d077d814eb5b15d31cef74aabb5
Autor:
Huijing Li, Hong Sun
Publikováno v:
Systems and Soft Computing, Vol 6, Iss , Pp 200092- (2024)
A multi-modal feature based motion emotion analysis model based on a fusion deep learning model is proposed for the problem of analyzing the motion emotions of participants in the joint exercise quality expansion task. This model involves three major
Externí odkaz:
https://doaj.org/article/1593d77f26474cd5b95b50f629ff9b02
Publikováno v:
Computers in Human Behavior Reports, Vol 15, Iss , Pp 100457- (2024)
This study investigates the dynamics between social media engagement and well-being, employing a multi-dimensional analysis encompassing psychological, behavioral, social media usage patterns, and physiological perspectives. Through the utilization o
Externí odkaz:
https://doaj.org/article/d55892b34c2f472b82aa06f9f2dd1065
Publikováno v:
Frontiers in Virtual Reality, Vol 5 (2024)
Cybersickness is still a prominent risk factor potentially affecting the usability of virtual reality applications. Automated real-time detection of cybersickness promises to support a better general understanding of the phenomena and to avoid and co
Externí odkaz:
https://doaj.org/article/ea5db93ecc994f3aa200f38929f55fd6
Autor:
Sina Labbaf, Mahyar Abbasian, Brenda Nguyen, Matthew Lucero, Maryam Sabah Ahmed, Asal Yunusova, Alexander Rivera, Ramesh Jain, Jessica L. Borelli, Nikil Dutt, Amir M. Rahmani
Publikováno v:
Data in Brief, Vol 54, Iss , Pp 110228- (2024)
This dataset was collected from university students before, during, and after the COVID-19 lockdown in Southern California. Data collection happened continuously for the average of 7.8 months (SD=3.8, MIN=1.0, MAX=13.4) from a population of 21 studen
Externí odkaz:
https://doaj.org/article/08d587f372a64673a2c2ec326e10494e