Výsledky vyhledávání

Akademický článek

Comparing multimodal physiological responses to social and physical pain in healthy participants

Autor: Eun-Hye Jang, Young-Ji Eum, Daesub Yoon, Jin-Hun Sohn, Sangwon Byun

Publikováno v: Frontiers in Public Health, Vol 12 (2024)

BackgroundPrevious physiology-driven pain studies focused on examining the presence or intensity of physical pain. However, people experience various types of pain, including social pain, which induces negative mood; emotional distress; and neural ac

Externí odkaz: https://doaj.org/article/570d4c04899d4e8495b534844f0b716f

Zobrazit plný text záznamu

Akademický článek

Factors affecting real-time evaluation of muscle function in smart rehab systems

Autor: Hyunwoo Joe, Hyunsuk Kim, Seung-Jun Lee, Tae Sung Park, Myung-Jun Shin, Hooman Lee, Daesub Yoon, Woojin Kim

Publikováno v: ETRI Journal, Vol 45, Iss 4, Pp 603-614 (2023)

Advancements in remote medical technologies and smart devices have led to expectations of contactless rehabilitation. Conventionally, rehabilitation requires clinicians to perform routine muscle function assessments with patients. However, assessment

Externí odkaz: https://doaj.org/article/f5c06dbd10514925b3768f44e7a495fb

Zobrazit plný text záznamu

Akademický článek

Machine learning-based classification analysis of knowledge worker mental stress

Autor: Hyunsuk Kim, Minjung Kim, Kyounghyun Park, Jungsook Kim, Daesub Yoon, Woojin Kim, Cheong Hee Park

Publikováno v: Frontiers in Public Health, Vol 11 (2023)

The aim of this study is to analyze the performance of classifying stress and non-stress by measuring biosignal data using a wearable watch without interfering with work activities at work. An experiment is designed where participants wear a Galaxy W

Externí odkaz: https://doaj.org/article/ecf72793e5544d6d94b23a7780c7a67d

Zobrazit plný text záznamu

Akademický článek

Study on the Take-over Performance of Level 3 Autonomous Vehicles Based on Subjective Driving Tendency Questionnaires and Machine Learning Methods

Autor: Hyunsuk Kim, Woojin Kim, Jungsook Kim, Seung-Jun Lee, Daesub Yoon, Oh-Cheon Kwon, Cheong Hee Park

Publikováno v: ETRI Journal, Vol 45, Iss 1, Pp 75-92 (2023)

Level 3 autonomous vehicles require conditional autonomous driving in which autonomous and manual driving are alternately performed; whether the driver can resume manual driving within a limited time should be examined. This study investigates whethe

Externí odkaz: https://doaj.org/article/7247164b9ed242dfac30e1f1a9781661

Zobrazit plný text záznamu

Akademický článek

A novel study on subjective driver readiness in terms of non-driving related tasks and take-over performance

Autor: Jungsook Kim, Woojin Kim, Hyun-Suk Kim, Seung-Jun Lee, Oh-Cheon Kwon, Daesub Yoon

Publikováno v: ICT Express, Vol 8, Iss 1, Pp 91-96 (2022)

This study investigates the influence of Non-Driving Related Tasks (NDRTs) on subjective driver readiness and take-over performance in level 3 automated driving system, and the effect of the readiness on driver’s take-over performance. A driving si

Externí odkaz: https://doaj.org/article/0453c11b829340269b676b3959d24106

Zobrazit plný text záznamu

Akademický článek

Driver Behavior Recognition via Interwoven Deep Convolutional Neural Nets With Multi-Stream Inputs

Autor: Chaoyun Zhang, Rui Li, Woojin Kim, Daesub Yoon, Paul Patras

Publikováno v: IEEE Access, Vol 8, Pp 191138-191151 (2020)

Understanding driver activity is vital for in-vehicle systems that aim to reduce the incidence of car accidents rooted in cognitive distraction. Automating real-time behavior recognition while ensuring actions classification with high accuracy is how

Externí odkaz: https://doaj.org/article/ab28758f8c92475cb5716345fbef3fb5

Zobrazit plný text záznamu