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DTSTAMP:20231221T152341Z
UID:E8CE9351-A9F1-4EB0-BDFB-5A3DF3C61DB2
DTSTART;TZID=America/New_York:20231121T110000
DTEND;TZID=America/New_York:20231121T120000
DESCRIPTION:Nowadays\, due to the fast pace of society and the pressure fro
 m all aspects of work and life\, many individuals suffer from stress and a
 ssociated negative emotions. Prolonged exposure to such emotions can escal
 ate into more severe mental and physical disorders\, underlining the impor
 tance of monitoring emotional changes. The advent of Internet of Things (I
 oT) systems has opened new avenues for analyzing and predicting people's s
 tress or emotions through technology\, which can enable people to pay more
  attention to their mental health in time. As emotional fluctuations can a
 ffect physiological signals\, monitoring these can offer insight into one'
 s emotional state. Specifically\, the fluctuations in skin conductivity re
 sulting from different sweat secretion levels make electrodermal activity 
 (EDA) signals a promising candidate for emotion detection. With the advant
 ages of wearable devices equipped with EDA and other physiological signal 
 sensors in IoT systems\, there is a convenient and cost-effective avenue t
 o collect the EDA data. This seminar will introduce the mechanisms of stre
 ss and emotion detection with EDA and methods to process and analyze the s
 ignals. Moreover\, the existing difficulties and future directions in this
  field will also be discussed.\n\nFurthermore\, the speaker will share ins
 ights from her highly productive Ph.D. journey\, particularly focusing on 
 her extensive experience in publishing journal and conference papers.\n\nC
 o-sponsored by: OC2 Lab - Western University\n\nSpeaker(s): Lili Zhu\, \n\
 nVirtual: https://events.vtools.ieee.org/m/382075
LOCATION:Virtual: https://events.vtools.ieee.org/m/382075
ORGANIZER:lyang339@uwo.ca
SEQUENCE:23
SUMMARY:Stress and Emotion Detection in IoT Systems with Machine Learning T
 echniques and Wearable Devices
URL;VALUE=URI:https://events.vtools.ieee.org/m/382075
X-ALT-DESC:Description: <br /><p>Nowadays\, due to the fast pace of society
  and the pressure from all aspects of work and life\, many individuals suf
 fer from stress and associated negative emotions. Prolonged exposure to su
 ch emotions can escalate into more severe mental and physical disorders\, 
 underlining the importance of monitoring emotional changes. The advent of 
 Internet of Things (IoT) systems has opened new avenues for analyzing and 
 predicting people's stress or emotions through technology\, which can enab
 le people to pay more attention to their mental health in time. As emotion
 al fluctuations can affect physiological signals\, monitoring these can of
 fer insight into one's emotional state. Specifically\, the fluctuations in
  skin conductivity resulting from different sweat secretion levels make el
 ectrodermal activity (EDA) signals a promising candidate for emotion detec
 tion. With the advantages of wearable devices equipped with EDA and other 
 physiological signal sensors in IoT systems\, there is a convenient and co
 st-effective avenue to collect the EDA data. This seminar will introduce t
 he mechanisms of stress and emotion detection with EDA and methods to proc
 ess and analyze the signals. Moreover\, the existing difficulties and futu
 re directions in this field will also be discussed.</p>\n<p>Furthermore\, 
 the speaker will share insights from her highly productive Ph.D. journey\,
  particularly focusing on her extensive experience in publishing journal a
 nd conference papers.</p>
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