TY - GEN
T1 - Unobtrusive identification of cognitive states for improved knowledge acquisition
AU - Tag, Benjamin
AU - Sugiura, Kazunori
N1 - Publisher Copyright:
© 2018 Copyright is held by the owner/author(s). Publication rights licensed to ACM.
PY - 2018/10/8
Y1 - 2018/10/8
N2 - One of the major steps in the evolution of Human-computer interaction (HCI) is the introduction of physiological computing. Real-time measurements and analysis of physiological signals through sensors help opening up an implicit communication channel between computers and their users. Awareness of the user's emotional and cognitive states allow computers to react and adapt in real time, and therefore potentially maximize HCI performance efficiency and communication. Ubiquitous wearable computing enables us to make use of computational power in everyday situations. This liberates experiments and applications from necessary heavy stationary devices and controlled laboratory environments. Physiological computing has been used to increase the efficiency of performance, and improve the pleasure derived from interacting with computers. By analyzing physiological data from the user, cognitive states can be monitored and identified [6]. Thereby, the computer becomes aware of the physical, mental, and emotional context of a user. Consequently, the physical data describing negative or positive states can be used as an input modality to dynamically adjust the system, e.g. by altering certain contents, by providing assistance with additional information, turning on/off of certain functions, or triggering a reminder to take a break or walk when sleepiness or frustration result in decreasing attention. These context-aware systems have a proactive nature and therefore omit the necessity for explicit input devices, such as a mouse or a keyboard. They are able to create an interactive loop between a user and a computer. Since the user is constantly processing the information received (e.g. from a watched video), and the ubiquity of mobile devices allows for sensor data to be constantly monitored and processed, we can create biocybernetic loops that are able to respond to desirable and undesirable states [13].
AB - One of the major steps in the evolution of Human-computer interaction (HCI) is the introduction of physiological computing. Real-time measurements and analysis of physiological signals through sensors help opening up an implicit communication channel between computers and their users. Awareness of the user's emotional and cognitive states allow computers to react and adapt in real time, and therefore potentially maximize HCI performance efficiency and communication. Ubiquitous wearable computing enables us to make use of computational power in everyday situations. This liberates experiments and applications from necessary heavy stationary devices and controlled laboratory environments. Physiological computing has been used to increase the efficiency of performance, and improve the pleasure derived from interacting with computers. By analyzing physiological data from the user, cognitive states can be monitored and identified [6]. Thereby, the computer becomes aware of the physical, mental, and emotional context of a user. Consequently, the physical data describing negative or positive states can be used as an input modality to dynamically adjust the system, e.g. by altering certain contents, by providing assistance with additional information, turning on/off of certain functions, or triggering a reminder to take a break or walk when sleepiness or frustration result in decreasing attention. These context-aware systems have a proactive nature and therefore omit the necessity for explicit input devices, such as a mouse or a keyboard. They are able to create an interactive loop between a user and a computer. Since the user is constantly processing the information received (e.g. from a watched video), and the ubiquity of mobile devices allows for sensor data to be constantly monitored and processed, we can create biocybernetic loops that are able to respond to desirable and undesirable states [13].
KW - Circadian computing
KW - Cognition-aware systems
KW - Cognitive load
KW - Eye blink
KW - Fatigue
KW - Thermography
KW - Wearable sensors
UR - http://www.scopus.com/inward/record.url?scp=85058313835&partnerID=8YFLogxK
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U2 - 10.1145/3267305.3267315
DO - 10.1145/3267305.3267315
M3 - Conference contribution
AN - SCOPUS:85058313835
T3 - UbiComp/ISWC 2018 - Adjunct Proceedings of the 2018 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2018 ACM International Symposium on Wearable Computers
SP - 559
EP - 564
BT - UbiComp/ISWC 2018 - Adjunct Proceedings of the 2018 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2018 ACM International Symposium on Wearable Computers
PB - Association for Computing Machinery, Inc
T2 - 2018 Joint ACM International Conference on Pervasive and Ubiquitous Computing, UbiComp 2018 and 2018 ACM International Symposium on Wearable Computers, ISWC 2018
Y2 - 8 October 2018 through 12 October 2018
ER -