TY - GEN
T1 - Cognitive rhythms
T2 - 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing, UbiComp 2016
AU - Abdullah, Saeed
AU - Murnane, Elizabeth L.
AU - Matthews, Mark
AU - Kay, Matthew
AU - Kientz, Julie A.
AU - Gay, Geri
AU - Choudhury, Tanzeem
N1 - Funding Information:
This work was supported by a grant from the Robert Wood Johnson Foundation and the Health Data Exploration Project, the Intel Science&Technology Center for Pervasive Computing, Semiconductor Research Corporation, and the National Science Foundation (DGE-1144153 and IIS-1344613).
PY - 2016/9/12
Y1 - 2016/9/12
N2 - Throughout the day, our alertness levels change and our cognitive performance fluctuates. The creation of technology that can adapt to such variations requires reliable measurement with ecological validity. Our study is the first to collect alertness data in the wild using the clinically validated Psychomotor Vigilance Test. With 20 participants over 40 days, we find that alertness can oscillate approximately 30% depending on time and body clock type and that Daylight Savings Time, hours slept, and stimulant intake can influence alertness as well. Based on these findings, we develop novel methods for unobtrusively and continuously assessing alertness. In estimating response time, our model achieves a root-mean-square error of 80:64 milliseconds, which is significantly lower than the 500ms threshold used as a standard indicator of impaired cognitive ability. Finally, we discuss how such real-time detection of alertness is a key first step towards developing systems that are sensitive to our biological variations.
AB - Throughout the day, our alertness levels change and our cognitive performance fluctuates. The creation of technology that can adapt to such variations requires reliable measurement with ecological validity. Our study is the first to collect alertness data in the wild using the clinically validated Psychomotor Vigilance Test. With 20 participants over 40 days, we find that alertness can oscillate approximately 30% depending on time and body clock type and that Daylight Savings Time, hours slept, and stimulant intake can influence alertness as well. Based on these findings, we develop novel methods for unobtrusively and continuously assessing alertness. In estimating response time, our model achieves a root-mean-square error of 80:64 milliseconds, which is significantly lower than the 500ms threshold used as a standard indicator of impaired cognitive ability. Finally, we discuss how such real-time detection of alertness is a key first step towards developing systems that are sensitive to our biological variations.
UR - http://www.scopus.com/inward/record.url?scp=84991516822&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84991516822&partnerID=8YFLogxK
U2 - 10.1145/2971648.2971712
DO - 10.1145/2971648.2971712
M3 - Conference contribution
AN - SCOPUS:84991516822
T3 - UbiComp 2016 - Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing
SP - 178
EP - 189
BT - UbiComp 2016 - Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing
PB - Association for Computing Machinery, Inc
Y2 - 12 September 2016 through 16 September 2016
ER -