TY - GEN
T1 - Towards circadian computing
T2 - 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing, UbiComp 2014
AU - Abdullah, Saeed
AU - Matthews, Mark
AU - Murnane, Elizabeth L.
AU - Gay, Geri
AU - Choudhury, Tanzeem
N1 - Publisher Copyright:
Copyright © 2014 by the Association for Computing Machinery, Inc. (ACM).
PY - 2014
Y1 - 2014
N2 - We often think of ourselves as individuals with steady capabilities. However, converging strands of research indicate that this is not the case. Our biochemistry varies significantly over the course of a 24 hour period. Consequently our levels of alertness, productivity, physical activity, and even sensitivity to pain fluctuate throughout the day. This offers a considerable opportunity for the UbiComp community to identify novel measurements and interventions that can leverage these daily variations. To illustrate this potential, we present results from an empirical study with 9 participants over 97 days investigating whether such variations manifest in low-level smartphone use, focusing on daily rhythms related to sleep. Our findings demonstrate that phone usage patterns can be used to detect and predict individual daily variations indicative of temporal preference, sleep duration, and deprivation. We also identify opportunities and challenges for measuring and enhancing well-being using these simple and effective markers of circadian rhythms.
AB - We often think of ourselves as individuals with steady capabilities. However, converging strands of research indicate that this is not the case. Our biochemistry varies significantly over the course of a 24 hour period. Consequently our levels of alertness, productivity, physical activity, and even sensitivity to pain fluctuate throughout the day. This offers a considerable opportunity for the UbiComp community to identify novel measurements and interventions that can leverage these daily variations. To illustrate this potential, we present results from an empirical study with 9 participants over 97 days investigating whether such variations manifest in low-level smartphone use, focusing on daily rhythms related to sleep. Our findings demonstrate that phone usage patterns can be used to detect and predict individual daily variations indicative of temporal preference, sleep duration, and deprivation. We also identify opportunities and challenges for measuring and enhancing well-being using these simple and effective markers of circadian rhythms.
UR - http://www.scopus.com/inward/record.url?scp=84908599029&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84908599029&partnerID=8YFLogxK
U2 - 10.1145/2632048.2632100
DO - 10.1145/2632048.2632100
M3 - Conference contribution
AN - SCOPUS:84908599029
T3 - UbiComp 2014 - Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing
SP - 673
EP - 684
BT - UbiComp 2014 - Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing
PB - Association for Computing Machinery, Inc
Y2 - 13 September 2014 through 17 September 2014
ER -