Joyce Ho
ABSTRACT
The potential for sensor-enabled mobile devices to proactively present information when and where users need it ranks among the greatest promises of ubiquitous computing. Unfortunately, mobile phones, PDAs, and other computing devices that compete for the user's attention can contribute to interruption irritability and feelings of information overload. Designers of mobile computing interfaces, therefore, require strategies for minimizing the perceived interruption burden of proactively delivered messages. In this work, a context-aware mobile computing device was developed that automatically detects postural and ambulatory activity transitions in real time using wireless accelerometers. This device was used to experimentally measure the receptivity to interruptions delivered at activity transitions relative to those delivered at random times. Messages delivered at activity transitions were found to be better received, thereby suggesting a viable strategy for context-aware message delivery in sensor-enabled mobile computing devices.
- E. Arroyo, T. Selker, and A. Stouffs. Interruptions as multimodal outputs: which are the less disruptive? In Proceedings of the 4th IEEE International Conference on Multimodal Interfaces, pages 479--482. IEEE Press, 2002. Google Scholar
Digital Library
- B.P. Bailey, J.A. Konstan, and J.V. Carlis. Measuring the effects of interruptions on task performance in the user interface. In IEEE Conference on Systems, Man, and Cybernetics 2000 (SMC 2000), pages 757--762. IEEE Press, 2000.Google ScholarCross Ref
- L. Bao and S.S. Intille. Activity recognition from user-annotated acceleration data. In A. Ferscha and F. Mattern, editors, Proceedings of PERVASIVE 2004, volume LNCS 3001, pages 1--17. Springer-Verlag, Berlin Heidelberg, 2004.Google ScholarCross Ref
- E. Cutrell, M. Czerwinski, and E. Horvitz. Effects of instant messaging interruptions on computing tasks. In Extended Abstracts of CHI 2000, Human Factors in Computing Systems. ACM Press, 2000. Google ScholarDigital Library
- E. Cutrell, M. Czerwinski, and E. Horvitz. Notification, disruption and memory: Effects of messaging interruptions on memory and performance. In M. Hirose, editor, Human-Computer Interaction-Interact '01, pages 263--269. IOS Press, 2001.Google Scholar
- J. Fogarty, S.E. Hudson, and J. Lai. Examining the robustness of sensor-based statistical models of human interruptibility. In Proceedings of the 2004 Conference on Human Factors in Computing Systems. ACM Press, New York, NY, 2004. Google ScholarDigital Library
- D. Garlan, D. Siewiorek, A. Smailagic, and P. Steenkiste. Project Aura: toward distraction-free pervasive computing. IEEE Pervasive Computing, April-June:22-31, 2002. Google ScholarDigital Library
- T. Gillie and D. Broadbent. What makes interruptions disruptive? A study of length, similarity, and complexity. Psychological Research, 50(4):243--50, 1989.Google ScholarCross Ref
- S.M. Hess and M. Detweiler. Training to reduce the disruptive effects of interruptions. In Proceedings of the Human Factors and Ergonomics Society 38th Annual Meeting, volume 2, pages 1173--1177. Human Factors & Ergonomics Society, Santa Monica, CA, 1994.Google ScholarCross Ref
- K. Hinckley and E. Horvitz. Toward more sensitive mobile phones. In Proceedings of the 14th annual ACM Symposium on User Interface Software and Technology, pages 191--192. ACM Press, 2001. Google ScholarDigital Library
- J. Ho. Interruptions: Using Activity Transitions to Trigger Proactive Messages. M.Eng. Thesis, Massachusetts Institute of Technology, 2004.Google Scholar
- E. Horvitz and J. Apacible. Learning and reasoning about interruption. In Proceedings of the 5th International Conference on Multimodal Interfaces, pages 20--27. ACM Press, New York, NY, 2003. Google ScholarDigital Library
- E. Horvitz, A. Jacobs, and D. Hovel. Attention-sensitive alerting. In K.B. Laskey and H. Prade, editors, UAI '99: Proceedings of the Fifteenth Conference on Uncertainty in Artificial Intelligence, pages 305--513. Morgan Kaufmann, 1999. Google ScholarDigital Library
- E. Horvitz, C.M. Kadie, T. Paek, and D. Hovel. Models of attention in computing and communications: from principles to applications. Communications of the ACM, 46(3):52--59, 2003. Google ScholarDigital Library
- E. Horvitz, P. Koch, C. Kadie, and A. Jacobs. Coordinates: probabilistic forecasting of presence and availability. In Proceedings of the 18th Annual Conference on Uncertainty in Artificial Intelligence (UAI-02), pages 224--233. Morgan Kaufmann Publishers, 2002. Google ScholarDigital Library
- J.M. Hudson, J. Christensen, W.A. Kellogg, and T. Erickson. 'I'd be overwhelmed, but it's just one more thing to do:' availability and interruption in research management. In Proceedings of the Confererence on Human Factors in Computing Systems. ACM Press, 2002. Google ScholarDigital Library
- S.E. Hudson, J. Fogarty, C.G. Atkeson, D. Avrahami, J. Forlizzi, S. Kiesler, J.C. Lee, and J. Yang. Predicting human interruptability with sensors: a Wizard of Oz feasibility study. In Proceedings of the Conference on Human Factors and Computing, pages 257--264. ACM Press, New York, NY, 2003. Google ScholarDigital Library
- N. Kern and B. Schiele. Context-aware notification for wearable computing. In Proceedings of the 7th International Symposium on Wearable Computing, pages 223--230. IEEE Press, 2003. Google ScholarDigital Library
- N. Kern, B. Schiele, and A. Schmidt. Multi-sensor activity context detection for wearable computing. In European Symposium on Ambient Intelligence (EUSAI), volume LNCS 2875, pages 220--232. Springer-Verlag, Heidelberg, 2003.Google ScholarCross Ref
- K.K. Liu. A Personal, Mobile System for Understanding Stress and Interruptions. S.M. Thesis, Massachusetts Institute of Technology, 2004.Google Scholar
- P. Lukowicz, H. Junker, M. Staeger, T. von Bueren, and G. Troester. WearNET: a distributed multi-sensor system for context aware wearables. In Proceedings of the 4th International Conference on Ubiquitous Computing, pages 361--370. Springer, 2002. Google ScholarDigital Library
- C.E. McCarthy and M.E. Pollack. A plan-based personalized cognitive orthotic. In M. Ghallab, J. Hertzberg, and P. Traverso, editors, Proceedings of the Sixth International Conference on Artificial Intelligence Planning Systems, pages 243--252. AAAI Press, 2002.Google Scholar
- D.S. McCrickard and C.M. Chewar. Attuning notification design to user goals and attention costs. Communications of the ACM, 45(3):67--72, 2003. Google ScholarDigital Library
- D.C. McFarlane. Coordinating the interruption of people in human-computer interaction. In A. Sasse and C. Johnson, editors, Human-Computer Interaction -INTERACT'99, pages 295--303. IOS Press, 1999.Google Scholar
- Y. Miyata and D.A. Norman. Psychological issues in support of multiple activities. In D.A. Norman and S.W. Draper, editors, User-Centered System Design, pages 265--284. Lawrence Erlbaum Associates, Hillsdale, NJ, 1986.Google Scholar
- D.P. Siewiorek, A. Smailagic, J. Furukawa, A. Krause, N. Moraveji, K. Reiger, J. Shaffer, and F.L. Wong. SenSay: a context-aware mobile phone. In Proceedings of the 7th IEEE International Symposium on Wearable Computers, pages 248--249. IEEE Press, 2003. Google ScholarDigital Library
- C. Speier, J.S. Valacich, and I. Vessey. The effects of task interruption and information presentation on individual decision making. In Proceedings of the Eighteenth International Conference on Information Systems, pages 21--36. Association for Information Systems, 1997. Google ScholarDigital Library
- A.A. Stone and S. Shiffman. Capturing momentary, self-report data: a proposal for reporting guidelines. Annals of Behavioral Medicine, 24(3):236--243, 2002.Google ScholarCross Ref
- N.A. Storch. Does the user interface make interruptions disruptive? A study of interface style and form of interruption. UCRL-JC-108993, Lawrence Livermore National Laboratory, 1992.Google Scholar
- E.M. Tapia, N. Marmasse, S.S. Intille, and K. Larson. MITes: Wireless portable sensors for studying behavior. In Proceedings of Extended Abstracts Ubicomp 2004: Ubiquitous Computing. 2004.Google Scholar
- M. van Dantzich, D. Robbins, E. Horvitz, and M. Czerwinski. Scope: providing awareness of multiple notifications at a glance. In Proceedings of AVI 2002, ACM Conference on Advanced Visual Interfaces.ACM Press, 2002. Google ScholarDigital Library
- R. van Solingen, E. Berghout, and F. van Latum. Interrupts: just a minute never is. IEEE Software, 15(5):97--103, 1998. Google ScholarDigital Library
Index Terms
- Using context-aware computing to reduce the perceived burden of interruptions from mobile devices
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