S. S. Intille, "Technological innovations enabling automatic, context-sensitive ecological momentary assessment," in The Science of Real-Time Data Capture: Self-Report in Health Research, A. A. Stone, S. Shiffman, A. A.A., and L. Nebeling, Eds.: Oxford University Press, 2005. In Press.


Emerging technological innovations will create new opportunities for researchers interested in using real-time data collection for health research. This chapter reviews some of the technologies that will change the type and quality of health data that can be collected from free-living subjects in natural environments such as homes, workplaces, and communities. The technologies can be leveraged to support automatic, context-sensitive ecological momentary assessment, where mobile computers such as PDAs or phones continuously collect and analyze data to trigger real-time, context-sensitive, and highly tailored self-report. Four different enabling technologies for real-time, self-report data collection are described and compared: paper, current electronic mobile computing devices, current context-sensitive computing devices, and future context-sensitive computing devices (ten years from now).


Context-sensitive ecological momentary assessment, context-aware experience sampling, context-aware computing, longitudinal assessment, mobile computing.


Dr. Intille is supported, in part, by National Science Foundation ITR grant #0112900 and the House_n Consortium. He thanks Jennifer Beaudin for comments on a draft of this paper. Emmanuel Munguia Tapia designed the wireless sensors shown in Figure 2. John Rondoni implemented the first version of the MIT PDA software for CS-EMA.