Σύγκριση μεθόδων

	Συλλογή Διαχρονικών Δεδομένων Αισθητήρων	Μέθοδος Δειγματοληψίας Εμπειρίας μέσω Κινητού
Πεδίο	Μεθοδολογία Επισκοπήσεων	Μεθοδολογία Επισκοπήσεων
Οικογένεια	Process / pipeline	Process / pipeline
Έτος προέλευσης	1990s–2000s (accelerated with IoT and wearable devices from ~2010)	1983–1987
Δημιουργός	Emerging from ambulatory assessment and wearable technology research communities	Mihaly Csikszentmihalyi & Reed Larson
Τύπος	Longitudinal quantitative/mixed data collection technique	Intensive longitudinal data collection technique
Θεμελιώδης πηγή	Lanza, S. T., Collins, L. M., Lemmon, D. R., & Schafer, J. L. (2005). PROC LCA: A SAS procedure for latent class analysis. Structural Equation Modeling, 14(4), 671–694. [For longitudinal intensive repeated-measures designs context, see also: Shiffman, S., Stone, A. A., & Hufford, M. R. (2008). Ecological momentary assessment. Annual Review of Clinical Psychology, 4, 1–32.]	Csikszentmihalyi, M., & Larson, R. (1987). Validity and reliability of the Experience-Sampling Method. Journal of Nervous and Mental Disease, 175(9), 526–536.
Εναλλακτικές ονομασίες	long-term sensor monitoring, longitudinal sensing, continuous sensor logging, repeated-measures sensor collection	ESM, ecological momentary assessment, EMA, daily diary via mobile
Συναφείς	3	4
Σύνοψη	Longitudinal sensor data collection deploys physical or digital sensors to record phenomena continuously or at regular intervals across an extended study period — days, months, or years. Unlike one-shot measurement, the repeated temporal structure captures change, trajectory, and variability in outcomes such as physical activity, environmental exposure, sleep, or physiological state. The approach combines the ecological validity of real-world sensing with the analytical power of longitudinal design.	The Mobile Experience Sampling Method (ESM) collects repeated, time-stamped self-reports from participants in their natural environment using a smartphone app. By signaling participants multiple times per day over days or weeks, researchers capture psychological states, behaviors, and contexts as they occur — eliminating retrospective bias and revealing within-person dynamics that single-session surveys cannot detect.