Experience Sampling Method (ESM)

The Experience Sampling Method (ESM) is a research procedure for studying what people do, feel, and think during their daily lives, It consists in asking individuals to provide systematic self-reports at random occasions during the waking hours of a normal week. Sets of these self-reports from a sample of individuals create an archival file of daily experience.

Larson, Reed, and Mihaly Csikszentmihalyi. “The experience sampling method.” Flow and the foundations of positive psychology. Springer, Dordrecht, 2014. 21-34.


Experiencer is the outcome of an endeavor to create an ESM solution that benefits both researchers and study participants while leveraging the physiological sensors of commodity-level wearable devices.

source: IJERPH | Free Full-Text | Assessing the Influence of Physical Activity Upon the Experience Sampling Response Rate on Wrist-Worn Devices (mdpi.com)
Presenting Experiencer at EAI Pervasive Health Conference, Thessaloniki, Greece, 2022.

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TensorFlow.js runs seamlessly on Experiencer, on the smartwatch, to enable on-device real-time personalization.

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Project home on GitHub

Key Publications

Khanshan, Alireza, Pieter Van Gorp, and Panos Markopoulos. “Experiencer: An Open-Source Context-Sensitive Wearable Experience Sampling Tool.” International Conference on Pervasive Computing Technologies for Healthcare. Cham: Springer Nature Switzerland, 2022.

Khanshan, Alireza, et al. “Assessing the influence of physical activity upon the experience sampling response rate on wrist-worn devices.” International Journal of Environmental Research and Public Health 18.20 (2021): 10593.