QuantifyMe: An automated single-case experimental design platform

Akane Sano, Sara Taylor, Craig Ferguson, Akshay Mohan, Rosalind W. Picard

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations


We designed, developed, and evaluated a novel system, QuantifyMe, for novice self-experimenters to conduct proper-methodology single-case self-experiments in an automated and scientific manner using their smartphones. In this work we evaluate its use with four different kinds of personalized investigations, examining how variables such as sleep duration and regularity, activity, and leisure time affect personal happiness, stress, productivity, and sleep efficiency. We describe lessons learned developing the system, and recommendations for its improvement, as well as its potential for enabling personalized insights to be scientifically evaluated in many individuals.

Original languageEnglish (US)
Title of host publicationWireless Mobile Communication and Healthcare - 7th International Conference, MobiHealth 2017, Proceedings
EditorsAmir M. Rahmani, Nima TaheriNejad, Paolo Perego
Number of pages8
ISBN (Print)9783319985503
StatePublished - 2018
Event7th International Conference on Wireless Mobile Communication and Healthcare, MobiHealth 2017 - Vienna, Austria
Duration: Nov 14 2017Nov 15 2017

Publication series

NameLecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST
ISSN (Print)1867-8211


Conference7th International Conference on Wireless Mobile Communication and Healthcare, MobiHealth 2017


  • Mobile health
  • Self-experiment
  • Self-tracking
  • Single-case experimental design

ASJC Scopus subject areas

  • Computer Networks and Communications


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