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Quantified self

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The Quantified Self[1] is a movement to incorporate technology into data acquisition on aspects of a person's daily life in terms of inputs (e.g. food consumed, quality of surrounding air), states (e.g. mood, arousal, blood oxygen levels), and performance (mental and physical). Such self-monitoring and self-sensing, which combines wearable sensors (EEG, ECG, video, etc.) and wearable computing, is also known as lifelogging. Other names for using self-tracking data to improve daily functioning[2] are “self-tracking”, "auto-analytics", “body hacking” and “self-quantifying”.[3]

History

The history of self-tracking using wearable sensors combined with wearable computing and wireless communication, dates back many years, and appeared, in the form of sousveillance (wearable physiological sensors, etc.) in the 1970s.[4][5][6][7] The term "quantified self" appears to have been proposed by Wired Magazine editors Gary Wolf[8] and Kevin Kelly[9] in 2007[10] as "a collaboration of users and tool makers who share an interest in self knowledge through self-tracking." In 2010, Wolf spoke about the movement at TED,[11] and in May 2011 the first international conference was held in Mountain View, California.[12]

Today the global community has over a hundred groups in 31 countries around the world.[13]

Methodologies

The primary methodology of self-quantification is data collection, followed by visualization, cross-referencing and the discovery of correlations.[14]

Life-tracking information from various applications can be difficult to integrate and find meaning. Many websites can help by synergizing, visualizing, and analyzing the cacophony data to identify correlations between specific input factors and treatments (independent variables) and mood outcomes (dependent variables). The Pearson product-moment correlation coefficient derived from an XY scatterplot of input behaviours and output states can quantify the effectiveness of various treatments.

The human mind is not powerful enough to keep track of the countless factors that go into producing an emotional state. Timeline graphical analysis can help to identify potential confounding uncontrolled variables that may be contaminating the results of an experiment.

Fine-grained, personalized minimum effective dosages of drugs can be established. Degrees of drug tolerance and withdrawal symptoms can be quantified. By integrating the area under the mood curves, true cost-benefit analyses weighing therapeutic benefits against adverse effects can be performed.

Critiques

As a form of "somatic surveillance," some scholars have drawn attention to the potential of self-quantification to strip social context from data and possibly aggravate social inequalities.[15] For instance, dominant modes of self-quantification tend toward highly individualized forms of commodification that may mask the ways that such data might be used to discriminate against individuals based on lifestyle (e.g., by insurance companies or employers). Self-quantification may cultivate a view of health and environmental problems as discrete and individual, thereby requiring individual-based interventions rather than collective action.

Devices and Services

Notable self-quantification tools are listed below. Numerous other hardware devices and software are available,[16] thanks to recent advances and cost reductions in sensor technology, mobile connectivity, and battery life.

Activity monitors

Sleep monitors


Other

See also

References

  1. ^ Gary, Wolf. "QS & The Macroscope". Retrieved 10 February 2013.
  2. ^ Dorminey, Bruce (2012-05-31). "Tic-Toc-Trac: New Watch Gadget Measures Time Perception For The Self-Quantifying". Forbes.
  3. ^ "Counting every moment". The Economist. Mar 3rd 2012. {{cite web}}: Check date values in: |date= (help)
  4. ^ Intelligent Image Processing, Steve Mann, John Wiley and Sons, 2001
  5. ^ Mann, S. (1998). "Humanistic computing: "WearComp" as a new framework and application for intelligent signal processing" (PDF). Proceedings of the IEEE. 86 (11): 2123–2151. doi:10.1109/5.726784. {{cite journal}}: Unknown parameter |month= ignored (help)
  6. ^ Persuasive Technology and Digital Design for Behaviour Change, Dan Lockton, Brunel University - Brunel Design; University of Warwick - WMG, August 7, 2012
  7. ^ WEB 2.0, VIGILÂNCIA E MONITORAMENTO: ENTRE FUNÇÕES PÓSMASSIVAS E CLASSIFICAÇÃO SOCIAL, Tarcízio Silva, Universidade Federal da Bahia
  8. ^ Singer, Emily. "The Measured Life". MIT. Retrieved 2011-07-05.
  9. ^ Wolf, Gary. "Quantified Self". Gary Wolf. Archived from the original on 2012-03-26. Retrieved 2012-03-26.
  10. ^ "Quantified Self Blog, oldest entries". Archived from the original on 2012-03-26. Retrieved 2012-03-26.
  11. ^ Wolf, Gary. "The quantified self". TED (conference). Retrieved 2012-03-26.
  12. ^ "Invasion of the body hackers". Financial Times. 2011-06-10. Archived from the original on 2012-03-26.
  13. ^ http://quantified-self.meetup.com/
  14. ^ Hesse, Monica (September 9, 2008). "Bytes of Life". Washington Post. Retrieved 2012-03-26.
  15. ^ Monahan, T. and Wall, T. (2007). Somatic Surveillance: Corporeal Control through Information Networks. Surveillance & Society, 4 (3), 154-173.
  16. ^ "The Guide to Self-Tracking Tools". Quantified Self. Retrieved 2012-03-27.
  17. ^ a b "MyBasis".
  18. ^ Panzarino, Matthew. "Lark expands from a sleep monitor to a full on coaching service". The Next Web. Retrieved 2012-04-20.
  19. ^ Pachal, Pete. "Jawbone Opens 'UP' Platform to Other Apps". Mashable. Retrieved 2013-04-30.
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