Quantified Self

A movement that aims to incorporate technology into data acquisition, taking into account every aspect of daily life. The data inputs range from the amount of food consumed, quality of surrounding air to physical states such as mood, arousal, blood oxygen levels, and mental and physical health.
Technology Life Cycle

Technology Life Cycle


Marked by a rapid increase in technology adoption and market expansion. Innovations are refined, production costs decrease, and the technology gains widespread acceptance and use.

Technology Readiness Level (TRL)

Technology Readiness Level (TRL)

Fully Operative

Technology is operative and demonstrates considerable market competition among manufacturing industries.

Technology Diffusion

Technology Diffusion

Early Majority

Adopts technologies once they are proven by Early Adopters. They prefer technologies that are well established and reliable.

Quantified Self

Quantified self is a movement that encourages individuals to use self-tracking tools to gather data on their physical and mental health, behavior, and performance. The goal is to gain insights into one's own patterns and to optimize one's daily routine and overall well-being.

The technology used for quantified self can include various types of wearables, such as fitness trackers, smartwatches, implants, and health apps that collect data on a wide range of parameters, including sleep, exercise, heart rate, glucose levels and nutrition. Other tools used include self-reported surveys, mood trackers, and goal-setting apps.

The data collected can be analyzed and visualized in different ways, allowing individuals to track changes over time and make informed decisions about their health and lifestyle. By using this approach, individuals can identify patterns in their behavior to help them make positive changes in their lives, such as getting more exercise, improving sleep quality, adjusting their diet or even better time or finance management.

Currently, there is a rising concern regarding the use and manipulation of the data collected. Popular cases related to data leaks have led consumers to an ethical dilemma between efficiency and privacy. Although privacy and accountability efforts are required, both from companies and governments, this movement also brings new ways to tracking methods, which could subsequently help in manifold industries, such as healthcare, finance, and many more.

More than providing registers, quantified-self platforms are being remodeled to give support to consumers while openly considering diversity and particularities (for example, senior consumers, women's health, people with diabetes, and child support).

Future Perspectives

Digital assistants could work as a catalyst for all tracking apps by analyzing and processing all collected data and offering therapeutic and life coach-style advice regarding health, fitness, dating, professional tips, and education. However, as these systems become more pervasive, it becomes of utmost importance for companies to ensure the privacy of user data. Integration with blockchain systems could not only enforce security in data transactions but also offer connections with reward programs and, finally, the tokenization of behavioral data.

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Better performance through self-quantification
Our mood states, caloric intake, physical activity and even our skin conductance; in our modern digital society it is possible to track every single bit of our daily lives with various types of tracking devices. Using this data, our health and personal development can be analyzed and modified to improve our functioning. It leads to a self expressed in numbers, a so-called “quantified self”. This course will enable students to critically examine the current developments in the digital-data industry and separate the truth from the hype of these developments. In this course, students will examine the claims of the information revolution with a focus on the quantified self – for instance driven by wearables or Facebook usage. Students will survey the ongoing developments in this area based on news reports and peer-reviewed literature. Through brief written reports and in-class presentations, students will reveal their findings in terms of scientific validity and societal implications. For each seminar, students will choose a technology and connect with the guiding theme of the seminar.
All your industrious tracking of periods, sex, and basal body temperature is also valuable as a database.
How long did I sleep? How many steps did I take? How many calories did I eat? These questions were the mainstay of the Quantified Self movement. While getting the data on your life was alluring —…
What happens when people turn their everyday experience into data: an introduction to the essential ideas and key challenges of self-tracking.
Technology and health: Measuring your everyday activities can help improve your quality of life, according to aficionados of “self-tracking”
Tracking and data can help you make improvements. Learn how the concepts from the Quantified Self movement can be applied to your life.
It is now widely accepted that having real-time data on what we eat, how much we exercise and how we sleep may be able to help us manage our health and wellbeing. We've become accustomed to using digital technology to measure everything from steps and calories to heart rate and body fat. There's even a movement that has grown up around this life-logging trend - the Quantified Self movement - and a burgeoning industry in wearable tech to do the monitoring.
The recent proliferation of self-tracking technologies has allowed individuals to generate significant quantities of data about their lifestyle. These data can be used to support health interventions and monitor outcomes. However, these data are often stored and processed by vendors who have commercial motivations, and thus, they may not be treated with the sensitivity with which other medical data are treated. As sensors and apps that enable self-tracking continue to become more sophisticated, the privacy implications become more severe in turn. However, methods for systematically identifying privacy issues in such apps are currently lacking.
Our results demonstrate that prior research has focused on 3 stakeholders with respect to self-tracking and the quantified self, namely end users, patients and people with illnesses, and health care professionals and caregivers. We used these stakeholder groups to cluster the research themes of the reviewed studies. We identified 11 research themes. There are 6 themes under the end-user cluster: user motivation and goal setting, usage and effects of self-tracking, continuance intention and long-term usage, management of personal data, rejection and discontinuance, and user characteristics. The patient and people with illnesses cluster contains three themes: usage experience of patients and people with illnesses, management of patient-generated data, and advantages and disadvantages in the clinical context. The health care professional and caregiver cluster contains two themes: collaboration among patients, health care professionals, and caregivers, and changes in the roles of patients and professionals. Moreover, we classified the future research suggestions given in the literature into 5 directions in terms of research designs and research topics. Finally, based on our reflections on the observations from the review, we suggest four future research directions: (1) users’ cognitions and emotions related to processing and interpreting the information produced by tracking devices and apps; (2) the dark side of self-tracking (eg, its adverse psychosocial consequences); (3) self-tracking as a societal phenomenon; and (4) systemic impacts of self-tracking on health care and the actors involved. to also use our site. To restore access and understand how to better interact with our site to avoid this in the future, please have your system administrator contact info@ncbi.nlm.nih.gov.

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