Since the term was coined in 2007, Quantified Self (QS) has become more and more popular. It is based on quantifying elements that have an impact on our day-to-day activity in order to analyze them and enhance our quality of life. If we keep a record of what we eat, how many hours we sleep and our physical exercise we may be able to identify and change trends in our behavior to improve our well-being.
The concept itself is not new, since there are devices that measure our physical activity (heart rate, calories, distance, etc.) when we practice a sport. However, the technological advances seen in recent years (microsensors, smartphones with specific QS apps) are greatly facilitating its expansion.
The types of data that can be collected include the distance we walk and how long it takes, the intensity of the exercise, the hours of sleep, our calorie intake, the calories we burn, the types of nutrients in the food we eat (fats, hydrates, proteins, vitamins, etc.), our habits (tobacco and alcohol consumption), the medicines we take often, the levels of blood oxygen, the hours of sunlight, climatological data, the quality of the air we breathe, the environmental noise, etc.
As can be seen, this list can be very long and could include any aspect that has an impact on our lives. There are more and more types of sensors that can capture new information.
In addition to this data, that we might call objective, it is very important to complete the information with other more emotional data such as our mood, feelings, state of mind, situations of stress, etc.
The captures of data that offer the best results are those that are done passively, i.e. when the sensor is capable of collecting all the information without our intervention, since it is done in a more precise and methodological way. Today, this is not possible for certain metrics, but current medical advances could in the not too distant future enable the development of chip implants to expand the range of characteristics to be measured.
One of the results of the success of QS is the large number of applications and sensors from different manufacturers that coexist. To a certain extent, this makes it difficult to correlate the information from different sources, as the measurement criteria and scales are not standardized among the competitors. However, other technological trends such as Big Data can mitigate this problem and provide a great deal of added value in the processing and analysis of the data, revealing correlations among the information, and even cross-referencing them with other unstructured sources.
The search for a better quality of life is something desirable and Quantified Self is on the right path. QS can not only show us how to enhance our own well-being, but this information can also be used as a database for other people in the search for correlations that enrich even further the conclusions of the original information.
However, we should not forget that the storage and shared use of information is always a controversial issue, especially if it is not done in a rigorous and safe way, in accordance with current legislation. As we can imagine, the type of information collected in QS should be treated with the utmost diligence, as it consists of extremely sensitive data that can tell a lot about us.
Igor Delgado
Manager in the Corporate Data Warehouse, BBVA
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