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Those who do things others are unable to perform (to uplift the humankind) are considered great people. Those who can not are considered little.
Wearables and the type of health data they collect
Sep 17, 2014
In this article I would like to draw a parallel between automobiles and human beings to make a point I seem to have understood well. This comparison may sound a little insensitive to some. While humans are way too superior biological machines compared to automobiles, we will agree that even automobiles have a notion of health.
We normally look at three types of data when we want to assess the quality and performance of an automobile. First we look at the make, model and the year of manufacture. This data provides information about the engineering, quality of materials and construction of the automobile. Next we look at how many times a vehicle has been serviced/ repaired, by whom and for what reasons. This data lets us understand how the machine has been maintained and the type of part replacements/ reconstructions it has undergone. Third we look at operational data on the vehicle dashboard. This data is called the ‘activity data’ - what is the engine rev at the moment, how fast is the vehicle traveling, what is its current milage, what is the engine temperature, etc.,
We can draw parallels for humans for each of the above type. The DNA / genome data is the first type. The records of clinical/hospital visits, medication taken and surgical interventions are the second type. The third type ‘activity data’ is about heart rate, pulse, number of steps taken, and other operational data. The wearables of today measure this activity data. In an automobile these gadgets and dashboards are in-built. In humans we are trying to add the gadgetry and dashboard in the form of wearables.
After several years of continuous improvement and innovations, the technology in cars that provide activity data provides for accuracy of measurements. The vehicle’s wearables have become dependable to the extent that in premium vehicle segments, this data is used by service stations to determine the best service strategy. In contrast, wearables are at a very nascent stage. There is no guarantee yet that the data they provide is close to reality. It will therefore take time for physicians and surgeons to rely on activity data in diagnosis and prognosis.
However, with volume and application of statistical maths, we can still draw some useful insights from the data, if not at individual level, probably at a community level. We are in baby years of wearables.