Most of us own at least one smartphone that can count our steps every day. Increasingly, some people also wear wristbands, watches and other devices that collect fitness-related data such as heart rate. But how does the science behind this technology work? Is the information they provide us any use?

The use of smart watches has increased in recent years. Among other things, they are capable of measuring heart rate and, from this, we can estimate a person’s fitness level . But in reality this cannot be considered a direct measure of physical condition. In fact, the use of devices to measure it is still uncommon and this practice is not widespread among the population, although some devices have functionalities to estimate it.

You may have seen the route of a run or bike ride recorded by a smartwatch or phone and shared on social media. How do they measure their owners’ movement? One answer is that they rely on GPS (“global positioning system”), but that technology is less common when we want to know how much a person moves.

In reality, GPS devices provide information obtained from connections with satellites located in Earth’s orbit. They are precise, and increasingly so, but they only estimate a person’s movement and, in addition, they need to be in places that allow the device to connect with the satellites.

This is why it is difficult to take measurements indoors or even on cloudy days . This makes it difficult to use in certain areas where weather conditions make it difficult to practice outdoor activities, although there are alternatives.

The popularity of accelerometers

In fact, to measure movement we can use other devices called “accelerometers” , which record the changes in speed that occur in the device.

Accelerometers have come a long way in recent years, to the point that all smartphones now have one. There are different formats that include “inclinometers” and even displays to view information.

A recent study highlights the need to improve methods for validating information from these devices. However, they are widely used in research to analyze movement behaviors, which integrate physical activity, sedentary behavior, and sleep .

These three components allow us to understand people’s movement from a more global point of view. It is a very standard type of assessment for studying the child population, since the recommendations are established in the continuum of the 24 hours of a day, dividing it between sleep and wakefulness. Within the latter are the recommended times for performing light and moderate to vigorous intensity physical activity, avoiding sedentary lifestyles exceeding a maximum time.

Many advances, but technology is lacking

On the other hand, if we want to measure certain specific movements, we can find technology that provides information on the amount of force a person can generate with their legs (dynamometers), or the speed with which we hit a ball in different sports, for which we can use sensors such as radars.

In addition, we have technology to simulate human movement from videos recorded of people , with which we can identify movement patterns (to predict and diagnose diseases). These cameras are specific and can be connected to each other to generate the human figure through biomechanical techniques and methods:

However, when it comes to indicators related to physical or bodily health, especially when applied in childhood and adolescence, there is little valid, reliable technology with adequate usability.

The world of sensors has made great strides in recent years and they have been incorporated into many facets of our lives. Even so, there is still a great deal of room for improvement in the data collection process. This would help physical-sports educators to capture information on physical condition, since these are the professionals who have the necessary training to evaluate it and determine the appropriate activities and intensities.

All of the above technology examples record a significant amount of data, stored on the device (local) or on a remote server (the cloud), although the sheer amount of information to be managed can be a problem. However, data science is being applied to the study of human movement and, more specifically, to improving sports training , allowing for the efficient use of that information.

In the near future, thanks to the use of data science and artificial intelligence, it will be possible to carry out analyses of the information collected to propose improvements in physical condition in a personalized way, just as it already happens in sports training and injury prevention .

Author Bios: Javier Brazo-Sayavera is Professor of Physical Education and Sports at Pablo de Olavide University, Arkaitz Larrinaga Undabarrena is Professor and Researcher in Human Motility and Promotion of Physical Activity at the University of Deusto, Francisco A. Gomez Vela is Full Professor, Department of Computer Languages ​​and Systems and Garazi Angle Garay is a Research technician in the area of ​​physical activity in childhood and adolescence both at Pablo de Olavide University