Week 5 Limitations with Wearables and Sensors Go back ◀

Wearables and sensors can be great, except when they aren’t. In this module we are going to look at some of the challenges of sensors and wearables. In some cases, we will see how wearables and sensors can be overly invasive. In other cases, we’ll see how the same data that can keep athletes healthy and safe, can also be used to alert trainers and coaches of a decline in performance, which might be grounds for dismissal. We will also look at ways you can trick different sensors and wearables.

To kick things off, take a look at the following video:


Take a moment and reflect in your Data in Motion journal:

American Football players are not the only ones using technology to enhance their training and performance. Take a look at how the Seattle Reign are using wearables and sensors in soccer. As the video plays, write down some of the types of wearables and sensors that the players use, and what kind of data they are asked to provide in your journal.

Seattle Reign Video

Near the end of the video, someone says, “So it’s a double-edged sword. On the one hand, it can help with performance and injury prevention. At the same time, depending on who sees it, it can also come back to bite them.”

In some sense, this is like information that teachers collect about students at school. The information can be used to let your teachers know where you are doing particularly well, and where you might need some additional support. The difference, though, is that it's like your teachers can collect data about you at home, and use that information to make decisions. For example, considering the pandemic, teachers might ask you to turn your videos on so they can see you during class, regardless of what is happening in the background. This is a tough trade-off between participating and feeling like your personal life is being invaded. It raises the question again of who should have access to your personal data.

Activity 1:

We tend to put a lot of trust in data and wearables, but should we? To explore how well different sensors and wearables can be trusted, let’s pull out your Microbit step counter, Moov watch, or both.

Start whichever device you decide to use and see if you can find a way to trick the device into counting more steps than you actually take.

Were you able to fool the sensor? If someone else is around, take the device to a friend or family member and give them the same challenge.

Now we will try to do the opposite. With the device on your ankle, see if you can take 20 steps without the sensor detecting that you moved.

How did that go, what was your strategy? Take a few minutes to write down your strategy in your Data in Motion journal.

Activity 2:

Fooling sensors is not only a problem with wearables, it can also be a problem with camera based sensors too. To explore this, take a look at this homecourt video where a young kid gets the most push-ups of anyone in the world.


So, as you can see, they weren’t actually doing push-ups. And when you look at some of the videos at the top of the leaderboard on homecourt activities, it is not uncommon to see instances where someone was able to hack, or trick, the camera.

This is all well and good when we are thinking about leaderboards in a sports training app, but what about scenarios that really matter, like the facial recognition technologies that we saw in a previous activity.

This first video talks about problems with the underlying technology

This second video highlights connections with law enforcement strategies.

This third video discusses ways for tricking the computer algorithms.

This technology has come a long way, and can do a lot of things right. However, there are important questions about for whom this technology works well, and who ends up being targeted. As you reflect on this technology, take some notes in your Data in Motion Journal.

Take a moment and reflect in your data in motion journal:

Video technology is not just used in conjunction with athletes, it is also being used with fans. Many of these technologies have significant problems with them in terms of how they profile people with certain physical characteristics. They also have to be concerned with different rules about data privacy. Watch this video with a caretaker, friend, or family member and think about some of the pros and cons of this type of technology. Take some notes in your Data In Motion journal.