A simple exercise to help you conceptualise a next generation wearable device.
Callaghan Innovation National Technology Network Manager Kirsten Edgar blogs about how to use the ‘thinking exercise’ from the May C-Prize information roadshows to help produce a wearable technology concept that pushes the boundaries.
During the week of 1-5 May, a series of C-Prize information roadshows were run across the country, and I was lucky enough to take part in them. I wanted to share the thinking exercise that all attendees took part in during the roadshow. I encourage you to download it and do it yourself at home.
The purpose of the exercise is to help you conceptualise a next generation wearable device. One of the aspects of being human is that we know what we know, and we tend to use this knowledge in a linear fashion. Take a current, and seemingly ubiquitous, wearable; a fitbit. With tens of millions of people now using one, it’s no surprise that other wearable tech developers want to piggy-back on it, leading to the approach of making “new” wearables simply by adding new sensors to this existing watch-type device. This is an iteration – very much ‘thinking inside the box’ – but we believe that here in New Zealand, we can do something more exciting by engaging fully in the convergence of technology and talent.
So, let’s start by trying out the thinking exercise, which I hope you’ve now downloaded. If you’re anything like I was the first time I saw it, you’re staring at it blankly and thinking “what the hey?”. No need to fret – keep reading for help. The aim of this is to get you thinking about how technology can open new doors, and to get your creative juices flowing on all things wearable!
First off, I’d strongly recommend that you gather some friends / family / colleagues / random strangers on a bus before you tackle this. The corollary of us knowing what we know, is that we don’t know what we don’t know, and for this exercise 3 or 4 heads are better than one.
On one side of the page is a list of things that we at Callaghan Innovation see as exciting developments in technology, human methods of interaction, and business models. We call them ‘Technology Signals’, and as you can see, they include everything from the internet of things, to spider silk. This is not exhaustive, so if there are other developments that you’re excited about, just use this list as a starting point, and add your own.
Once we have our signals in one place, we can get on with the exercise:
- Choose 2-3 of the Technology Signals that excite you;
- Flip the page over, and write one in each of the spaces labelled “Write Signal X Here”;
- Decide whether your wearable is going to help someone live healthier, work safer, or play smarter – this is what we call ‘Your Track’, and these three tracks match up with those in this year’s C-Prize;
- Within that track, think about a specific user; perhaps a forestry worker, a swimmer, or an amputee;
- Think about a specific need that this user would have, or a challenge they face;
- Now think about how the developments (signals) you’ve selected could come together to provide a wearable solution to that challenge or need;
- And finally, using your best pens, draw up your concept for a next generation wearable!
Easy, huh? Maybe not…So, to help you along, I’ve included the details of what myself and couple of colleagues came up with when we did this exercise.
As you can see, the signals we chose were the X-Games, Analytics, and Project Jacquard. With the X-Games getting bigger each year, we decided to focus on ‘playing smarter’ as our track, and specifically on the BMX riders who can land crazily big jumps. Next, we had to think about how Project Jacquard and data analytics could contribute to a next generation wearable that would provide riders with feedback to help them train to land those jumps?
Project Jacquard gives you the ability to weave electronics into fabric. Data analytics allows you to take seemingly unrelated points of information and find patterns. What if you could develop a training suit that had sensors woven around the elbows, knees, and hips, which measured the angles of those joints, or determined the pressure they’re under? And then what if we wove in transmitters so that the data could be sent to a computer? And then correlated that data with the rider’s success or failure in landing the training jump? You could use analytics to spot patterns, and to determine the subtle changes to the rider’s stance – straighter arms, more bent legs, whatever it might be – that give them the best chance of landing that crowd-pleasing jump and winning their event. And boom, there you have it! A potential next generation wearable that addresses an end-user’s need by measuring something about that person or their environment, processing that data, and feeding the packaged information back to the user. My drawing skills are limited to say the least, but just for you, I’ve even included the picture that I drew. Why not give it a go? You’ll be amazed at how quickly your team comes up with fantastic ideas!