Lab Rat

Lumo Run: Diving Deeper into Running Metrics

During a recent interval workout, a cyclist pulled up alongside me to give me some pointers. I would run faster, he said, if I tucked my left elbow in. This is by no means an unusual occurrence for me. My running form really is so awkward-looking that complete strangers are frequently unable to resist trying to help me.

You might wonder why, after 25 years of running, I haven’t fixed it. The truth is that running form remains a hotly contested topic among sports scientists. It’s clear that some people run more efficiently, and with a lower risk of injury, than others. But figuring out what needs to change, how to change it, and how to assess whether the change has been successful remains a dark art – especially if you don’t happen to have a state-of-the-art biomechanics lab to assess to your gait.

All this meant that I was eager to try the Lumo Run, a tiny oval pod launched last summer that clips to the back of your shorts and measures a set of stride parameters. Some of the measurements, like cadence (the number of steps you take each minute) are recorded by gps watches, fitness monitors and smartphone apps. But Lumo also offers more specialized metrics like bounce (up-and-down motion of your body), braking (how much you slow down with each foot strike), rotation (twisting of your pelvis) and drop (how much each hip lowers).

The first problem I encountered was that you need to run with an iPhone to get real-time feedback on your form. Lumo also offers real-time tips to help you improve weak areas: if you’re bouncing too much, for example, the app might suggest that you imagine you’re trying to balance an egg on your head. For those who don’t like running with a phone, fortunately, you can still run with the pod, sync the device afterward and then review the collected data.

Lumo’s verdict, after a few runs, was that my bounce and drop were pretty good, but my cadence, braking and rotation were appalling relative to the norms their research team has identified. (For example, they suggest that bounce of less than five per cent of your height is a good target.)

I think it’s good that, rather than simply dumping a bunch of data off to you, they offer some context and goals for each variable. That said, it’s worth taking these goals with a grain of salt. My typical cadence of around 167 steps per minute for easy runs is below their goal of 180. But the longstanding hype about the “magic” cadence of 180 is based on observations of Olympic runners during races. Cadence increases with running speed, and other studies have found that elite runners drop below 180 strides per minute when they’re running slower than about 3:00/km.

When I took the Lumo out for quicker ( but not 3:00/km!) tempo runs, I found that my cadence increased to the mid-170s and my bounce got even smoother, but my braking and rotation got worse. These are the kinds of observations – teasing out the subtleties of how my form changes at different speeds, and offering some tips for how to address negative changes – that seem like Lumo’s biggest benefit for someone like me. I’ll also be curious to see how different types of shoes affect subtle stride metrics like braking.

Ultimately, what wearable technology is good at right now is observation. Lumo gives me fascinating form data that, until recently, would only have been available from a sophisticated university laboratory. Whether following the app’s personalized coaching advice will really make me faster or healthier remains speculative at best – but for dedicated running nerds, the data itself is pretty cool.

Read Alex Hutchinson’s regular column ‘The Science of Running’ on p.38