If only Nike+ could connect the dots...

Having finally suffered from the dreaded Fitbit Sweat Rash, I've bought three new straps for my Flex.

Looking at the new straps, I really hadn't realised just how hammered the original two pink straps had become.

Coincidentally, yesterday I got an email from Nike reminding me to replace my running shoes every 300 km. Interestingly, according to Nike+, my current pair have done almost 600 km.

If software was connected to sales, it could offer me a discount.

But, as with so many aspects of the health/fitness wearable industry, there's plenty of data in the system, but few smarts on how to use it effectively.

Two problems with the Quantifiable Self - quantification and self

Anyone who works with data knows what a messy situation it always is. All data - at least all useful data - has issues, ranging from how it’s recorded to how it should be processed. This is particularly the case with systems that rely on some human input. Self-reporting is notoriously hopeless, with research suggesting, for example, that the self reporting of ‘calories eaten’ is under reported by around 30 percent. Even using a device like my Fitbit Flex, you have to remember to switch it into sleep mode for it to automatically measure sleep (yes, I know you can manually add it later, but who does?). Similarly my Nike+ GPS watch can take anything up to a minute to lock onto the satellites it requires. Not to mention, randomly resetting itself to 2010 if it runs out of power, and the five or so times it never got a satellite signal during a 30 minute run. Margin of error These are slight errors of self and quantification, of course. More worrying - given we appear to be ready to hand over aspect of personal medicine to such devices (c.f. Apple’s HealthKit) - is the basic accuracy of the devices we’re using. A recent example. I went for a run using a Beurer fitness watch with heart monitor, and my Nike+ GPS watch. Both were started at the same time, but at the end of the run, the Nike+ watch listed 403 calories burnt, while the Beurer said 320. Assuming the Beurer+heart rate monitor is the more accurate of the two, that’s a 26 percent difference. Combining my two examples then, I could be over-exaggerating my calories burnt by 26 percent and under-exaggerating my calories in by 30 percent. That’s massive inaccuracy. Life and death? Yet, again, it could be said this is a trivial case. Where it does get concerning is when devices say they can accurately measure proper medical metrics such as cholesterol or blood sugar, or for some people even heart rate and calories (in and out). Not to mention when doctors are relying on people using the devices properly,: and that could be whether legitimate or illegitimate misuse c.f. the statistics about how many people complete their set treatment of antibiotics (22 percent of 16-24 year olds) But maybe I’m being too pessimistic. The Quantified Self can clearly produce great results, even with the current generation of devices. In most of these cases, though, it works because the motivation behind the Quantified Self is the self. Initial self awareness and self motivation enables quantification to positively feedback into a better self. Where we need to be concerned is in the cases of those where we expect quantification alone to drive self and change behaviour. 

Apple, HealthKit and the Walled Garden

Somewhere between a bang and a whimper, Apple announced its HealthKit platform.

This being revealed at the company's developer conference, Apple didn't talk about any consumer hardware. Instead its focus was to talk briefly about how the platform unifies multiple health metrics.

Combined with Apple's linked and overarching Health app, it looks like the baseline configuration won't offer anything different that the current generation of health trackers - tracking calories, sleep, heart rate etc - plus what looks like more comprehensive medical metrics, listed as ominously as Diagnostics. Lab Results and Medical ID.

Apple has said that HealthKit will be open to thirdparties, mentioning for example the Nike+ fitness platform. But the point of the platform is that within iOS, you'll be able to share whatever data you're monitoring with integrated apps, including links to professional healthcare providers.

US regional provider Mayo Clinic has been particularly keen to praise the move.

Perhaps the biggest unanswered question, however, is how open the data is, particularly in the longterm?

Obviously there's a privacy issue involved in terms of how medical data is shared and made available in the short-term, but equally, given Apple's proprietary nature (aka The Walled Garden), it seems unlikely it's adopting open industry standards, which as I've argued is a main longterm concern with this sort of fitness and health data.

And maybe, as important, it's not clear how Apple's iOS 8-centric approach will en/discourage the wider health and fitness app industry, which is something that will require support for Android and the web.

After all, we're not going to be using Apple hardware for the rest of our lives. 

Why smart watch market share estimates remain meaningless hokum

According to market intelligence outfit Strategy Analytics, the smart watch market is exploding.

It reckons global shipments were up 250 percent year-on-year in Q1 2014 to over 700,000 units.

The key driver of this growth was Samsung, which shipped 500,000 units, taking an estimated 71 percent market share.

What tosh...

Whether the numbers are correct or not - and the fact these are units shipped not sold is a clue - it's pretty clear Samsung is not going to be the market leader on this sort of scale.

After all, back in 2013, rival market intelligence outfit Canalyst estimated that Samsung had a 54 percent market share but that was when it had shipped lots of Galaxy Gear smartphones, many of which were subsequently returned to retailers because it was a rubbish product.

But did Canalyst track those returns? Did it heck.

Of course, the more vital issue with Samsung smart watches is they only work with Samsung phones. Sure, that's a big market but it also demonstrates that Samsung doesn't get the potential of smart watches in the way that Pebble (which supports iOS and Android phone) does - and I'm not just saying that because I'm a Pebbler.

But, perhaps even more importantly, the smart watch market is so nascent at the moment that until we've had a couple of quarters of Android Wear hardware shipping (and more importantly being sold and worn by real people), there's little point even discussing market share percentages.

Still, if you have $6,999 burning a hole in your pocket, feel free to buy Strategy Analytics' no doubt awesome 6-page report. 

The importance of important data

I've been using my Fitbit Flex for a couple of months now, and I like it. I haven't lost it, like my Fitbit One and it hasn't been recalled, like the Fitbit Force. Sure it's merely functional but that's all I need.

One thing I particularly like is the weekly email of my data, which I've worked up into some graphs.

But are these graphs (and hence the underlying data) useful? Not in all cases, I fear.

I don't do anything clever in terms of entering my eating habits into the Fitbit website so that means the graph of total calories burnt is data once removed as it's reversed engineered from my activity; something effectively covered by the other two graphs.

Also, it's pretty clear to see that total distance travelled (in km) and total steps are measuring the same thing.

Still, I do find it interesting that my both are on an upwards curve. Now if only there was a simple way of extracting sleep data...

Predicting 90 million wearable devices shipped in 2014

As demonstrated at CES 2014, wearables are *the* explosive industry sector.

Which is why the all market intelligence companies are frantically releasing their views of just how large the market can be.

The latest outfit to chance its arm is ABI Research, which reckons that 90 million wearable computing devices will be shipped in 2014.

The majority of this - it predicts - will be from healthcare and the sports and activity sectors - the latter driven by health-lite concerns about weight and obesity. ABI Research doesn't think devices such as Google Glass and smart watches like Pebble, while driving consumer interest, won't be commercially successful, however.

"The next twelve months will be a critical period for the acceptance and adoption of wearable devices," says ABI's senior analyst Joshua Flood.

"Healthcare and sports and activity trackers are rapidly becoming mass-market products. On the flipside, wearable devices like smart watches need to overcome some critical obstacles.

"Aesthetic design, more compelling use cases, battery life and lower price points are the main inhibitors."

I.e. wearable devices need to be nice to wear.

Other companies have based their view on the industry around its financial value. Back in 2013, Gartner says it would be worth $10 billion in 2016, while Juniper Research takes the view of $19 billion in 2018.

D.I.Y. Data: Two months of monitoring my vital signs

Two months ago, I started regularly tracking some of my biometrics using a blood pressure monitor.

It's a semi-serious attempt to see how my body is reacting to the stresses and strains of daily life, and something I'll be looking to continue into 2014.

And with that in mind, here are the first 50 days of the experiment.

I think it's difficult to see any clear trends. I try to take the readings at the same time in my day - at the start - but given my weird operating routine, that's certainly not the same time each day in terms of GMT.

Still, there is a clear downwards trend in systolic blood pressure, although that may partly be because I'm getting more used to taking my own blood pressure.

My diastolic pressure has remained more constant during the period, so the systolic-diastolic line has decreased thanks to the downward trend in systolic pressure. Weight and heartrate have remained steady. 

D.I.Y. Data: Checking my vital signs

Following the self-destruction of my Up band, and general moaning about the lack of open source data, I've come up with a solution.

Well, a solution of sorts. I've started manually tracking myself.

Luckily, we had a blood pressure monitor in a back cupboard and that's the core of my new regime.

When I get up, I weight myself and check my blood pressure and heart rate. That's manually entered into a spreadsheet, and I drop the numbers into a simple graph (below).

It's not rocket science, but checking these vital signs at roughly the same time every day (always before eating) should provide consistent results.

More generally, checking our vital signs is a step beyond the sport and health trackers because you certainly can't take a blood pressure reading without a proper sleeve attachment. However, the monitors themselves aren't expensive and some manufacturers of other health equipment such as Beurer and Withings do sub-£30/$50 examples.

Equally, measuring your blood pressure is medically more important than factors such as heartrate, sleeping patterns or even weight. There's a reason they call high blood pressure the 'silent killer'.

Of course, it is related to metrics such as weight, diet and general fitness, but as you can see, at the start of the process, my blood pressure was rather high.

I've since made some lifestyle tweaks and am happy to see it dropping towards the standard '120 over 80', although I'm sure there's a large psychological element in this. My lifestyle changes are not so radical that it would have had this impact so quickly.

Anyhow, what's more significant for me is not just rely on what my sensors are recording. Sure, that's useful but just because we're measuring something doesn't mean it's important. 

The wearable technology dilemma: Where's My Data?

Despite now being broken, I'm found my five months with the Jawbone Up bracelet an interesting period.

It's given me my first decent set of personal data, which is surely the point of wearable tech.

When it comes to five months of sleep data, it's not always so reliable as sometimes I forget to toggle into sleep mode, but at least I can see some broad data. September was a good month of sleep (holiday!). July and October weren't - too much travelling.

It is good to see that I've been getting more active.

Still, with my Up band now out of action, the sad thing is this data is now pretty much useless.

It's been said that the most important thing about wearable technology is that is has to be in a form that people will wear. Yet equally important is that you can get the data out of the system in a form that you can combine it with data from sensors from other companies (and even manually-inputed data). After all, over the years, we're going to be using equipment from various providers.

I think the latter will be a harder problem to solve than the former.

21 months with Nike+ SportsWatch GPS

When it comes to big data, the problem for the self-monitoring individual is that it takes a lot of time to generate a big enough set.

Conversely, it's very quick to generate big data on a big population, and because you're looking for broad trends, you don't really care about individual variations - again, that's exactly what the self-monitoring individual is looking for.

In my own small way, the biggest dataset I've recorded to-date comes from my Nike+ TomTom running watch. It's not been perfect - due to user error as much as system deficiencies - but over the past 21 months, I've seen some trends.

In particular, I was surprised to see that of the four months in which I've been running the most, three of them were during 2012, with August 2012 being by far my 'best' month.

More generally, I was surprised to see that I managed 69 runs in 10 months in 2012, compared to only 61 runs in 10 and a half months in 2013. I was sure I'd been running more this year.

Certainly I'll need to get my skates on if I want to hit 70 runs this year.

And, on the most crude level, that's why big data is useful for the individual - when it combines with your inherent motivation...