Battle of the Bands

Josh Valcarcel/WIRED

Josh Valcarcel/WIRED

Josh Valcarcel/WIRED

Josh Valcarcel/WIRED

Josh Valcarcel/WIRED

Josh Valcarcel/WIRED

Josh Valcarcel/WIRED

Josh Valcarcel/WIRED

Josh Valcarcel/WIRED

Josh Valcarcel/WIRED

Josh Valcarcel/WIRED

Josh Valcarcel/WIRED

With Google’s Android Wear initiative and Apple’s upcoming smartwatch, Microsoft was notably absent from the war for our wrists. But after a surprise leak last week, Redmond finally released a wearable of its own: the Microsoft Band.

Microsoft made a couple curious decisions with the Band. First, it’s not a smartwatch. The Band is a 24-hour activity tracker designed to be worn alone or on whatever wrist doesn’t have a smartwatch strapped to it. Second, it’s not limited to Microsoft’s Windows Phone ecosystem—it’s cross-platform, coordinating with an iOS, Android, and Windows Phone 8.1 app called Microsoft Health.

This means Microsoft is not directly competing for the same wrist space as smartwatches like the Moto 360, Sony Smartwatch 3, or the Apple watch, which are fighting to unseat a place dominated by classic Rolexes and Omegas. Instead, the Band is pitted against options like the Jawbone Up, Runtastic Orbit, or upcoming Fitbit Charge. Still, it could prove a landmark product for the company if it’s done right.

After using Microsoft’s activity band for roughly a week on both iOS and Windows Phone, I found that it offers a reasonably polished experience. But a few missing details—ones that Microsoft will hopefully address in future updates—keep it from being a truly great product.

On the outside, the Band doesn’t look all that remarkable. It’s thicker and slightly heavier than many other activity trackers. It doesn’t weigh down your hand, but it doesn’t quite disappear into the wrist like some slimmer options. The shape is boxy, squared off on either side of the display. This focuses the band’s fit on the top, sides, and bottom of the device, rather than curving and hugging your entire wrist. I actually didn’t mind this because the Band still offers a comfortable, customizable fit thanks to its adjustable slider clasp. It allows you to easily make minute adjustments, like tightening it during a workout and loosening it when you’re hanging around the house.

The positioning of the Band’s two buttons perplexed me at first: The power button and action button (used to start and stop tracking activities) are on the bottom side, facing your arm if you wear it like a traditional watch. But Microsoft hopes folks will wear it with the screen on the inside of their wrist. This positioning is handy for workouts, and also ensures your incoming notifications are kept discreet. So far, the screen hasn’t succumbed to scratches using this placement.

That’s good because the Band’s bright, full color TFT display is one of the main highlights of the device. Its interface is reminiscent of a tiled Windows Phone homescreen, and it opens up to a fullscreen tile with the time, and either your heart rate, step count, the date, distance walked, or calories burned. With a swipe and a tap you can access the other tiles, which include options for messages, emails, calls, your calendar, run tracking, sleeping, UV monitoring, and alarms. You can re-order, add, or remove these as you see fit through the Health app, the control center for the Band experience.

That experience, particularly receiving calls and text notifications, is superb. There was zero delay between the vibration and notification of an incoming text message on my phone and on the device. Guided workouts, which you download onto the device through Microsoft Health, are convenient and easy to follow (at least for the Couch to 5K routines I tried), although the downloading process took several tries. The tracker bothered me less during sleep than I would have thought given its size. Because it tracks both heart rate and movement, it theoretically offers a more accurate picture of your overall sleep efficiency than a product that tracks movement alone. While the optical heart rate tracking missed some momentary high-effort peaks during workouts, it seemed far more accurate than other wrist-based heartbeat monitors.

The Band is supposed to get up to two days of battery life, but if you use it as intended, tracking your sleep and daily activities, I gets more like one to one-and-a-half days. The battery died partway through a four hour bike ride I was tracking as a general workout, and using the guided workout feature for a run also quickly sapped its battery life. The low battery alert is very subtle and easy to miss. During weekdays, I’d suggest charging for a couple hours while you’re at work to get enough juice for an evening workout and a night of sleep tracking.

Unlike some wearables I’ve tested, using the Microsoft Band felt natural. The mix of subtle, customizable call and text notifications and fitness tracking features blended seamlessly into my day. Both the hardware and software feel high quality. But some things still need work. Sleep tracking, for example, requires you manually start and stop monitoring at the beginning and end of the night. Customizing the features on the band, or uploading workouts to Guided Workouts, often took multiple tries. And Cortana, a Windows Phone-only feature, didn’t allow the wrist-based voice functionality the product page promised.

Still, much of what an average activity tracker does, the Microsoft Band does better. And if Microsoft can deliver on its promise to provide a product that doesn’t just track and visualize your data, but also offer something actionable, the Band could become one of the best wearables out there. For now, it’s just really good activity tracker.

Wearables Are Totally Failing the People Who Need Them Most

Then One/WIRED

As the Internet of Things becomes an actual thing, more steps are being counted, more sleep patterns are being logged, more activities are being app-ified. What isn’t appearing in the data is much common sense or ambition. Instead, developers continue flocking to a saturated market filled with hipster pet rocks, devices that gather reams of largely superficial information for young people whose health isn’t in question, or at risk.

It’s a shame because the people who could most benefit from this technology—the old, the chronically ill, the poor—are being ignored. Indeed, companies seem more interested in helping the affluent and tech-savvy sculpt their abs and run 5Ks than navigating the labyrinthine world of the FDA, HIPPA, and the other alphabet soup bureaucracies. This may be their own undoing, as there is a very real—and potentially lucrative—potential to shake up the healthcare system and frack the $2 trillion annual cost of chronic disease.

Bangled with Fitbits and Jawbones and peering through their augmented reality spectacles, the audience at D.C.’s Wearables + Things conference saw the hype cycle of the industry buckle in on itself. Peter Li, a twenty-something inventor who studied biomedical engineering at Johns Hopkins, demonstrated a fitness watch that accurately detected and counted the push-ups and jumping jacks he performed onstage. Nike’s chief scientist pooh-poohed smart watches’ most commonly collected biometrics—steps, temperature, and blood oxygen—as irrelevant to athletic performance, while promoting the importance of smart algorithms for analyzing human performance. Adidas demonstrated a heart rate monitor that clips onto its biometric sports bra. At least someone finally figured out that women already run with a band around their chest.

But then there was Kabir Kasagood, director of business development for Qualcomm Life, which manufactures the semiconductors used in many wearable gadgets. He exhorted developers to stop screwing around in a saturated market for activity trackers and embrace the red-tape and regulatory friction of the healthcare industry. “Go from the children’s table to the grown-up table,” he said. “If you’re serious about this, embrace the FDA. Learn how HIPAA works. Make sure it’s connected to the [electronic medical record] and that all the health laws are observed. There’s a tremendous dearth of innovation here. I would move away from fitness and go hardcore into health. That’s where the money is.”

Dorthy, iStrategyLabs’ shoe clip device. Maggie Winters/iStrategyLabs

The audience response was lukewarm. After all, regulation is yucky. Clinical trials are a drag. Integration with legacy systems is boring. Security requirements and limitations on how user data can be monetized? Meh. As if to prove the point, minutes later, the marketing director of iStrategy Labs demonstrated “Dorothy,” a shoe clip that allows you to click your heels together three times to call Uber. By far the biggest hit of the conference, this hacked-together prototype snowballed into an appearance on Good Morning America.

As of September 30, there were 266 wearable devices on the market (including 118 fitness wearables), with 23 slated for release before the year is out. From Silicon Valley and San Francisco to Austin and MIT, young, healthy, highly educated, mostly male entrepreneurs are developing marginally useful apps and gadgets for people just like themselves. And indeed, most of the information technologies we currently use started this way, from personal computers to the Internet and social media. The alpha geeks home-brew technologies that are taken up by early adopters and spread until your mom is on board. The Silicon Valley assumption is that health and wellness will follow that same path.

But if you follow the money, and you really understand the population with the most to gain from improvements health and wellness, that assumption falls apart. It turns out the wave of wearables adoption isn’t rolling out the same way as the web or smartphones. More than half of US consumers who have owned an activity tracker no longer use it. A third of them took less than six months from unboxing the device to shoving it in a drawer or fobbing it off on a relative.

Test For Diabetes Elderly Person, Everyday life of an independent nurse, Bagnolet, France. Diabetic patient. BSIP/UIG/Getty Images

So who’s made a long-term commitment to measuring and tracking their health? People with two or more chronic diseases. According to a Pew Foundation survey, 45 percent of US adults are dealing with at least one chronic condition. While only 19 percent of people with no chronic conditions track their health indicators, 40 percent of adults with one chronic condition do so, and 62 percent of adults with two chronic conditions do so. So far this year $2.8 billion has been spent on wearable medical devices, and that’s expected to grow to $8.3 billion in the next five years. If you took all the fitness bracelets and smart watches sold in 2014 and multiplied that retail number by six, it still wouldn’t match the $6.3 billion US market for blood glucose test strips.

People with chronic diseases don’t suddenly decide that they’re over it and the novelty has worn off. Tracking and measuring—the quantified self—is what keeps them out of the hospital. And yet there are more developers who’d rather make a splash at a hackathon than create apps and devices for people who can benefit hugely from innovation in this area.

At some point, you’ve got to ask yourself whether it’s just the friction created by health-industry regulation—the HIPAA security rules and FDA approval (or waiver) process and the hassle of integration with legacy systems. Or is it too daunting for a twenty-something engineer to develop technology for people who aren’t like them at all? An obese diabetic on a motorized scooter? Or a frail old lady with memory loss? Or her caregiver? Someone who’s three bus transfers away from a doctor’s office?

Can our innovators rise to the challenge of an aging, chronically ill society whose medical costs are swamping our economy? Or will techies just click their heels together three times, and call Uber?

J.C. Herz is the author of Learning to Breathe Fire .

An Architect Whose Wild Structures Imitate Cells

Sabin’s work draws from fields like biology, materials science, and mechanical engineering. MICHAEL GEORGE

Sabin’s work draws from fields like biology, materials science, and mechanical engineering.

MICHAEL GEORGE

ColorFolds responds to its environment, folding and unfolding when sensors detect changes to its own structure or people walking below. MICHAEL GEORGE

ColorFolds responds to its environment, folding and unfolding when sensors detect changes to its own structure or people walking below.

MICHAEL GEORGE

The installation’s color shifts thanks to layered polyester film. Nickel-­titanium wires contract like muscle fibers in response to heat or electricity. MICHAEL GEORGE

The installation’s color shifts thanks to layered polyester film. Nickel-­titanium wires contract like muscle fibers in response to heat or electricity.

MICHAEL GEORGE

Team members (clockwise from left include Martin Miller, Nick Cassab, Giffen Ott (on ladder), Andrew Moorman, Jenny E. Sabin, Andrew Lucia, David Rosenwasser, Jessica Jiang. Not shown: Max Vanatta MICHAEL GEORGE

Team members (clockwise from left include Martin Miller, Nick Cassab, Giffen Ott (on ladder), Andrew Moorman, Jenny E. Sabin, Andrew Lucia, David Rosenwasser, Jessica Jiang. Not shown: Max Vanatta

MICHAEL GEORGE

Architects like to poach design elements from the life sciences—a DNA helix here, a spherical nucleus there. But Cornell architecture professor Jenny Sabin goes even more interdisciplinary. “I'm not interested in just making buildings from beautiful forms in biology,” she says. Her experimental installations draw from just about every department on campus.

One of Sabin's latest projects is a set of hanging panels called ColorFolds that echoes the extracellular matrix, the zone between cells filled with proteins and other molecules critical to cell function. The structure responds to its environment like cells do, folding and unfolding when sensors detect people walking below. As it moves, the colors change, thanks to a polyester film Sabin tracked down after talks with a materials scientist. And for the movement, two mechanical engineers made springs from nickel-titanium wires that shorten in response to heat and electricity, contracting like muscle fibers. Looks like the engineers are borrowing from biology too.

How Graph Databases Can Reinvent Recruiting

lumaxart/Flickr

They say it’s not what you know but who you know. However, the missing implication of that is the importance of who they know. The ways that we are all connected are broadly interesting in a “six degrees of Kevin Bacon” way. However, for recruitment sites trying to find and access important, talented people, it’s much more valuable than that. Endless internet searches and manually trawling through CVs is the common process for many recruiters today — but this is time consuming and quite restrictive in what information it can deliver. Also, once the data is gathered it can be difficult to sit back and actually make sense of it. So, how can the recruitment industry move on from this?

Traditionally, the ways that such data is stored has not been easy to access or analyse. Relational databases, often formatted in tables, could provide plenty of information about individual records in a basic siloed form, but simply weren’t designed to show relationships and patterns between those records. You could unearth some of these connections at a very high level, but the results were extremely slow and lacked real definition. It’s like the difference between understanding two people that live in one house and knowing if they are married, siblings, flatmates or tenants.

Today, far too much time and effort is consumed in the slow process of working with the old style of databases or manual methods like trawling the internet. This works, of course — but it gives you little or no advantage over your competition. And the market for great talent is nothing if not competitive.

For example, tools like LinkedIn are built on a different kind of database in the background that fundamentally tracks relationships. This is the same as Facebook, Twitter — any social network, which revolves around how people know each other. The reasons these companies run on this kind of technology are clear. For a start, it’s much faster and more efficient. You can achieve the same kinds of effects in these ‘graph’ databases with 10 to 100 times less code. But perhaps more importantly, you can also perform different kinds of tasks that just aren’t possible on older tech.

If recruitment sites collect existing data sets from the likes of LinkedIn, other job sites and personal records/CVs to create their own, more comprehensive graph database, they could start to immediately understand and classify candidates based on their relationships with others, their background, specific skills and even their hobbies and interests to see if they have cultural fit. This would not be identified by reading it on profiles, but by asking the right questions with specific search criteria and key words. For example, ‘has Joan Phillips ever worked for Sony or known anyone that has?’ These systems can pick out the important connections for us in a matter of seconds.

When it comes to looking at interests and hobbies, recruitment sites can use this information to proactively approach individuals for roles that may be of interest to them. Graph databases can help source individuals who aren’t necessarily looking to move but have a clear link of interests with another dimension of the role or the company itself. For example, it might be clear from the interest data that the candidate is a football fan — the perfect match for a role at the FA. These sorts of advantages are, at best, laborious and, at worst, impossible to generate manually.

The important detail here is that it makes us more effective at identifying people who genuinely should be the best match for a position. This industry is much maligned for contacting people out of the blue for roles they aren’t interested in — but that’s because the best examples of execution are so effective and such a great match that they remain undercover. Graph databases help create more of these instances.

This doesn’t mean there’s no human component. It just means you’re able to use the power of machines to quickly and at scale, crunch the numbers, answer your queries and give you superhuman ability. The machine does what it’s good at and the recruiter is able to concentrate on what they are good at.

Equally, these tools should increase the opportunity for candidates to understand the possibilities that lie before them. If you can describe to them the caliber of employees who have worked at your company (or your client’s) — even the kinds of things those people have gone on to achieve after leaving, you can add to your arguments with clear, persuasive data. Again, this comes directly from better tracking of relationships in the data.

For a long time, this industry has been built around the power of informal, real world networks and word of mouth recommendations. There’s no longer any reason that the tools we use to pursue those same goals are designed around the same philosophy. Armed with graph databases, recruitment sites will be able to quickly identify the best candidates for their roles and in turn, candidates are much more likely to be happy with their new jobs that have been matched so well.

Emil Eifrem is founder of the Neo4j open source graph database project.