Yet, it is the emergence of what


he calls “wearables 3.0” that is set to change how we manage our health and well-being, Smith be- lieves. Why? Because these tools are a new class of wearable that measure what the body is doing in real time. For example, they measure blood glucose, blood pressure, heart rate variability, functional nutrition, sleep qual- ity and inflammation measures. To explore “wearables 3.0” I


recently asked Smith to discuss these new technologies and why he is so excited by them.


Colin Milner: Ken, what are your


views on older adults and their adoption of technology? Is the stereotype true? Ken Smith: The stereotype for how


older individuals interact with tech- nology is incomplete. In that view, old- er individuals will not adopt technol- ogy because they are either too set in their ways or because they are not dig- ital natives. I see this differently. Older individuals have a higher bar for the use of a technology; they ask, “What does this do for me?” If they see the value that a technology could add to their lives, they will adopt it and figure it out. Technology is a tool, rather than an end in itself, for older users.


CM: What do you find so interesting


about “wearables 3.0,” as you call this new generation of products? KS: Firstly, given the heterogeneity


of the aging population, it is very dif- ficult to say how much a 70-year-old should exercise, for example. Some of these wearables will allow us to per- sonalize things based on the actual physical capability of the individual instead of providing blanket solutions. Secondly, behavioral change solu-


tions are hard, particularly when we ask someone to do something that we hope will have a long-term effect. For example, will you avoid that donut now in order to have a lower likelihood of developing type 2 diabetes in 20 years time? This connects with what psychologists call temporal discount- ing. It means that we tend to discount things that offer future rewards rela- tive to things that reward us now.


With some of these new wearables,


people will start to sense what’s going on in the body in an almost real-time manner; they may also gain more im- mediate feedback. For example, if I ate that donut, I would see my glucose measurement jump and my blood pres- sure rise, and possibly also see some inflammatory response. The wearables pull the action (i.e., eating the donut) and the impact (i.e., rise in glucose) tighter together, which helps people better realize what they’re doing to themselves.


CM: How will these tools change in-


teractions with doctors and the medical system in general? KS: I hope wearables put more fo-


cus on the things we can do to opti- mize wellness rather than to wait until something goes wrong and then try to fix it, which is the focus of the cur- rent medical system. These technol- ogies will definitely push us in that direction. Wearables could augment such


things as doctor visits. For example, to- day if a person consults a doctor and the doctor chooses to do a measure- ment in the lab, it will capture only one snapshot in time of that individ- ual’s health. However, it is possible to see different things with these new tools that measure people on a lon- ger-term basis, so a doctor might re- spond very differently because there is more patient data. That’s a good thing. Individuals will also be able to take ownership of a lot of that data, enabling them to reach some of their own conclusions.


CM: Will we see artificial intelli-


gence (AI) integrated with wearables to make health recommendations long be- fore the stage where a person needs to visit a doctor? KS: We are already seeing AI take


on lots of tasks that are repetitive in nature and often driven by data. Medical diagnosis is one of those things. So, AI may become as good as a doctor at determining illness, perhaps even better. But there is a caveat: We have all these theories of how various measurements relate to our health, and we make recommendations based on these theories, yet we don’t always have large data sets that actually tell us that those theories are valid.


This is a cart and horse problem.


Right now, there is a lot of credible dis- cussion going on about some of these measurements, but it is not really vali- dated. If we collect a lot of data, we can eventually start to make conclusions. But, we will not have that data until we have more measurements. And un- til we can use the measurements for something, people will not necessarily do them, and so on. Still, I think AI will gradually be-


come the front end for doctors. Physicians will likely have much bet- ter information then, so they can spend more targeted time on what needs attention. One more caveat: Data security is


one of the top concerns for organiza- tions and individuals. We need some- thing to be developed that allows peo- ple to trust where their data goes and what’s being done with it. The double- edged sword of any data collection is that data can be used for good, but it also can be used to exclude a person from insurance or to change what in- surance will pay to cover. So there is a lot of work needed to create that trust so we can say, “If data is taken on me, I know where it goes and I have control over who sees it and who does some- thing with it.”


CM: What technologies do you think


are terrific products? KS: There are products I find inter-


esting, and then there are products I think have a business model I would put my money behind. That has been a sticking point for many of these tech- nologies—is there a real business case for them? One area I’m excited about is heart


rate variability [HRV], which is the statistical variation in the distance between the peak measurement on an ECG. A lot of science indicates that people with lower HRV are less healthy than people with higher HRV. Technologies are being developed to measure this variability, which it turns out can also be a good thing for ath- letic training. When individuals do a big workout one day, they’ll find the next day that their HRV has actually dropped, and that’s an indicator to rest or to do something a little different. Wearable technologies that measure HRV give real-time input on how best to train.


» Fall 2018 Fitness Business Canada 17


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