Quantified self

As wearable technology improves we can develop a more patient-centric approach to medical diagnosis and treatment


Even though wearable devices are largely single purpose the persistent log of data they produce is invaluable, establishing baselines against which deviations can be observed. Photo: AP
Even though wearable devices are largely single purpose the persistent log of data they produce is invaluable, establishing baselines against which deviations can be observed. Photo: AP

Rachel Kalmar is a Stanford PhD in neuroscience who also happens to hold the world record for the most number of wearable sensors worn continuously. When you meet her, your eyes are immediately drawn to the dozen different sensors strapped to her forearm, attached to her belt and hanging around her neck. For the last three years, Rachel has worn between 10 and 30 sensors on her body every day and has collected data from these devices to better understand issues relating to data access and interoperability.

Rachel may be an outlier in terms of the sheer number of wearables on her person but if you look around you right now, chances are at least one person in your immediate vicinity is using some sort of wearable device that tracks the number of steps he takes or how she sleeps.

These devices are constantly collecting information—their software offering us real-time visualisations of what’s going on with our bodies. And even though they are largely single purpose—designed to track movement and goad us into greater physical activity—the persistent log of data they produce is invaluable, establishing baselines against which deviations can be observed.

These datasets have already begun to insinuate themselves into the courtroom. Personal injury lawyers have started to use personal trackers to produce evidence as to the extent of personal suffering by comparing activity levels before and after trauma. Insurers and defendants are trying to force plaintiffs into disclose personal tracker data in order to refute injury claims by analysing the wearable data at the precise time of the alleged accident. In at least one instance, wearable data has been used to refute allegations of sexual assault.

In most instances, legal protection against self-incrimination would fail if the information can be requisitioned directly from the cloud.

But the true benefits of personal tracking lie elsewhere—in the not too distant future.

Larry Smarr is an astrophysicist and computer scientist who has taken the concept of quantified self to unprecedented heights.

A couple of years ago, The Atlantic nick-named Larry “The Measured Man” in a piece that described the extent to which he tracks his personal parameters. Larry’s armband doesn’t just track movement—it records acceleration in three dimensions along with skin temperature, galvanic skin response and heat flux.

When he sleeps, his headband monitors his sleep patterns every thirty seconds. Eight times a year he draws blood to track over 100 different markers and he’s deeply obsessed with his own faeces—measuring the microbial content of everything he excretes, charting it over time to better understand his personal intestinal biome.

This is extreme personal quantification—and while it might seem a bit much, thanks to his obsession with personal tracking, Larry Smarr discovered that he had Crohn’s disease well before any of the symptoms associated with the onset of Crohn’s became evident.

But what is even more interesting is his (equally scientific) approach to treatment.

After he discovered he had Crohn’s, Larry continued to measure himself, now focusing on minute variations in body patterns that could give him an early warning well before his body reacted with discomfort.

He looks to identify imbalances and ways in which he can chemically compensate for them so that he can restore his biological balance.

This, to me, is the future of medicine—quantified personal measurement coupled with customised treatment that addresses each individual patient’s particular condition.

At present, our approach to diagnosis and treatment is exactly the opposite. Consider, by way of example, our drug approval process.

Pharma companies are required by law, to test new drugs on a small sample of the human population before they can be approved—on the assumption that the reactions of that sample group can be accurately extrapolated to the larger population. This population-centric approach is clearly flawed but, until now, is what we had to live with as it is practically impossible to monitor individuals for as long as it would take to establish the baseline necessary for customised treatment.

As wearables proliferate and as the quality and variety of the physiological data they collect improves, it will soon be possible for us to make medical treatment more patient-centric.

As Larry Smarr continues to demonstrate, we are within touching distance of this future.

However, in order for this to come to pass, we need to make changes to the regulatory framework around medical treatment and drug discovery in order to allow our diagnostic protocols to more directly respond to the medical needs of individual patients.

And if we really want to leverage the power of algorithmic diagnosis, we will need to radically re-think our notions of privacy so that we can apply more universally, the kinds of software driven analysis that Larry Smarr used to diagnose and treat himself.

Rahul Matthan is a partner at Trilegal. Ex Machina is a column on the intersection of technology and law.

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