More than a decade ago, an Intel team doing ethnographic studies of families dealing with Alzheimer’s came across an 86-year-old man named “Carl” who loved woodworking. I can still remember the amazing kitchen cabinets, toys, and desks he made for friends and family who put requests for him to make them things in what Carl called his “purpose jar.”


Carl’s troubles began with shoulder pain and stiffness; he thought it was simply a muscle strain from working in his shop. But his physical and cognitive symptoms got progressively worse, with fatigue in his hands that soon made his stamina and accuracy at woodworking start to crumble. We have photos of his wife sitting on the opposite side of the shop room door, waiting to dial for an ambulance if he hurt himself moving all of those dangerous saws and equipment around, but she couldn’t bear to steal away what she called his “soul purpose.”


It took three years and many confusing doctors’ visits (and the emotional, physical, and financial burdens of numerous tests and experimental treatments) to figure out that Parkinson’s disease, not Alzheimer’s, was behind Carl’s frustrating set of symptoms. As we did follow-up studies with Parkinson’s families afterwards, we heard story after story of how long it took people to be diagnosed because of the complex and sometimes confusing ways in which Parkinson’s can manifest as well as the decided lack of objective measures to rely upon.


I think fondly of Carl as I reflect on the exciting potential of today’s announcement that Intel is working with the Michael J. Fox Foundation on a next generation of Parkinson’s research – using technologies that we only dreamed of a decade ago. That quest that we started back then to use everyday technologies to identify “behavioral markers” for better early detection, progression monitoring, and individualized treatment of disease is becoming much more viable and scalable in a world of cloud and wearable computing—and the Internet of Things.


Here is the journey we had to take back then. In the summer of 2004, I had several meetings with Andy Grove about his desire to measure Parkinson’s symptoms more objectively. As Carl’s case painfully illustrated, the means of the day to assess how a person’s symptoms were progressing were terrible – occasional doctor’s visits, some patient diaries, all poorly recollected and approximated for a disease that can be so variable person-to-person and hour-by-hour for an individual.


Our team spent six months understanding existing tests, interviewing specialists with promising new tests, and sketching/trying out some early designs. We had alpha quality systems built in August of 2005 and completed our beta systems in November of 2005. By early 2006, we started with our first study participants, and even demonstrated initial results at the 2006 World Parkinson’s Congress in Washington, DC and to a U.S. Senate hearing.  Up until that point, I think few Parkinson’s experts understood the positive disruption that these technologies might enable, but with Andy’s example and leadership, many in the field started to get interested.


What was the invention back then? We called it “the brick.” It was a tabletop appliance, weighing roughly as much as a couple of bricks, to guide a patient through a 20-minute battery designed to capture metrics quantifying her condition, as well as a watch-sized device measuring tremor. These included tests of coordination, fine and gross motor skills, reaction times, speech quality, and tremor analysis. In order for it to be effective, the patient needed to go through the 20-minute battery regularly.

We demonstrated this investigational device to yield clearly more objective measurements than those gathered by infrequent doctors’ visits. But it was cumbersome, expensive, and difficult to scale to larger studies.



Sensing symptoms wasn’t so much an issue as getting the results from people’s homes to the study coordinator. The world wasn’t as connected; WiFi was fairly rare, and some study participants didn’t live in areas that could support a broadband connection. On the sensing front, the fact that people were taking a dedicated test – performing for a show, so to speak – caused some interesting effects. Once they were bored by the activity, they’d stop trying so hard and we’d typically see a decline in our metrics that didn’t match disease progression.


Today, in the new project announced with Michael J. Fox Foundation, the problems we encountered 10 years ago are largely gone. (It almost seems like magic, even though I’ve been working at a hard-charging technology company all this time and know that it’s hard engineering work, not magic, that solves such problems.)


It is game-changing to apply ultra-mobile wearable devices, unobtrusively embedded into everyday life, and a big data analytics platform to the problem of tracking Parkinson’s symptoms and treatment response in hundreds, and eventually thousands, of patients. All they need to do is wear a cool watch and touch a smart phone app to record how they are feeling and how they are doing with their medications. No more special purpose “bricks” to lug around—and many of the “tests” now mean just going about one’s daily life, as sensor and analytics act in the background on his or her behalf.


That’s a far cry from sitting at a table and taking a somewhat frustrating test, and a much farther cry from the subjective tests that doctors have been using since Parkinson’s disease was first described by Dr. James Parkinson in 1817.


Going forward, instead of getting a few sporadic and poorly recorded data points from a specific desktop device, researchers get hundreds of readings per second from everyday devices. I firmly believe that somewhere in all that big data are answers to improve the quality of life for the 5 million people globally who have Parkinson’s and their families. And the learnings from Parkinson’s may have impact on a range of other neurological and neuromuscular challenges.


For all those families who allowed us in to their lives a decade ago to help inform these innovations, I am thrilled to see this model moving forward. Tracking disease and treatment responses using bio-sensing technologies around, on and even inside the body --- continuously sending big data that can be mined to discover new generations of therapies and personalize care down to a person’s movements and molecules – these are possibilities barely unimaginable in Carl’s time.  But they are becoming real in a world of connected, secure, ubiquitous computing.


There are many, many medical conditions that rob quality of life and cost society greatly for which this new model holds promise. That’s why I am so honored for Intel to have this new collaboration with the Michael J. Fox Foundation. That’s why I am so hopeful about the future of healthcare. That’s why I am so excited to share this with you on this important day.  And for the Intel team, our own “purpose jar” of projects for the next decade is full and fulfilling, as we scale these kinds of capabilities from research to the everyday lives of people around the world.


Eric Dishman is an Intel Fellow and General Manager of the Intel Health & Life Sciences Group.