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Alexis Madrigal

Alexis Madrigal - Alexis Madrigal is a senior editor at The Atlantic. He's the author of Powering the Dream: The History and Promise of Green Technology.
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The New York Observer calls him, "for all intents and purposes, the perfect modern reporter." Madrigal co-founded Longshot magazine, a high-speed media experiment that garnered attention from The New York Times, The Wall Street Journal, and the BBC. While at Wired.com, he built Wired Science into one of the most popular blogs in the world. The site was nominated for best magazine blog by the MPA and best science Web site in the 2009 Webby Awards. He also co-founded Haiti ReWired, a groundbreaking community dedicated to the discussion of technology, infrastructure, and the future of Haiti.

He's spoken at Stanford, CalTech, Berkeley, SXSW, E3, and the National Renewable Energy Laboratory, and his writing was anthologized in Best Technology Writing 2010 (Yale University Press).

Madrigal is a visiting scholar at the University of California at Berkeley's Office for the History of Science and Technology. Born in Mexico City, he grew up in the exurbs north of Portland, Oregon, and now lives in Oakland.

iPhones Everywhere: Measuring Your 'Tango Walk'

By Alexis Madrigal
Aug 1 2010, 2:40 PM ET Comment

In some previous phase, perhaps to reconnect with my Latin roots, I signed up for a tango class. I never actually went, but that moment of inspiration landed me on Portland dance teacher Clay Nelson's email list.

For years, I idly meant to get off of the e-mail list: I don't tango and I don't live in Portland, and even if I did, I don't think I would need regular updates about the union of that Venn diagram.

But I never quite hit the unsubscribe link. This morning, my laziness and/or faith have been rewarded. Nelson's latest missive arrived with the subject: "Using an iPhone to measure your tango walk." In it, he describes his recently completed paper on using the device's accelerometers to measure the smoothness of one's tango walk. That, in turn, is a good proxy for dance skill, Nelson argues.

"Generally speaking, a smoother walk will result in lower acceleration readings, and, although of a more subjective nature, there also appears to be a correlation in the smoothness of a person's walk (low acceleration readings) and the experience and proficiency of the dancer," he wrote.

Turns out Nelson got a PhD in theoretical and applied mechanics at the University of Illinois, so the accompanying paper details his methodology [pdf] and app choice (AccelGraph) with generous helpings of charts and descriptions. Here's one:

tango_600.jpg

"Note that the lines start fairly smooth as the subject stands still for the first 4 counts. After this smooth part, the walking motion is easily detected on the graph. Note also that the average 'Up & Down' motion is displaced in the negative direction by a magnitude of approximately 1.0," Nelson explained. "This is a result of gravity pulling in the downward direction. Note also that the 'Side to Side' and 'Start & Stop' motion do not average around zero as they should. This is because the iPhone was not held in a perfectly vertically aligned position. Thus there is a small component of the gravity vector acting in these other two directions."

A good Sunday morning reminder that if you put tools in people's hands, they'll do things with them you could never have anticipated.


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