LoJacking Grandma and “Reality Mining,” or “Daddy, What was Anonymity?”
photo by mrsmartino via flickr
Mark Heftler, a geriatric care manager who is slated to begin study at Seton Hall Law in the Fall, has written an interesting article on RFID (Radio Frequency Identification) and its potential usage as a means of early diagnosis of dementia among the elderly. Researchers at the University of South Florida have developed and tested an RFID technology which assesses the walking patterns of those which it monitors.
By monitoring the movements of the elderly within geriatric facilities, “the researchers hope to be able to diagnose the onset Alzheimer’s in their patients. Sudden veers, long pauses, and a tendency to wander are all indicators of dementia.”
As MIT’s Technology Review notes, “Drugs that are currently available can only slow the progression of related diseases, so the earlier dementia is caught, the better a patient’s treatment will be.”
Technology Review also notes, “In particular, dementia increases the risk of injury caused by a fall… ‘That’s a huge problem for assisted-living facilities,’” said William Kearns, an assistant professor who researches aging and mental health at USF.
Not Just Grandma
Although one can readily see the positive cost/benefit and quality of life implications of warding off the falls of the elderly, as Frank Pasquale recently noted on both this blog and Concurring Opinions, the proliferation of “personal” electronic data is not without its danger.
The Technology Review article provides a link to another article which points out that RFID technology is also being harnessed to gather social networking information through what is referred to as “reality mining,”
“…a field that Tanzeem Choudhury pioneered as a PhD student at the MIT Media Lab. Working at Intel after graduation, she created a pager-size sensor pack–loaded with software plus microphones, accelerometers, and other data-gathering devices–to collect and analyze data about human interactions and activity. For instance, by processing verbal utterances, she can identify the most influential people in a social network.
Now an assistant professor of computer science at Dartmouth, Choudhury is conducting experiments with the sensor-laden iPhone. Within a few years, she says, simple versions of her software could be available for cell phones.”
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