A new iPhone app can diagnose the differences between severe, mild and faked alcohol withdrawal symptoms, all of which are major issues in hospital emergency rooms.
Developed by Parham Aarabi, a professor in the Edward S. Rogers Sr. Department of Electrical & Computer Engineering, in partnership with Mount Sinai Hospital, the app uses the phone’s motion detector to measure the intensity, frequency and consistency of withdrawal-caused body tremors as the patient holds the phone.
The app analyzes the measurements to determine whether someone needs psychoactive medications to treat their withdrawal, or whether they are merely gaming the system to gain access to the drugs.
“We can determine whether the person has a real tremor – and can tell when someone is faking it or is faking it,” Aarabi says. “And if they have a real tremor, how severe is it? Are they in severe alcohol withdrawal or is it more subtle?”
Currently, diagnosis is labour intensive, requiring multiple measurements spread out over several hours. Aarabi’s app makes collecting and analyzing measurements easier.
Tremor frequencies tend to be higher among genuine sufferers than fakers, Aarabi says. But the most illuminating data concern consistency. “Real tremors are more constant,” he says. “Fake tremors tend to vary a lot more. Initially they are more intense, and as time goes on, the person becomes tired, and the tremors become less intense.”
The app is currently being evaluated and fine-tuned at several Toronto hospitals. “The app in its current form is on par with a junior physician, slightly less accurate than a senior physician,” Aarabi says. He and his team are already working on improvements, as well as seeking additional applications. “One direction I’m interested in is expanding this to diagnosing and assessing other tremor-related diseases like Parkinson’s.”
Once medically validated, the app will be available for free.