Disease Detecting Apps for Mobile

Disease Detecting Apps for Mobile. Mobile trend has affected the field of medicine. New technology of detecting Parkinson’s disease by using phone is being developed through The Parkinson’s Voice Initiative, a project aimed to help people with Parkinson’s disease.

The project is pioneered by Max Little, a math scientist from Oxford University, UK. He develops algorithm to detect abnormal voice which is a helpful detector of Parkinson’s disease.

Parkinson’s disease is a degenerative disorder of the central nervous system. Generally, those in the middle to later years i.e. 50-75 are affected. The disease was named after Dr. James Parkinson who described the symptoms of the disease in “An Essay on the Shaking Palsy” in 1817. The essay was based on six cases he had observed in his own practice and on walks around his neighborhood.

The most obvious symptoms of the disease are movement-related; these include shaking, rigidity, slowness of movement and difficulty with walking and gait. Later, cognitive and behavioral problems may arise, with dementia commonly occurring in the advanced stages of the disease. Other symptoms include sensory, sleep and emotional problems.

Sometimes it is hard to diagnose this diseases since the disease develop slowly. Most people with Parkinson’s disease begin to experience shaking of certain limbs when they get exhausted.

Max Little and his team had tested the apps they developed. They detected the voices of people with Parkinson’s disease. According to Little, the accuracy rate is high, it is 86%. Now, they are analyzing 10,000 voice samples that they collected through telephone.

In other countries, various mobile apps are developed to detect diseases, too. The Wall Street Journal reported that the researchers of University of Pittsburgh Medical Center are testing 4 apps to analyze hundreds of mole images and flexes which have been examined by skin disease experts.

The best apps are capable of detecting skin diseases, including skin cancer, with accuracy rate reaches 98%. In the other hand, the poorest apps only reach 6.8% of accuracy rate. Unfortunately, the researchers did not mention the tested apps’ names.

Formerly, a mobile app was developed to detect lungs diseases. The app was calledSpiroSmart and developed by the researchers from University of Washington. SpiroSmart analyzes lip reverberation of the users to monitor pulmonary ailments such as asthma, chronic obstructive pulmonary disease, and cystic fibrosis.

Besides, the researchers also use social networking apps such as Twitter, to detect diseases. The researchers from John Hopkins University detect influenza cases in US by identifying tweets saying about influenza from users. The tweets are to map the spots influenza spreads.

Those apps are helpful to detect disease early, but even the best apps cannot replace doctors’ roles.