BACKGROUND: Diagnosing @entity75 , such as @entity191 ( @entity191 ) or @entity195 , is often difficult, especially in the early stages. Moreover, it has been estimated that nearly 40% of @entity1 with @entity191 may not be diagnosed. Traditionally, the diagnosis of @entity16 , such as @entity191 , often required a doctor to observe the @entity1 over time to recognize signs of @entity2003 in movement. MATERIALS AND METHODS: The pedestrian dead reckoning (PDR) system is a self-contained technique that has been widely used for indoor localization. In this work we propose a PDR-based method to continuously monitor and record the @entity1 's gait characteristics using a smartphone. Seventeen @entity1 were studied over a period of 1 year. During the year it became apparent that 1 of the @entity1 was actually developing @entity191 . To the best of our knowledge, our work is the first attempt to use sensors in a smartphone to help identify @entity1 in their early stages of @entity16 . RESULTS: On average, the accuracy of our step length estimation was about 98%. Using a binary classification method-namely, support vector machine-we carried out a case study and showed that it was feasible to identify changes in the walking patterns of a @entity191 @entity1 with an accuracy of 94%. CONCLUSIONS: Using 1 year of gait trace data obtained from the users' phones, our work provides a first step to experimentally show the possibility of applying smartphone sensor data to provide early warnings to potential @entity191 @entity1 to encourage them to seek medical assistance and thus help doctors diagnose this disease earlier.

Gait Monitoring for Early XXXX Detection Using Sensors in a Smartphone: Validation and a Case Study of Parkinsonism.

@entity1 :: ('9606', 'Species') :: ['patients', 'patient', 'people'] @entity2003 :: ('MESH:D009127', 'Disease') :: ['rigidity'] @entity75 :: ('MESH:D001927', 'Disease') :: ['brain disorders'] @entity16 :: ('MESH:D009422', 'Disease') :: ['neurological disorders', 'neurological disease'] @entity191 :: ('MESH:D010300', 'Disease') :: ["Parkinson's disease", 'PD'] @entity195 :: ('MESH:D000544', 'Disease') :: ["Alzheimer's disease"]
@entity16 :: (MESH:D009422,Disease) :: ['Neurological Disorder']
