New pose estimation software has the potential to help neurologists and their patients capture important clinical data using simple tools such as smartphones and tablets, according to a study by Johns Hopkins Medicine, the Kennedy Krieger Institute and the University of Maryland. Human pose estimation is a form of artificial intelligence that automatically detects and labels specific landmarks on the human body, such as elbows and fingers, from simple images or videos.

To measure the speed, rhythm and range of a patient’s motor function, neurologists will often have the patient perform certain repetitive movements, such as tapping fingers or opening and closing hands. An objective assessment of these tests provides the most accurate insight into the severity of a patient’s condition. However, objective motion capture devices are often expensive or only have the ability to measure one type of movement. Therefore, most neurologists must make subjective assessments of their patients’ motor function, usually by simply watching patients as they carry out different tasks.

The new Johns Hopkins-led study sought to find whether pose estimation software developed by the research team could track human motion as accurately as manual, frame-by-frame visual inspections of video recordings of patients performing movements.

The research team had healthy subjects record smartphone video of themselves performing tasks often assigned to neurology patients during motor function assessments: finger taps, hand closures, toe taps, heel taps and hand rotations. Their movements were tracked using a freely available human pose estimation algorithm, then fed into the team’s software for evaluation.

Results showed that across all five tasks, the software accurately detected more than 96% of the movements identified by the manual inspection method. These results held up across several variables, including location, type of smartphone used and method of recording: Some subjects placed their smartphone on a stable surface and hit “record,” while others had a family member or friend hold the device.

The research team’s next step is to test the software on people who require neurological care.

Read the full story: New Software May Help Neurology Patients Capture Clinical Data With Their Own Smartphones