Automated method to distinguish toe walking strides from normal strides in the gait of idiopathic toe walking children from heel accelerometry data

Abstract

Toe walking mainly occurs in children due to medical condition or physical injury. When there are no obvious signs of any medical condition or physical injury, a diagnosis of Idiopathic Toe Walking (ITW) is made. ITW children habitually walk on their toes, however can modify their gait and walk with a heel–toe gait if they want to. Correct gait assessment in ITW children therefore becomes difficult. To solve this problem, we have developed an automated way to assess the gait in ITW children using a dual axis accelerometer. Heel acceleration data was recorded from the gait of ITW children using boots embedded with the sensor in the heel and interfaced to a handheld oscilloscope. An innovative signal processing algorithm was developed in IgorPro to distinguish toe walking stride from normal stride using the acceleration data. The algorithm had an accuracy of 98.5%. Based on the statistical analysis of the heel accelerometer data, it can be concluded that the foot angle during mid stance in ITW children tested, varied from 36° to 11.5° while as in normal children the foot stance angle is approximately zero. This algorithm was later implemented in a system (embedded in the heel) which was used remotely to differentiate toe walking stride from normal stride. Although the algorithm classifies toe walking stride from normal stride in ITW children, it can be generalized for other applications such as toe walking in Cerebral Palsy or Acquired Brain Injury subjects. The system can also be used to assess the gait for other applications such as Parkinson's disease by modifying the algorithm.