Evaluation of Gait Parameters using Wearable Sensors in Simulated Freezing of Gait Episodes

Background and Hypothesis: Freezing of gait (FoG), the failure to initiate or maintain locomotion, is a common symptom in Parkinsonism that severely impacts patients’ quality life. Wearable technology such as inertial measurement units (IMU) are being widely investigated method detecting these episodes with increasing sensitivity specificity. The aim this initial study collect objective data using IMU sensors via Perception Neuron software develop an analysis pipeline for quick in-clinic calculation parameters.
 Experimental Design: 16 IMU’s were attached feet, legs, arms, waist, back, head individuals without any abnormalities. Subjects instructed walk 10 meters normally, followed by interspersed, simulated FoG episodes. This was processed analyzed through Axis Studio MATLAB identify kinematic markers associated gait. correlation between right left foot gyroscopic z-axis determined plotted against time, less than 0.5 considered episode. Further, parameters including stride duration, stance swing length calculated from input raw establish control comparison future studies Parkinson’s patients.
 Results: Data demonstrated increased duration shorter stimulated compared normal developed code further able accurately distinguish given parameter difference <0.5.
 Conclusion: Our findings showed obtained can be succinctly detect calculate parameters. Ultimately, will used baseline investigating use spinal cord stimulation treatment Disease.