Introduction:Hindrance in normal movement is common among stroke survivors (SS), leading to a larger prevalence of falling and serious injuries. Current methods for analyzing the movement restrictions (camera-based motion capture) are limited to laboratory/clinical environments. Meanwhile, the presence of Inertial Measurement Unit (IMU) sensors in our everyday lives (e.g., in smartphones) is ever increasing due to their portability, affordability, and accessibility. The purpose of this study was to determine whether a single IMU sensor can differentiate movements between SS and healthy control (HC).Methods:Turning (360°) was selected as the activity since it is a common and complex motion. Data was collected from 12 participants (6 SS, 6 HC) using an IMU sensor (Xsens®) placed on unaffected leg (shank) and was analyzed using a 3-step process: filtration (5 Hz cutoff frequency), segmentation (cycles – consecutive foot placement), and feature extraction. Analyzed features included duration of task (sec), number of cycles, mean angular velocity (deg/sec) of shank per cycle, ratio of stance-time to the duration of task (%), and range of flexion angle (deg) for shank.Results:Obtained values were larger in SS for number of cycles (SS: 5.8, HC: 3.2, p-value<0.01) and duration of task (7.8, 3.4, <0.01). Meanwhile, HC showed higher velocity of shank (unaffected) flexion (1.2, 1.7, <0.01) and the ratio of stance-time to the duration of task (57.7, 32.3, <0.01).Conclusion:A single IMU sensor successfully detected kinematic disparities between two groups. Meanwhile, further work is required to examine the robustness and detection improvements upon using other sensor locations. The use of a single IMU sensor, also present in most smartphones/smartwatches, could enable this accessible technology to be used as a remote assessment/monitoring tool, extending the reach of diagnostic tools and rehabilitation programs.