title: A computational algorithm for classifying step and spin turns using pelvic center of mass trajectory and foot position.
abstract: Transient changes in direction during ambulation are typically performed using a step (outside) or spin (inside) turning strategy, often identified through subjective and time-consuming visual rating. Here, we present a computational, marker-based classification method utilizing pelvic center of mass (pCOM) trajectory and time-distance parameters to quantitatively identify turning strategy. Relative to visual evaluation by three independent raters, sensitivity, specificity, and overall accuracy of the pCOM-based classification method were evaluated for 90-degree turns performed by 3 separate populations (5 uninjured controls, 5 persons with transtibial amputation, and 5 persons with transfemoral amputation); each completed turns using two distinct cueing paradigms (i.e., laser-guided "freeform" and verbally-guided "forced" turns). Secondarily, we compared the pCOM-based turn classification method to adapted versions of two existing computational turn classifiers which utilize trunk and shank angular velocities (AV). Among 366 (of 486 total) turns with unanimous intra- and inter-rater agreement, the pCOM-based classification algorithm was 94.5% accurate, with 96.6% sensitivity (accuracy of spin turn classification), and 93.5% specificity (accuracy of step turn classification). The pCOM-based algorithm (vs. both AV-based methods) was more accurate (94.5% vs. 81.1-80.6%; P<0.001) overall, as well as specifically in freeform (92.9 vs. 80.4-76.8%; P<0.003) and forced (96.0 vs. 83.8-81.8%; P<0.001) cueing, and among individuals with (92.4 vs. 80.2-78.8%; P<0.001) and without (99.1 vs. 86.2-80.8%; P<0.001) amputation. The pCOM-based algorithm provides an efficient and objective method to accurately classify 90-degree turning strategies using optical motion capture in a laboratory setting, and may be extended to various cueing paradigms and/or populations with altered gait.
authors.affiliation: Research & Development Section, Department of Rehabilitation, Walter Reed National Military Medical Center, Bethesda, MD 20889, USA.
authors.forename: Pawel R
authors.initials: PR
authors.lastname: Golyski
authors.affiliation: Research & Development Section, Department of Rehabilitation, Walter Reed National Military Medical Center, Bethesda, MD 20889, USA; Department of Rehabilitation Medicine, Uniformed Services University of Health Sciences, Bethesda, MD 20814, USA; DOD/VA Extremity Trauma and Amputation Center of Excellence, Walter Reed National Military Medical Center, Bethesda, MD 20889, USA. Electronic address: bradford.hendershot@gmail.com.
authors.forename: Brad D
authors.initials: BD
authors.lastname: Hendershot
mesh_terms: D000328:Adult; D000465:Algorithms; D000671:Amputation, Surgical; D001696:Biomechanical Phenomena; D005260:Female; D005528:Foot / Q000502:physiology*; D006801:Humans; D008297:Male; D010388:Pelvis / Q000502:physiology*; D012680:Sensitivity and Specificity; D060726:Torso / Q000502:physiology; D016138:Walking / Q000502:physiology*; D055815:Young Adult
keywords: Amputation; Biomechanics; Freeform; Gait classification; Turning