title: The development and concurrent validity of a real-time algorithm for temporal gait analysis using inertial measurement units.
abstract: The use of inertial measurement units (IMUs) for gait analysis has emerged as a tool for clinical applications. Shank gyroscope signals have been utilized to identify heel-strike and toe-off, which serve as the foundation for calculating temporal parameters of gait such as single and double limb support time. Recent publications have shown that toe-off occurs later than predicted by the dual minima method (DMM), which has been adopted as an IMU-based gait event detection algorithm.In this study, a real-time algorithm, Noise-Zero Crossing (NZC), was developed to accurately compute temporal gait parameters. Our objective was to determine the concurrent validity of temporal gait parameters derived from the NZC algorithm against parameters measured by an instrumented walkway. The accuracy and precision of temporal gait parameters derived using NZC were compared to those derived using the DMM. The results from Bland-Altman Analysis showed that the NZC algorithm had excellent agreement with the instrumented walkway for identifying the temporal gait parameters of Gait Cycle Time (GCT), Single Limb Support (SLS) time, and Double Limb Support (DLS) time. By utilizing the moment of zero shank angular velocity to identify toe-off, the NZC algorithm performed better than the DMM algorithm in measuring SLS and DLS times. Utilizing the NZC algorithm's gait event detection preserves DLS time, which has significant clinical implications for pathologic gait assessment.
authors.affiliation: University of Miami, Department of Biomedical Engineering, Coral Gables, FL, USA.
authors.forename: E
authors.initials: E
authors.lastname: Allseits
authors.affiliation: University of Miami, Miller School of Medicine, Department of Physical Therapy, Miami, FL, USA; Miami Department of Veterans Affairs Healthcare System, Miami, FL, USA.
authors.forename: J
authors.initials: J
authors.lastname: Lučarević
authors.affiliation: University of Miami, Miller School of Medicine, Department of Physical Therapy, Miami, FL, USA.
authors.forename: R
authors.initials: R
authors.lastname: Gailey
authors.affiliation: University of Miami, Miller School of Medicine, Department of Physical Therapy, Miami, FL, USA; University of Miami, Department of Biomedical Engineering, Coral Gables, FL, USA.
authors.forename: V
authors.initials: V
authors.lastname: Agrawal
authors.affiliation: University of Miami, Miller School of Medicine, Department of Physical Therapy, Miami, FL, USA; Miami Department of Veterans Affairs Healthcare System, Miami, FL, USA.
authors.forename: I
authors.initials: I
authors.lastname: Gaunaurd
authors.affiliation: University of Miami, Frost School of Music, Music Engineering Technology, Coral Gables, FL, USA. Electronic address: bennett@miami.edu.
authors.forename: C
authors.initials: C
authors.lastname: Bennett
mesh_terms: D000328:Adult; D000465:Algorithms; D005121:Extremities / Q000502:physiology; D005260:Female; D005684:Gait / Q000502:physiology; D006365:Heel / Q000502:physiology; D006801:Humans; D008297:Male; D008875:Middle Aged; D008991:Monitoring, Physiologic; D013997:Time Factors; D055815:Young Adult
keywords: Gait analysis; Inertial measurement unit; Real-time; Temporal gait parameters; Toe-off identification