Elsevier

Journal of Biomechanics

Volume 55, 11 April 2017, Pages 27-33
Journal of Biomechanics

The development and concurrent validity of a real-time algorithm for temporal gait analysis using inertial measurement units

https://doi.org/10.1016/j.jbiomech.2017.02.016Get rights and content

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.

Section snippets

Background

Gait analysis provides information related to diagnosing pathology (Andriacchi et al., 1977), fall risk (Maki, 1997) and mortality (Fritz et al., 2009). Advances in technology, which include optical motion capture systems, instrumented walkways, and forceplates, have become gold standards (Najafi, 2011), but their use is constrained by cost, time, and physical space. Body worn inertial measurement units (IMU) have arisen as a low-cost, portable alternative to these traditional systems and holds

Description of shank angular velocity waveform

Gyroscope-derived shank angular velocity during gait has a well-defined, quasi-periodic waveform that consists of a region of positive angular velocity corresponding to advancing the shank relative to the knee and a region of negative angular velocity corresponding to advancing the shank relative to the ground (Fig. 1). In the middle of the negative angular velocity region exists a maximum corresponding to MidStance (MSt) (Hanlon and Anderson, 2009) and in the middle of the positive angular

Subjects and data acquisition

Eleven subjects participated in the study (5 females) with a mean age of 32.4 ± 6.9 yrs (20.3–45.9 yrs), height of 173.4 ± 11.4 cm, and weight of 75.9 ± 23.2 kg. The IMU system captured roughly 6 times as many measurements of GCT and SLS and 3 times as many measurements of DLS as the MatScan (Table 1).

Temporal gait parameters

CoV was calculated for each temporal gait parameter across subjects under the SSWS condition (Table 2). The Wilcoxon sign-ranked test found no significant difference between NZC and the criterion measure

Discussion

The results show that while both NZC and LP yield accurate and precise estimates of GCT, only NZC accurately estimates SLS and DLS time intervals. NZC identifies HS concurrently with LP, validating our earlier hypothesis that mean difference in SLS and DLS times from the instrumented walkway reflects the accuracy of TO event detection. Using Bland-Altman results and Eq. (2), LP identifies TO 170 ms early, while NZC identifies TO only 27 ms (∼1 sample) late, demonstrating that the zero-crossing

Conclusion

The NZC method, although an indirect measure of temporal gait parameters, has been shown to be concurrently valid with the direct measure instrumented walkway. NZC produces stable and repeatable measures of gait event landmarks that yield accurate and precise estimates of gait phase intervals that can be acquired in the subject’s everyday life. The ability of NZC to accurately detect GCT variability and DLS interval times allows for clinicians to utilize an IMU system for gait assessment.

Conflict of interest

All authors declare that there is no proprietary, financial, professional or other personal interest of any nature or kind in any product, service or company that could be construed as influencing the position presented in this manuscript.

Acknowledgments

The Authors would like to thank the Joint Incentive Fund for supporting this work under the DoD-VA Mobile Device Outcomes-based Rehabilitation Program.

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