The HoloLens Augmented Reality System Provides Valid Measures of Gait Performance in Healthy Adults

Koop, Mandy Miller; Rosenfeldt, Anson B.; Johnston, Joshua; Streicher, Matthew C.; Qu, Jingan; Alberts, Jay L.

doi:10.1109/thms.2020.3016082

Cited by 16 publications

(15 citation statements)

References 32 publications

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“…The results from this project support the hypothesis that biomechanical outcomes characterizing lower extremity function during walking and functional gait, derived from the HL2 and gold standard motion capture, are equivalent to one another. Equivalency between systems support and expand our earlier work, indicating that first-generation HL1 data could be used to evaluate walking patterns [18]. Notably, the participants in the current study walked a substantially greater distance compared to our earlier project (47 m versus 3 m).…”

Section: Discussionsupporting

confidence: 69%

“…Motion data for when an individual ambulated outside the capture volume of the MoCap system were removed from the HL2 dataset. Additional details regarding data synchronization and alignment are provided in our previous publication [18]. The HL2 is an AR headset with four visible light cameras, two infrared cameras, a depth sensor, and an IMU.…”

Section: Equipment Processing and Data Analysismentioning

confidence: 99%

“…Following data alignment, 3D positional data from MoCap markers (right heel, left heel, and markers on the HL2 headset) and 3D positional and rotational data of the headset from the HL2 were used to calculate biomechanical metrics of gait, which included: cumulative distance, number of steps, step and stride length, total time, and gait velocity. Details of the mathematical calculations have been published previously [18].…”

Section: Continuous Gait Biomechanical Variablesmentioning

confidence: 99%

“…We recently completed a validation study of the HL1 motion sensors to characterize gait compared to a 3-dimensional (3D) motion capture (MoCap) system [18]. The results indicated that the 3D position and orientation data from the HL1 resulted in the accurate and reliable calculation of spatiotemporal gait variables (≤5% error) during straight-line walking compared to a MoCap system across multiple walking speeds [18]. The preliminary results were very promising.…”

Section: Introductionmentioning

confidence: 99%

“…The primary aim of this project was to determine whether the data derived from the HL2 characterizing lower extremity function during continuous walking and the TUG were equivalent to the outcomes derived using the gold standard MoCap system. Based on positive pilot studies using the HL1 [16][17][18][19], it was hypothesized that the biomechanical outcomes of gait, turning, and functional mobility from the two systems would be equivalent.…”

Section: Introductionmentioning

confidence: 99%

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The Microsoft HoloLens 2 Provides Accurate Measures of Gait, Turning, and Functional Mobility in Healthy Adults

Koop

Rosenfeldt

Owen

et al. 2022

Sensors

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Augmented-reality (AR) headsets, such as the Microsoft HoloLens 2 (HL2), have the potential to be the next generation of wearable technology as they provide interactive digital stimuli in the context of ecologically-valid daily activities while containing inertial measurement units (IMUs) to objectively quantify the movements of the user. A necessary precursor to the widespread utilization of the HL2 in the fields of movement science and rehabilitation is the rigorous validation of its capacity to generate biomechanical outcomes comparable to gold standard outcomes. This project sought to determine equivalency of kinematic outcomes characterizing lower-extremity function derived from the HL2 and three-dimensional (3D) motion capture systems (MoCap). Sixty-six healthy adults completed two lower-extremity tasks while kinematic data were collected from the HL2 and MoCap: (1) continuous walking and (2) timed up-and-go (TUG). For all the continuous walking metrics (cumulative distance, time, number of steps, step and stride length, and velocity), equivalence testing indicated that the HL2 and MoCap were statistically equivalent (error ≤ 5%). The TUG metrics, including turn duration and turn velocity, were also statistically equivalent between the two systems. The accurate quantification of gait and turning using a wearable such as the HL2 provides initial evidence for its use as a platform for the development and delivery of gait and mobility assessments, including the in-person and remote delivery of highly salient digital movement assessments and rehabilitation protocols.

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Section: Discussionsupporting

confidence: 69%

Section: Equipment Processing and Data Analysismentioning

confidence: 99%

Section: Continuous Gait Biomechanical Variablesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%