A Comparison of Algorithms for Body-Worn Sensor-Based Spatiotemporal Gait Parameters to the GAITRite Electronic Walkway

Greene, Barry R.; Foran, Tim; McGrath, Denise; Doheny, Emer P.; Burns, Adrian; Caulfield, Brian

doi:10.1123/jab.28.3.349

Cited by 40 publications

(43 citation statements)

References 21 publications

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“…Furthermore, we measured spatiotemporal parameters at a rather homogenous speed in our sample and speed might have an impact on accuracy. 10 Spatiotemporal parameters were registered only over a short distance in a controlled setting, and we only included healthy subjects. Reliability and validity (specific parameters) results suggest that the BTS G-WALK ® sensor system might be used in community and athletic settings or clinical studies evaluating treatment effects; however, research in these specific populations is warranted.…”

Section: Discussionmentioning

confidence: 99%

Concurrent Validity of a Commercial Wireless Trunk Triaxial Accelerometer System for Gait Analysis

Ridder¹,

Lebleu²,

Willems³

et al. 2019

Journal of Sport Rehabilitation

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Context: Wearable sensor devices have notable advantages, such as cost-effectiveness, easy to use, and real-time feedback. Wirelessness ensures full-body motion, which is required during movement in a challenging environment such as during sports. Research on the reliability and validity of commercially available systems, however, is indispensable. Objective: To confirm the test–retest reliability and concurrent validity of a commercially available body-worn sensor—BTS G-WALK® sensor system—for spatiotemporal gait parameters with the GAITRite® walkway system as golden standard. Design: Reliability and concurrent validity study. Setting: Laboratory setting. Participants: Thirty healthy subjects. Main Outcome Measures: Spatiotemporal parameters: speed, cadence, stride length, stride duration, stance duration, swing duration, double support, and single support. Results: In terms of test–retest reliability of the BTS G-WALK® sensor system, intraclass correlation coefficient values for both the spatial and temporal parameters were excellent between consecutive measurements on the same day with intraclass correlation coefficient values ranging from .85 to .99. In terms of validity, intraclass correlation coefficient values between measurement systems showed excellent levels of agreement for speed, cadence, stride length, and stride duration (range = .88–.97), and showed poor to moderate levels of agreement (range = .12–.47) for single/double support and swing/stance duration. Bland–Altman plots showed overall percentage bias values equal to or smaller than 3% with limits of agreement ≤15% (speed, cadence, stride length, stride duration, swing duration, and stance duration). Only for single and double support, the limits of agreement were higher with, respectively, −15.4% to 19.5% and −48.0% to 51.4%. Conclusion: The BTS G-WALK® sensor system is reliable for all measured spatiotemporal parameters. In terms of validity, excellent concurrent validity was shown for speed, cadence, stride length, and stride duration. Cautious interpretation is necessary for temporal parameters based on final foot contact (stance, swing, and single/double support time).

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Section: Discussionmentioning

confidence: 99%

Concurrent Validity of a Commercial Wireless Trunk Triaxial Accelerometer System for Gait Analysis

Ridder¹,

Lebleu²,

Willems³

et al. 2019

Journal of Sport Rehabilitation

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“…The advantage of a 3D gait analysis is that provides extensive data that includes kinematics and kinetics, which often gait assessment tools that record spatio-temporal parameters alone, do not provide. There are commercially available gait assessment tools that can record spatio-temporal gait parameters such as instrumented mats with pressure sensors [10] and body worn sensors that incorporate accelerometers [11]. The limitations of these systems include difficulties in set-up within a clinical environment, where space is often limited, and although they may not be as expensive as the 3D gait analysis system, they are still costly for individual departments or independent rehabilitation clinics to utilize in providing a cost effective clinical assessment.…”

Section: Introductionmentioning

confidence: 99%

Development and validation of a low-cost, portable and wireless gait assessment tool

Macleod

Conway

Allan

et al. 2014

Medical Engineering & Physics

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“…Good gait speed agreement has also been shown between a Multi-Kinect v2 Instrumented 10-Meter Walkway and motion capture [19] (0.011 m/s for comfortable walking speed and 0.006 m/s for fast walking speed), between a GAITRite mat and body-worn sensors [20] (0.024 m/s for slow, -0.050 m/s for normal, and -0.302 m/s for fast walking speeds), and between Microsoft Xbox One Kinect and motion capture [21] (0.010 m/s for comfortable walking speed, and 0.000 m/s for fast walking speed). The 95% LOA, for all studies that reported them, were relatively narrow and comparable to what was observed here.…”

Section: Walk Testmentioning

confidence: 75%

Validity and feasibility of a cell phone application for the assessment of gait and other functional fitness outcomes

Salvatore¹,

Miller²,

Green³

et al. 2018

Phys Ther Rehabil

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Background: Our lab previously demonstrated that the manual assessment (with a cell phone stopwatch) of the 30-s Chair Stand, 8-ft Up-and-Go, and 6 Minute Walk Test was as or more valid and reliable than using body-worn sensors. Based on this finding, we developed an Android cell phone application (App) to improve the feasibility of data collection and to automatically calculate outcomes. The main purpose of the present study was to validate the App against slow-motion video analysis for the assessment of outcomes from the 30-s Chair Stand, 8-ft Up-and-Go, and 400 m Walk Test. Methods: A subset of 15 subjects were randomly selected from our larger Steps Taken Against Neuromuscular Decline (STAND) Initiative cohort for this validity assessment. Each subject completed a single trial of the 30-s Chair Stand, 8-ft Up-and-Go, and 400 m Walk Test (in that order). One investigator assessed the subject using the App, while another filmed the test at 240 frames per second. The videos were played back frame-by-frame to manually timestamp the same events that were timestamped live using the App. The mean difference between the App and video (bias) was assessed with paired t-tests, and 95% Limits of Agreement were established to represent the random error between the two measures. Results: No significant bias between the App and slow-motion video was detected for any 30-s Chair Stand or 400 m Walk Test outcome, or for the total time taken to complete the 8-ft Up-and-Go. Paired t-tests did, however, suggest a numerically small but systematic negative bias for all other 8-ft Up-and-Go outcomes, indicating that subcomponents of the 8-ft Up-and-Go are slightly faster when being assessed by the App, compared with slow-motion video. The 95% Limits of Agreement were most narrow for the 30-s Chair Stand and 400 m Walk Test components, as well as total time on the 8-ft Up-and-Go, with a broader limits for other 8-ft Up-and-Go components. Conclusions: The App validly assessed all 30-s Chair Stand and 400 m Walk Test outcomes, as well as the total time taken to complete the 8-ft Up-and-Go. Given that the App is as or more valid than existing technologies, with respect to the outcomes it reports, its greater feasibility may make it an appropriate addition to clinical and fitness settings.

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A Comparison of Algorithms for Body-Worn Sensor-Based Spatiotemporal Gait Parameters to the GAITRite Electronic Walkway

Cited by 40 publications

References 21 publications

Concurrent Validity of a Commercial Wireless Trunk Triaxial Accelerometer System for Gait Analysis

Concurrent Validity of a Commercial Wireless Trunk Triaxial Accelerometer System for Gait Analysis

Development and validation of a low-cost, portable and wireless gait assessment tool

Validity and feasibility of a cell phone application for the assessment of gait and other functional fitness outcomes

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