Agreement Analysis between Vive and Vicon Systems to Monitor Lumbar Postural Changes

Veen, Susanne M. van der; Bordeleau, Maude; Pidcoe, Peter E.; Thomas, James S.

doi:10.3390/s19173632

Cited by 30 publications

(42 citation statements)

References 26 publications

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“…In the publication by van der Veen [ 11 ], the lighthouse system has been used in a typical setup with two lighthouses in a dynamic test setup. Due to the high influence of the dynamic tracking algorithm of SteamVR in this test setup, these results are representative for a dynamic use case but may underestimate the reachable accuracy level of the Vive Tracker itself.…”

Section: Testing Environmentmentioning

confidence: 99%

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Accuracy Investigation of the Pose Determination of a VR System

Bauer

Lienhart

Jost

2021

Sensors

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The usage of VR gear in mixed reality applications demands a high position and orientation accuracy of all devices to achieve a satisfying user experience. This paper investigates the system behaviour of the VR system HTC Vive Pro at a testing facility that is designed for the calibration of highly accurate positioning instruments like geodetic total stations, tilt sensors, geodetic gyroscopes or industrial laser scanners. Although the experiments show a high reproducibility of the position readings within a few millimetres, the VR system has systematic effects with magnitudes of several centimetres. A tilt of about 0.4∘ of the reference plane with respect to the horizontal plane was detected. Moreover, our results demonstrate that the tracking algorithm faces problems when several lighthouses are used.

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Section: Testing Environmentmentioning

confidence: 99%

“…In 2019, a team of researchers around van der Veen investigated the position accuracy of the HTC Vive Tracker in a dynamic 3D setup [ 11 ]. In their test setup, the tracker was placed on a movable robot arm.…”

Section: Introductionmentioning

confidence: 99%

Accuracy Investigation of the Pose Determination of a VR System

Bauer

Lienhart

Jost

2021

Sensors

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“…The pose estimates of any Vive headset, controller, or tracker, each of which contains an array of strategically placed photodiodes, in this area are computed and tracked by the VR system. When using the trackers, the Vive was capable of estimating positions and orientations that agree with estimations made by a more expensive, marker-based optical tracking system (Vicon) [34]. Because the Vive is designed as a portable consumer device, this VR system can be used to track human pose in a variety of environments without being susceptible to magnetic elds as are IMUs, at the expense of a slightly longer setup time requirement.…”

Section: Introductionmentioning

confidence: 88%

Estimation of arm kinematics in stroke survivors using wearable sensors

Nie¹,

Nie²,

Hung³

et al. 2021

Preprint

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BackgroundStroke is the leading cause of long-term disability in the United States, often resulting in upper extremity (UE) motor impairment. Most existing outcome metrics of UE function in rehabilitation are insensitive to change or subject to observer bias. There is growing interest in using movement kinematics to measure UE motor function, since they can provide high-resolution, quantitative measurements. However, measuring arm kinematics in stroke survivors, particularly in the hospital or clinic, can be challenging for traditional optical tracking systems due to non-ideal environments, expense, and a limited ability to perform required calibration poses. The aim of this study was to develop a general framework for accurate measurements of wrist position during reaching movements in people with stroke using relatively inexpensive wearable sensors.MethodsWe developed and presented two methods, one using inertial measurement units (IMUs) and using virtual reality (Vive) sensors, that practically estimate wrist position with respect to the shoulder. We then assessed the estimation accuracies of each method during a 3D reaching task by using a Vicon motion capture system. We also demonstrated each methods ability to track two kinematic metrics, sweep area and smoothness, in chronic stroke survivors. We computed Pearson correlation coefficients when appropriate.ResultsCompared to a traditional optical system, both systems tracked with high accuracy during 3D reaching, with mean absolute errors of 1.00 ± 0.80 cm and 1.09 ± 0.51 cm for the IMU and Vive, respectively. Furthermore, both methods’ estimated kinematics highly agreed with each other (p < 0.01).ConclusionsThese methods may be useful for developing kinematic metrics to evaluate stroke rehabilitation outcomes in both laboratory and clinical environments.Trial RegistrationThe clinical trial (ClinicalTrial.gov ID: NCT03401762) was registered on January 17, 2018 (https://clinicaltrials.gov/ct2/show/NCT03401762) and posted on January 1, 2018. The trial is scheduled to be completed by August 2023. The trial was updated on December 2, 2020 and is currently recruiting.

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“…The comparison showed that 3D tracking was accurate within (0.7 ± 0.3) cm translationally and (1.64 ± 0.18)° rotationally. This results suggest that VR sensors can be used to accurately track joint motion for clinical and research applications, although accuracy on extracted parameters was not discussed [ 26 ].…”

Section: Introductionmentioning

confidence: 99%

“…IMU-based setups may show good accuracy in tracking human motions, however, specific sensor fusion algorithms are usually needed to achieve that performance [ 6 ]. Although, VR systems are spatially limited (they must be used indoors and calibrated), they do provide a more consistent and reliable position tracking since they, unlike IMUs, directly provide displacement information [ 26 ]. Furthermore, VR trackers can be used for long-term data acquisition without the added complexity for incorporating additional trackers [ 27 ].…”

Section: Introductionmentioning

confidence: 99%

Evaluating the Accuracy of Virtual Reality Trackers for Computing Spatiotemporal Gait Parameters

Guaitolini

Petros

Prado

et al. 2021

Sensors

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Ageing, disease, and injuries result in movement defects that affect daily life. Gait analysis is a vital tool for understanding and evaluating these movement dysfunctions. In recent years, the use of virtual reality (VR) to observe motion and offer augmented clinical care has increased. Although VR-based methodologies have shown benefits in improving gait functions, their validity against more traditional methods (e.g., cameras or instrumented walkways) is yet to be established. In this work, we propose a procedure aimed at testing the accuracy and viability of a VIVE Virtual Reality system for gait analysis. Seven young healthy subjects were asked to walk along an instrumented walkway while wearing VR trackers. Heel strike (HS) and toe off (TO) events were assessed using the VIVE system and the instrumented walkway, along with stride length (SL), stride time (ST), stride width (SW), stride velocity (SV), and stance/swing percentage (STC, SWC%). Results from the VR were compared with the instrumented walkway in terms of detection offset for time events and root mean square error (RMSE) for gait features. An absolute offset between VR- and walkway-based data of (15.3 ± 12.8) ms for HS, (17.6 ± 14.8) ms for TOs and an RMSE of 2.6 cm for SW, 2.0 cm for SL, 17.4 ms for ST, 2.2 m/s for SV, and 2.1% for stance and swing percentage were obtained. Our findings show VR-based systems can accurately monitor gait while also offering new perspectives for VR augmented analysis.

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Agreement Analysis between Vive and Vicon Systems to Monitor Lumbar Postural Changes

Cited by 30 publications

References 26 publications

Accuracy Investigation of the Pose Determination of a VR System

Accuracy Investigation of the Pose Determination of a VR System

Estimation of arm kinematics in stroke survivors using wearable sensors

Evaluating the Accuracy of Virtual Reality Trackers for Computing Spatiotemporal Gait Parameters

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