A novel validation and calibration method for motion capture systems based on micro-triangulation

Nagymáté, Gergely; Tuchband, Tamás; Kiss, Rita M.

doi:10.1016/j.jbiomech.2018.04.009

Cited by 17 publications

(10 citation statements)

References 9 publications

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“…A similar static wand length check test is proposed, in order to verify the effect of different calibration procedures on performance [ 22 ]. Another proposal to check the absolute accuracy over a 4 × 2.5 × 3 m 3 volume is through a high-precision 3D scanner used for engineering surveying problems [ 23 ]. In [ 24 ], the authors used a ThorLabs LTS300 linear motion capture device in order to evaluate the accuracy of an optical system composed of 42 cameras in a capture volume of 135 m 3 .…”

Section: Introductionmentioning

confidence: 99%

Metrological Evaluation of Human–Robot Collaborative Environments Based on Optical Motion Capture Systems

Gonzalez

Álvarez

López

et al. 2021

Sensors

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In the context of human–robot collaborative shared environments, there has been an increase in the use of optical motion capture (OMC) systems for human motion tracking. The accuracy and precision of OMC technology need to be assessed in order to ensure safe human–robot interactions, but the accuracy specifications provided by manufacturers are easily influenced by various factors affecting the measurements. This article describes a new methodology for the metrological evaluation of a human–robot collaborative environment based on optical motion capture (OMC) systems. Inspired by the ASTM E3064 test guide, and taking advantage of an existing industrial robot in the production cell, the system is evaluated for mean error, error spread, and repeatability. A detailed statistical study of the error distribution across the capture area is carried out, supported by a Mann–Whitney U-test for median comparisons. Based on the results, optimal capture areas for the use of the capture system are suggested. The results of the proposed method show that the metrological characteristics obtained are compatible and comparable in quality to other methods that do not require the intervention of an industrial robot.

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Section: Introductionmentioning

confidence: 99%

Metrological Evaluation of Human–Robot Collaborative Environments Based on Optical Motion Capture Systems

Gonzalez

Álvarez

López

et al. 2021

Sensors

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“…Instant graphical output is provided, including joint angles [31]. OptiTrack is a widely used motion capture system and considered as one of the most accurate [23,24]. These two systems can be regarded as gold standard markerbased systems; they are installed in movement analysis laboratories for the purposes of gait analysis, musculoskeletal research and animation.…”

Section: Validation Of Microsoft Kinect Azure Camera With Xsens Mvn A...mentioning

confidence: 99%

“…Although the previous Kinect version had acceptable applicability in motion analysis [18][19][20], the Kinect Azure system provides higher accuracy [21,22] and is technically comparable to those of standard motion capture systems, OptiTrack or MVN Xsens. [23][24][25][26]. The aim of the current study was to design a reliable assessment method of the single-leg squat (SLS) test with a second generation Kinect Azure 3D camera.…”

Section: Introductionmentioning

confidence: 99%

Kinect Azure–Based Accurate Measurement of Dynamic Valgus Position of the Knee—A Corrigible Predisposing Factor of Osteoarthritis

et al. 2021

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(1) Dynamic knee valgus is a predisposing factor for anterior cruciate ligament rupture and osteoarthritis. The single-leg squat (SLS) test is a widely used movement pattern test in clinical practice that helps to assess the risk of lower-limb injury. We aimed to quantify the SLS test using a marker-less optical system. (2) Kinect validity and accuracy during SLS were established by marker-based OptiTrack and MVN Xsens motion capture systems. Then, 22 individuals with moderate knee symptoms during sports activities (Tegner > 4, Lysholm > 60) performed SLS, and this was recorded and analyzed with a Kinect Azure camera and the Dynaknee software. (3) An optical sensor coupled to an artificial-intelligence-based joint recognition algorithm gave a comparable result to traditional marker-based motion capture devices. The dynamic valgus sign quantified by the Q-angle at the lowest point of the squat is highly dependent on squat depth, which severely limits its comparability among subjects. In contrast, the medio-lateral shift of the knee midpoint at a fixed squat depth, expressed in the percentage of lower limb length, is more suitable to quantify dynamic valgus and compare values among individual patients. (4) The current study identified a new and reliable way of evaluating dynamic valgus of the knee joint by measuring the medial shift of the knee-over-foot at a standardized squat depth. Using a marker-less optical system widens the possibilities of evaluating lower limb functional instabilities for medical professionals.

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“…A key consideration is marker visibility and in this study the optical volume is set up in a configuration so that at least three markers are visible at any point in time [25]. Nagymate et al introduced a novel micro-triangulation-based validation and calibration method for motion capture systems, supporting the volume setup and calibration used in this study [26]. There are several other optical tracking systems such as the one used by Gaspar et al, who introduced an infraredoptical tracking system designed for large scale immersive Virtual Environments or Augmented Reality [27].…”

Section: Related Workmentioning

confidence: 99%

Anatomical Joint Measurement With Application to Medical Robotics

Strydom

Banach

et al. 2020

IEEE Access

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Robotic-assisted orthopaedic procedures demand accurate spatial joint measurements. Tracking of human joint motion is challenging in many applications, such as in sport motion analyses. In orthopaedic surgery, these challenges are even more prevalent, where small errors may cause iatrogenic damage in patients-highlighting the need for robust and precise joint and instrument tracking methods. In this study, we present a novel kinematic modelling approach to track any anatomical points on the femur and / or tibia by exploiting optical tracking measurements combined with a priori computed tomography information. The framework supports simultaneous tracking of anatomical positions, from which we calculate the pose of the leg (joint angles and translations of both the hip and knee joints) and of each of the surgical instruments. Experimental validation on cadaveric data shows that our method is capable of measuring these anatomical regions with sub-millimetre accuracy, with a maximum joint angle uncertainty of ±0.47 o. This study is a fundamental step in robotic orthopaedic research, which can be used as a ground-truth for future research such as automating leg manipulation in orthopaedic procedures.

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A novel validation and calibration method for motion capture systems based on micro-triangulation

Cited by 17 publications

References 9 publications

Metrological Evaluation of Human–Robot Collaborative Environments Based on Optical Motion Capture Systems

Metrological Evaluation of Human–Robot Collaborative Environments Based on Optical Motion Capture Systems

Kinect Azure–Based Accurate Measurement of Dynamic Valgus Position of the Knee—A Corrigible Predisposing Factor of Osteoarthritis

Anatomical Joint Measurement With Application to Medical Robotics

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