Real-time, accurate, and open source upper-limb musculoskeletal analysis using a single RGBD camera

• URL: http://arxiv.org/abs/2406.10007v1
• Date: Fri, 14 Jun 2024 13:20:05 GMT
• Title: Real-time, accurate, and open source upper-limb musculoskeletal analysis using a single RGBD camera
• Authors: Amedeo Ceglia, Kael Facon, Mickaël Begon, Lama Seoud,
• Abstract summary: Biomechanical biofeedback may enhance rehabilitation and provide clinicians with more objective task evaluation. Our open-source approach offers a user-friendly solution for high-fidelity upper-limb kinematics using a single low-cost RGBD camera.
• Score: 0.14999444543328289
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Biomechanical biofeedback may enhance rehabilitation and provide clinicians with more objective task evaluation. These feedbacks often rely on expensive motion capture systems, which restricts their widespread use, leading to the development of computer vision-based methods. These methods are subject to large joint angle errors, considering the upper limb, and exclude the scapula and clavicle motion in the analysis. Our open-source approach offers a user-friendly solution for high-fidelity upper-limb kinematics using a single low-cost RGBD camera and includes semi-automatic skin marker labeling. Real-time biomechanical analysis, ranging from kinematics to muscle force estimation, was conducted on eight participants performing a hand-cycling motion to demonstrate the applicability of our approach on the upper limb. Markers were recorded by the RGBD camera and an optoelectronic camera system, considered as a reference. Muscle activity and external load were recorded using eight EMG and instrumented hand pedals, respectively. Bland-Altman analysis revealed significant agreements in the 3D markers' positions between the two motion capture methods, with errors averaging 3.3$\pm$3.9 mm. For the biomechanical analysis, the level of agreement was sensitive to whether the same marker set was used. For example, joint angle differences averaging 2.3$\pm$2.8{\deg} when using the same marker set, compared to 4.5$\pm$2.9{\deg} otherwise. Biofeedback from the RGBD camera was provided at 63 Hz. Our study introduces a novel method for using an RGBD camera as a low-cost motion capture solution, emphasizing its potential for accurate kinematic reconstruction and comprehensive upper-limb biomechanical studies.

Related papers

• COIN: Control-Inpainting Diffusion Prior for Human and Camera Motion Estimation [98.05046790227561]
  COIN is a control-inpainting motion diffusion prior that enables fine-grained control to disentangle human and camera motions. COIN outperforms the state-of-the-art methods in terms of global human motion estimation and camera motion estimation.
  arXiv  Detail & Related papers  (2024-08-29T10:36:29Z)
• OpenCap markerless motion capture estimation of lower extremity kinematics and dynamics in cycling [0.0]
  Markerless motion capture offers several benefits over traditional marker-based systems. System can directly detect human body landmarks, reducing manual processing and errors associated with marker placement. This study compares the performance of OpenCap, a markerless motion capture system, with traditional marker-based systems in assessing cycling biomechanics.
  arXiv  Detail & Related papers  (2024-08-20T15:57:40Z)
• MS-MANO: Enabling Hand Pose Tracking with Biomechanical Constraints [50.61346764110482]
  We integrate a musculoskeletal system with a learnable parametric hand model, MANO, to create MS-MANO. This model emulates the dynamics of muscles and tendons to drive the skeletal system, imposing physiologically realistic constraints on the resulting torque trajectories. We also propose a simulation-in-the-loop pose refinement framework, BioPR, that refines the initial estimated pose through a multi-layer perceptron network.
  arXiv  Detail & Related papers  (2024-04-16T02:18:18Z)
• 3D Kinematics Estimation from Video with a Biomechanical Model and Synthetic Training Data [4.130944152992895]
  We propose a novel biomechanics-aware network that directly outputs 3D kinematics from two input views. Our experiments demonstrate that the proposed approach, only trained on synthetic data, outperforms previous state-of-the-art methods.
  arXiv  Detail & Related papers  (2024-02-20T17:33:40Z)
• SDGE: Stereo Guided Depth Estimation for 360$^\circ$ Camera Sets [65.64958606221069]
  Multi-camera systems are often used in autonomous driving to achieve a 360$circ$ perception. These 360$circ$ camera sets often have limited or low-quality overlap regions, making multi-view stereo methods infeasible for the entire image. We propose the Stereo Guided Depth Estimation (SGDE) method, which enhances depth estimation of the full image by explicitly utilizing multi-view stereo results on the overlap.
  arXiv  Detail & Related papers  (2024-02-19T02:41:37Z)
• W-HMR: Monocular Human Mesh Recovery in World Space with Weak-Supervised Calibration [57.37135310143126]
  Previous methods for 3D motion recovery from monocular images often fall short due to reliance on camera coordinates. We introduce W-HMR, a weak-supervised calibration method that predicts "reasonable" focal lengths based on body distortion information. We also present the OrientCorrect module, which corrects body orientation for plausible reconstructions in world space.
  arXiv  Detail & Related papers  (2023-11-29T09:02:07Z)
• Next-generation Surgical Navigation: Marker-less Multi-view 6DoF Pose Estimation of Surgical Instruments [66.74633676595889]
  We present a multi-camera capture setup consisting of static and head-mounted cameras. Second, we publish a multi-view RGB-D video dataset of ex-vivo spine surgeries, captured in a surgical wet lab and a real operating theatre. Third, we evaluate three state-of-the-art single-view and multi-view methods for the task of 6DoF pose estimation of surgical instruments.
  arXiv  Detail & Related papers  (2023-05-05T13:42:19Z)
• Human Leg Motion Tracking by Fusing IMUs and RGB Camera Data Using Extended Kalman Filter [4.189643331553922]
  IMU-based systems, as well as Marker-based motion tracking systems, are the most popular methods to track movement due to their low cost of implementation and lightweight. This paper proposes a quaternion-based Extended Kalman filter approach to recover the human leg segments motions with a set of IMU sensors data fused with camera-marker system data.
  arXiv  Detail & Related papers  (2020-11-01T17:54:53Z)
• Inertial Measurements for Motion Compensation in Weight-bearing Cone-beam CT of the Knee [6.7461735822055715]
  Involuntary motion during CT scans of the knee causes artifacts in the reconstructed volumes making them unusable for clinical diagnosis. We propose to attach an inertial measurement unit (IMU) to the leg of the subject in order to measure the motion during the scan and correct for it.
  arXiv  Detail & Related papers  (2020-07-09T09:26:27Z)
• Road Curb Detection and Localization with Monocular Forward-view Vehicle Camera [74.45649274085447]
  We propose a robust method for estimating road curb 3D parameters using a calibrated monocular camera equipped with a fisheye lens. Our approach is able to estimate the vehicle to curb distance in real time with mean accuracy of more than 90%.
  arXiv  Detail & Related papers  (2020-02-28T00:24:18Z)
• A Single RGB Camera Based Gait Analysis with a Mobile Tele-Robot for Healthcare [9.992387025633805]
  This work focuses on the analysis of gait, which is widely adopted for joint correction and assessing any lower limb or spinal problem. On the hardware side, we design a novel marker-less gait analysis device using a low-cost RGB camera mounted on a mobile tele-robot.
  arXiv  Detail & Related papers  (2020-02-11T21:42:22Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.