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Optical Sensors for the Measurement of Human Posture and Movement

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A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Optical Sensors".

Deadline for manuscript submissions: closed (31 July 2022) | Viewed by 17160

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Special Issue Editor

Prof. Dr. Robert Sitnik

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Guest Editor

Institute of Micromechanics and Photonics, Mechatronics Faculty, Warsaw University of Technology, Św. A. Boboli 8, 520 room, 02-525 Warsaw, Poland
Interests: 3D/4D scanning; multi-modal and multi-directional 3D/4D scanning; 3D/4D data processing; 3D segmentation and recognition; automation of visual sensing processes; automation of 3D digitization
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Special Issue Information

Dear Colleagues,

Recent developments have led to widespread research in the field of optical sensors for measurement of human posture and movement. Such sensors use visible (VIS), near-infrared (NIR) light, or multimodal approaches in a variety of applications to support many medical use cases (posture, surgery, prescreening, etc.), biometrics, computer modeling, and graphics. Unresolved challenges are connected with making highly accurate and fast measurements, the development of multiview approaches, calibration of complex systems, and the maturity of optical sensors in practical conditions, to name a few. The goal of this Special Issue is to invite high-quality, state-of-the-art research papers that deal with challenging issues in optical sensors for measurement of human posture and movement. We solicit original papers of unpublished and completed research that are not currently under review elsewhere. Topics of interest include, but are not limited to, the following:

Development of new sensors for measurement of human posture and/or movement;
Development of methods and algorithms for human posture assessment and/or monitoring;
Applications of optical sensors for human posture estimation in various applications.

Prof. Dr. Robert Sitnik
Guest Editor

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Keywords

measurement of human posture
visible light optical sensors
infrared optical sensors
monitoring of human posture changes
measurement of human posture movement
algorithms for human posture assessment/monitoring
applications of human posture assessment

Published Papers (4 papers)

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31 pages, 22112 KiB

Open AccessArticle

A Novel Approach for Dynamic (4d) Multi-View Stereo System Camera Network Design

by Piotr Osiński, Jakub Markiewicz, Jarosław Nowisz, Michał Remiszewski, Albert Rasiński and Robert Sitnik

Sensors 2022, 22(4), 1576; https://doi.org/10.3390/s22041576 - 17 Feb 2022

Cited by 4 | Viewed by 1997

Abstract

Image network design is a critical factor in image-based 3D shape reconstruction and data processing (especially in the application of combined SfM/MVS methods). This paper aims to present a new approach to designing and planning multi-view imaging networks for dynamic 3D scene reconstruction without preliminary information about object geometry or location. The only constraints are the size of defined measurement volume, the required resolution, and the accuracy of geometric reconstruction. The proposed automatic camera network design method is based on the Monte Carlo algorithm and a set of prediction functions (considering accuracy, density, and completeness of shape reconstruction). This is used to determine the camera positions and orientations and makes it possible to achieve the required completeness of shape, accuracy, and resolution of the final 3D reconstruction. To assess the accuracy and efficiency of the proposed method, tests were carried out on synthetic and real data. For a set of 20 virtual images of rendered spheres, completeness of shape reconstruction was up by 92.3% while maintaining accuracy and resolution at the user-specified level. In the case of the real data, the differences between predictions and evaluations for average density were in the range between 33.8% to 45.0%. Full article

(This article belongs to the Special Issue Optical Sensors for the Measurement of Human Posture and Movement)

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23 pages, 7298 KiB

Open AccessArticle

A Modified Kinematic Model of Shoulder Complex Based on Vicon Motion Capturing System: Generalized GH Joint with Floating Centre

by Chunzhao Zhang, Mingjie Dong, Jianfeng Li and Qiang Cao

Sensors 2020, 20(13), 3713; https://doi.org/10.3390/s20133713 - 02 Jul 2020

Cited by 8 | Viewed by 6066

Abstract

Due to the complex coupling motion of shoulder mechanism, only a small amount of quantitative information is available in the existing literature, although various kinematic models of the shoulder complex have been proposed. This study focused on the specific motion coupling relationship between glenohumeral (GH) joint center displacement variable quantity relative to the thorax coordinate system and humeral elevation angle to describe the shoulder complex. The mechanism model of shoulder complex was proposed with an algorithm designed. Subsequently, twelve healthy subjects performed right arm raising, lowering, as well as raising and lowering (RAL) movements in sixteen elevation planes, and the motion information of the markers attached to the thorax, scapula, and humerus was captured by using Vicon motion capturing system. Then, experimental data was processed and the generalized GH joint with floating center was quantized. Simultaneously, different coupling characteristics were detected during humerus raising as well as lowering movements. The motion coupling relationships in different phases were acquired, and a modified kinematic model was established, with the description of overall motion characteristics of shoulder complex validated by comparing the results with a prior kinematic model from literature, showing enough accuracy for the design of upper limb rehabilitation robots. Full article

(This article belongs to the Special Issue Optical Sensors for the Measurement of Human Posture and Movement)

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21 pages, 6429 KiB

Open AccessArticle

Monitoring Improvement in Infantile Cerebral Palsy Patients Using the 4DBODY System—A Preliminary Study

by Krzysztof Krasowicz, Jakub Michoński, Paweł Liberadzki and Robert Sitnik

Sensors 2020, 20(11), 3232; https://doi.org/10.3390/s20113232 - 06 Jun 2020

Cited by 8 | Viewed by 4327

Abstract

Monitoring the patient’s condition during rehabilitation is the key to success in this form of treatment. This is especially important in patients with infantile cerebral palsy (ICP). Objective assessment can be achieved through modern optical measurement techniques. The 4DBODY system allows to capture dynamic movement with high accuracy. Eight patients with ICP participated in the study. The group underwent therapy lasting seven days using neurodevelopmental treatment (NDT) and functional training (FT). The patients’ condition was monitored by the 4DBODY system. The measurements were taken three times: before the therapy, after, and then again after one week. We have developed the Trunk Mobility in the Frontal Plane Index (TMFPI) for its assessment. The results were compared with a score obtained using the Gross Motor Function Measure scale (GMFM 88). An improvement of the TMFPI parameter was observed in five patients, inconsistent results in two and deterioration in one. The reference GMFM score was higher in all patients relative to pre-treatment values. We found that surface scanning with the 4DBODY system allows to precisely track body movement in ICP patients. The decrease in the TMFPI parameter reflects the improvement in the dysfunction of body alignment, balance and symmetry of movement on the L and R body side. Full article

(This article belongs to the Special Issue Optical Sensors for the Measurement of Human Posture and Movement)

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Other

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12 pages, 6453 KiB

Open AccessLetter

Resolving Position Ambiguity of IMU-Based Human Pose with a Single RGB Camera

by Tomoya Kaichi, Tsubasa Maruyama, Mitsunori Tada and Hideo Saito

Sensors 2020, 20(19), 5453; https://doi.org/10.3390/s20195453 - 23 Sep 2020

Cited by 12 | Viewed by 3951

Abstract

Human motion capture (MoCap) plays a key role in healthcare and human–robot collaboration. Some researchers have combined orientation measurements from inertial measurement units (IMUs) and positional inference from cameras to reconstruct the 3D human motion. Their works utilize multiple cameras or depth sensors to localize the human in three dimensions. Such multiple cameras are not always available in our daily life, but just a single camera attached in a smart IP devices has recently been popular. Therefore, we present a 3D pose estimation approach from IMUs and a single camera. In order to resolve the depth ambiguity of the single camera configuration and localize the global position of the subject, we present a constraint which optimizes the foot-ground contact points. The timing and 3D positions of the ground contact are calculated from the acceleration of IMUs on foot and geometric transformation of foot position detected on image, respectively. Since the results of pose estimation is greatly affected by the failure of the detection, we design the image-based constraints to handle the outliers of positional estimates. We evaluated the performance of our approach on public 3D human pose dataset. The experiments demonstrated that the proposed constraints contributed to improve the accuracy of pose estimation in single and multiple camera setting. Full article

(This article belongs to the Special Issue Optical Sensors for the Measurement of Human Posture and Movement)

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