Motion Capture Markers Research Articles

Effects of IMU Sensor-to-Segment Misalignment and Orientation Error on 3-D Knee Joint Angle Estimation

Accurate joint angle estimation using magneto-inertial measurement units (IMU) is a significant challenge for human movement analysis outside of the lab. Sensor-to-segment misalignment and sensor orientation errors are key factors in joint angle estimation. However, the effects of these factors on 3-D knee joint angle estimation accuracy are not well understood. This paper presents a general model to investigate the effects of sensor-to-segment misalignment and IMU orientation error on 3-D knee joint angle estimation accuracy. An analytical model was built to quantify the effects of sensor-to-segment misalignment and IMU orientation errors for 3-D knee joint angle estimation. Precise outcomes were quantified via simulation analysis and experimental testing in which fourteen healthy subjects performed drop landing and cutting tasks while wearing IMUs and optical motion capture markers for ground truth estimation. Sensor-to-segment misalignment accounted for 52% of the total knee abduction angle error and 40% of the knee internal rotation angle error but did not significantly affect knee flexion angle error. Conversely, IMU orientation error accounted for 55% of the knee flexion angle error but did not significantly affect knee abduction or internal rotation angle errors. These results indicate that sensor-to-segment misalignment significantly affects knee abduction and internal rotation angle estimation while IMU orientation error significantly affects knee flexion angle estimation. This study could serve to inform the development of accurate IMU-based 3-D knee joint angle algorithms for human movement analysis.

Intramuscular EMG-Driven Musculoskeletal Modelling: Towards Implanted Muscle Interfacing in Spinal Cord Injury Patients.

Surface EMG-driven modelling has been proposed as a means to control assistive devices by estimating joint torques. Implanted EMG sensors have several advantages over wearable sensors but provide a more localized information on muscle activity, which may impact torque estimates. Here, we tested and compared the use of surface and intramuscular EMG measurements for the estimation of required assistive joint torques using EMG driven modelling. Four healthy subjects and three incomplete spinal cord injury (SCI) patients performed walking trials at varying speeds. Motion capture marker trajectories, surface and intramuscular EMG, and ground reaction forces were measured concurrently. Subject-specific musculoskeletal models were developed for all subjects, and inverse dynamics analysis was performed for all individual trials. EMG-driven modelling based joint torque estimates were obtained from surface and intramuscular EMG. The correlation between the experimental and predicted joint torques was similar when using intramuscular or surface EMG as input to the EMG-driven modelling estimator in both healthy individuals and patients. We have provided the first comparison of non-invasive and implanted EMG sensors as input signals for torque estimates in healthy individuals and SCI patients. Implanted EMG sensors have the potential to be used as a reliable input for assistive exoskeleton joint torque actuation.

Testing a Quaternion Conversion Method to Determine Human Three-Dimensional Tibiofemoral Angles During an In Vitro Simulated Jump Landing.

Lower limb joint kinematics have been measured in laboratory settings using fixed camera-based motion capture systems; however, recently inertial measurement units (IMUs) have been developed as an alternative. The purpose of this study was to test a quaternion conversion (QC) method for calculating the three orthogonal knee angles during the high velocities associated with a jump landing using commercially available IMUs. Nine cadaveric knee specimens were instrumented with APDM Opal IMUs to measure knee kinematics in one-legged 3-4× bodyweight simulated jump landings, four of which were used in establishing the parameters (training) for the new method and five for validation (testing). We compared the angles obtained from the QC method to those obtained from a commercially available sensor and algorithm (APDM Opal) with those calculated from an active marker motion capture system. Results showed a significant difference between both IMU methods and the motion capture data in the majority of orthogonal angles (p < 0.01), though the differences between the QC method and Certus system in the testing set for flexion and rotation angles were smaller than the APDM Opal algorithm, indicating an improvement. Additionally, in all three directions, both the limits of agreement and root-mean-square error between the QC method and the motion capture system were smaller than between the commercial algorithm and the motion capture.

Towards a Mobile Gait Analysis for Patients with a Spinal Cord Injury: A Robust Algorithm Validated for Slow Walking Speeds.

Spinal cord injury (SCI) patients suffer from diverse gait deficits depending on the severity of their injury. Gait assessments can objectively track the progress during rehabilitation and support clinical decision making, but a comprehensive gait analysis requires far more complex setups and time-consuming protocols that are not feasible in the daily clinical routine. As using inertial sensors for mobile gait analysis has started to gain ground, this work aimed to develop a sensor-based gait analysis for the specific population of SCI patients that measures the spatio-temporal parameters of typical gait laboratories for day-to-day clinical applications. The proposed algorithm uses shank-mounted inertial sensors and personalized thresholds to detect steps and gait events according to the individual gait profiles. The method was validated in nine SCI patients and 17 healthy controls walking on an instrumented treadmill while wearing reflective markers for motion capture used as a gold standard. The sensor-based algorithm (i) performed similarly well for the two cohorts and (ii) is robust enough to cover the diverse gait deficits of SCI patients, from slow (0.3 m/s) to preferred walking speeds.

Optimal Sensor Location in a Smart-Shirt to Measure Accurate Tidal Volumes During Abdominal and Thoracic Respiration

Abstract The determination of respiratory parameters via respiration induced surface movements of the upper body has been the subject of research for many years. The displacements of 102 motion capture markers were evaluated in this study in terms of their information content with respect to the tidal volume recorded in parallel using a spirometer. Independent of the breathing types (spontaneous breathing, abdominal breathing, or chest breathing), the number and the location of sensors in a smart shirt to obtain tidal volume information was determined. Only 9 of 102 sensors were sufficient to obtain breathing volume information.

Biomechanical consequences of tibial tubercle osteotomy in a 3D-printed model of patellofemoral dysplasia (207)

Biomechanical consequences of tibial tubercle osteotomy in a 3D-printed model of patellofemoral dysplasia (207)

Are Wearable Sensors Valid and Reliable for Studying the Baseball Pitching Motion? An Independent Comparison With Marker-Based Motion Capture

Background: In recent years, the prevalence of medial ulnar collateral ligament injuries has increased in throwers of all ages and skill levels. The motusBASEBALL sensor possesses an inertial measurement unit (IMU) that has been developed and applied to the throwing arm to allow for measurements of several objective parameters, which may prove beneficial for monitoring, rehabilitation, and injury prevention in the throwing athlete. However, the reliability, consistency, and validity of the IMU have not been independently assessed. Purpose: To evaluate the reliability, consistency, and validity of the motusBASEBALL sensor compared with the historic gold standard of marker-based motion capture. Study Design: Controlled laboratory study. Methods: A total of 10 healthy male baseball athletes with varsity-level high school experience volunteered to participate in this study. Participants were fitted with 37 retroreflective markers for motion capture and the motusBASEBALL IMU sensor. Participants threw 5 fastballs at maximum effort, with measurements recorded simultaneously by motion capture and the IMU. Arm slot, arm speed, arm stress, and shoulder rotation were measured and compared. Results: Of the 4 metrics generated by the IMU, significant differences were found for 3 of the throwing metrics compared with motion capture including arm slot (5.0°± 6.1°; P = .037), elbow varus torque (9.4 ± 12.0 N·m; P = .037), and shoulder rotation (6.3°± 6.1°; P = .014). Arm speed did not demonstrate a statistically significant difference (29.2 ± 96.8 rpm; P = .375). The IMU consistently underreported pitching performance values. Shoulder rotation exhibited excellent reliability with <5° of error, and arm slot demonstrated good reliability with <10° of error. Arm stress and arm speed were less reliable. Conclusion: The IMU was not accurate or valid for arm slot, arm stress, and shoulder rotation compared with marker-based motion capture. It was relatively accurate for arm speed. Despite its lack of validity, it was consistent and reliable for arm speed and shoulder rotation and relatively reliable for arm slot and arm stress. Caution should be used when comparing values provided by this IMU to the gold standard of marker-based motion capture. Clinical Relevance: IMU technology has potential to be used in monitoring, rehabilitation, and injury prevention in throwing athletes if valid. This study demonstrates that the values provided by the IMU should not be considered equivalent to those generated by the gold standard of marker-based motion capture; however, there may still be a role for this technology when relying on its internal consistency for intrathrower comparisons and tracking.

Use of motion capture-coupled ultrasound sensors to determine scapular position

ABSTRACT Ultrasonic imaging is a safe, established, and non-invasive method to visualise the locations of structures within the body. Coupling existing skin mounted motion capture markers to ultrasound sensors could allow for precise measurement of positions and orientations of bones hidden under the skin, mitigating the effects of relative displacement between skin and bone that occurs in standard motion capture techniques. This is especially important in motions where skin-mounted markers are inaccurate, such as when tracking scapular position while shoulder abduction is greater than 80 degrees. Previous in silico research has shown that five ultrasound-coupled motion capture clusters could provide sub-millimetre levels of scapular RMS error. This study builds upon those results. The position of a scapular phantom measured by the motion capture plus ultrasound (MC+U) technique was compared to the phantom position as quantified by CT. The root mean squared measurement error in overall scapular position was . Mean translational and rotational errors were 0.74 mm and 0.42°, respectively. This level of accuracy would make MC+U a valuable new tool for quantifying scapular position and motion in vivo. The results of this study confirm that the further development of the MC+U technique is warranted and establish a reasonable target for the accuracy of this technique for future in vivo studies.

In Vivo Quantification of Hip Arthrokinematics during Dynamic Weight-bearing Activities using Dual Fluoroscopy.

Several hip pathologies have been attributed to abnormal morphology with an underlying assumption of aberrant biomechanics. However, structure-function relationships at the joint level remain challenging to quantify due to difficulties in accurately measuring dynamic joint motion. The soft tissue artifact errors inherent in optical skin marker motion capture are exacerbated by the depth of the hip joint within the body and the large mass of soft tissue surrounding the joint. Thus, the complex relationship between bone shape and hip joint kinematics is more difficult to study accurately than in other joints. Herein, a protocol incorporating computed tomography (CT) arthrography, three-dimensional (3D) reconstruction of volumetric images, dual fluoroscopy, and optical motion capture to accurately measure the dynamic motion of the hip joint is presented. The technical and clinical studies that have applied dual fluoroscopy to study form-function relationships of the hip using this protocol are summarized, and the specific steps and future considerations for data acquisition, processing, and analysis are described.

Single-Camera-Based Bridge Structural Displacement Measurement with Traffic Counting.

Vision-based structural displacement methods allow convenient monitoring of civil structures such as bridges, though they are often limited due to the small number of measurement points, constrained spatial resolution, and inability to identify the acting forces of the measured displacement. To increase the number of measurement points in vision-based bridge displacement measurement, this study introduces a front-view tandem marker motion capture system with side-view traffic counting to identify the force-inducing passing vehicles on the bridge’s deck. The proposed system was able to measure structural displacement at submillimeter resolution on eight measurement points at once at a distance of 40.8–64.2 m from a front-view camera. The traffic counting system with a side-view camera recorded the passing vehicles from two opposing lanes. We conducted a 35-min experiment for a 25 m-span steel road bridge with hundreds of cars passing over it and confirmed dynamic displacement distributions with amplitudes of several millimeters when large vehicles passed.

Can Markerless Pose Estimation Algorithms Estimate 3D Mass Centre Positions and Velocities during Linear Sprinting Activities?

The ability to accurately and non-invasively measure 3D mass centre positions and their derivatives can provide rich insight into the physical demands of sports training and competition. This study examines a method for non-invasively measuring mass centre velocities using markerless human pose estimation and Kalman smoothing. Marker (Qualysis) and markerless (OpenPose) motion capture data were captured synchronously for sprinting and skeleton push starts. Mass centre positions and velocities derived from raw markerless pose estimation data contained large errors for both sprinting and skeleton pushing (mean ± SD = 0.127 ± 0.943 and −0.197 ± 1.549 m·s−1, respectively). Signal processing methods such as Kalman smoothing substantially reduced the mean error (±SD) in horizontal mass centre velocities (0.041 ± 0.257 m·s−1) during sprinting but the precision remained poor. Applying pose estimation to activities which exhibit unusual body poses (e.g., skeleton pushing) appears to elicit more erroneous results due to poor performance of the pose estimation algorithm. Researchers and practitioners should apply these methods with caution to activities beyond sprinting as pose estimation algorithms may not generalise well to the activity of interest. Retraining the model using activity specific data to produce more specialised networks is therefore recommended.

Scaling of linear anthropometric dimensions in living humans.

Some previous studies suggest that humans do not conform to geometric similarity (isometry) in anthropometric dimensions of the upper and lower limbs. Researchers often rely on a single statistical approach to the study of scaling patterns, and it is unclear whether these methods produce similar results and are equally robust. This study used one bivariate and one multivariate method to examine how linear anthropometric dimensions scale in a sample of adult humans. Motion capture marker data from 104 adults of varying height and mass were used to calculate anthropometric dimensions. We analyzed scaling patterns in pooled and separate sexes with two methods: (1) bivariate log-log regression and (2) multivariate principal component analysis (PCA). We calculated 95% highest density/confidence intervals for each method and defined positive/negative allometry as estimates lying outside those intervals. Results identified isometric scaling of the upper arm, thigh, and shoulder, positive allometry of the forearm and shank, and negative allometry of the pelvis in the pooled sample using both statistical methods. Patterns of allometry in the pooled sample were similar between methods but differed in magnitude. Sex-specific results differed in both pattern and magnitude between log-log regression and PCA. Only one measurement (shoulder width) departed from isometry in the sex-specific log-log regressions. Our findings suggest that especially in sex-specific analyses, the pattern and magnitude of allometry are sensitive to statistical methodology. When body mass was selected as the size variable, most human linear anthropometric dimensions in this sample scaled isometrically and were therefore geometrically similar within sexes.

User-driven treadmill walking promotes healthy step width after stroke

BackgroundWalking with user-driven treadmill control is believed to be more like overground walking than fixed-speed treadmill walking. Walking speed and ground reaction forces differ between overground and fixed-speed treadmill walking, but not between overground and user-driven treadmill walking in healthy and post-stroke subjects. However, studies assessing spatiotemporal gait parameters during user-driven treadmill walking are limited. This information may help confirm that user-driven treadmill walking is more like overground walking than fixed-speed treadmill walking, as well as inform the development of post-stroke gait rehabilitation programs. Research questionHow do spatiotemporal gait parameters for individuals post-stroke differ between fixed-speed and user-driven treadmill walking? MethodsEighteen subjects (10 M, 8 F; 62 ± 12 years; 1.73 ± 0.12 m; 84.9 ± 12.9 kg; 40 ± 30 months post-stroke) with chronic post-stroke hemiparesis participated in this study. Participants walked on an instrumented treadmill in its fixed-speed and user-driven modes at their self-selected and fastest comfortable walking speeds. Subjects wore retroreflective markers for motion capture. Shapiro-Wilk tests were used to assess for normality and one-way repeated measures ANOVAs were used to compare between conditions with α = 0.05. Bonferroni corrections were used for multiple comparisons. ResultsStep width was significantly smaller with user-driven control (13.7 cm, 95 % CI: [0.131, 0.145]) than fixed-speed control (16.8 cm, 95 % CI:[0.160, 0.174]), while step length and step time did not differ across treadmill conditions. Step length and step time differed between self-selected and fast walking speeds, but not treadmill control conditions. SignificanceThe results of this study show that user-driven treadmill control encourages healthy gait biomechanics and a greater sense of stability in post-stroke subjects. Individuals post-stroke walked with smaller step width with user-driven treadmill control, which has been associated with increased balance. Post-stroke gait rehabilitation may benefit from programs with user-driven treadmill training paradigms to improve mobility following stroke.

Development and Validation of a Deep Learning Algorithm and Open-Source Platform for the Automatic Labelling of Motion Capture Markers

The purpose of this work was to develop an open-source deep learning-based algorithm for motion capture marker labelling that can be trained on measured or simulated marker trajectories. In the proposed algorithm, a deep neural network including recurrent layers is trained on measured or simulated marker trajectories. Labels are assigned to markers using the Hungarian algorithm and a predefined generic marker set is used to identify and correct mislabeled markers. The algorithm was first trained and tested on measured motion capture data. Then, the algorithm was trained on simulated trajectories and tested on data that included movements not contained in the simulated data set. The ability to improve accuracy using transfer learning to update the neural network weights based on labelled motion capture data was assessed. The effect of occluded and extraneous markers on labelling accuracy was also examined. Labelling accuracy was 99.6% when trained on measured data and 92.8% when trained on simulated trajectories, but could be improved to up to 98.8% through transfer learning. Missing or extraneous markers reduced labelling accuracy, but results were comparable to commercial software. The proposed labelling algorithm can be used to accurately label motion capture data in the presence of missing and extraneous markers and accuracy can be improved as data are collected, labelled, and added to the training set. The algorithm and user interface can reduce the time and manual effort required to label optical motion capture data, particularly for those with limited access to commercial software.

Assessment of Upper-Extremity Joint Angles Using Harmony Exoskeleton.

The biomechanical complexity of the human shoulder, while critical for functionality, poses a challenge for objective assessment during sensorimotor rehabilitation. With built-in sensing capabilities, robotic exoskeletons have the potential to serve as tools for both intervention and assessment. The bilateral upper-extremity Harmony exoskeleton is capable of full shoulder articulation, forearm flexion-extension, and wrist pronation-supination motions. The goal of this paper is to characterize Harmony's anatomical joint angle tracking accuracy towards its use as an assessment tool. We evaluated the agreement between anatomical joint angles estimated from the robot's sensor data and optical motion capture markers attached to the human user. In 9 healthy participants we examined 6 upper-extremity joint angles, including shoulder girdle angles, across 4 different motions, varying active/passive motion of the user and physical constraint of the trunk. We observed mostly good to excellent levels of agreement between measurement systems with for shoulder and distal joints, magnitudes of average discrepancies varying from 0.43° to 16.03° and width of LoAs ranging between 9.44° and 41.91°. Slopes were between 1.03 and 1.43 with r > 0.9 for shoulder and distal joints. Regression analysis suggested that discrepancies observed between measured robot and human motions were primarily due to relative motion associated with soft tissue deformation. The results suggest that the Harmony exoskeleton is capable of providing accurate measurements of arm and shoulder joint kinematics. These findings may lead to robot-assisted assessment and intervention of one of the most complex joint structures in the human body.

Artificial Intelligence-Assisted motion capture for medical applications: a comparative study between markerless and passive marker motion capture

We aimed to determine whether artificial intelligence (AI)-assisted markerless motion capture software is useful in the clinical medicine and rehabilitation fields. Currently, it is unclear whether the AI-assisted markerless method can be applied to individuals with lower limb dysfunction, such as those using an ankle foot orthosis or a crutch. However, as many patients with lower limb paralysis and foot orthosis users lose metatarsophalangeal (MP) joint flexion during the stance phase, it is necessary to estimate the accuracy of foot recognition under fixed MP joint motion. The hip, knee, and ankle joint angles during treadmill walking were determined using OpenPose (a markerless method) and the conventional passive marker motion capture method; the results from both methods were compared. We also examined whether an ankle foot orthosis and a crutch could influence the recognition ability of OpenPose. The hip and knee joint data obtained by the passive marker method (MAC3D), OpenPose, and manual video analysis using Kinovea software showed significant correlation. Compared with the ankle joint data obtained by OpenPose and Kinovea, which were strongly correlated, those obtained by MAC3D presented a weaker correlation. OpenPose can be an adequate substitute for conventional passive marker motion capture for both normal gait and abnormal gait with an orthosis or a crutch. Furthermore, OpenPose is applicable to patients with impaired MP joint motion. The use of OpenPose can reduce the complexity and cost associated with conventional passive marker motion capture without compromising recognition accuracy.

Acute effect of whole-body vibration on acceleration transmission and jumping performance in children

BackgroundWhole-body vibration (WBV) has emerged as a potential intervention paradigm for improving motor function and bone growth in children with disabilities. However, most evidence comes from adult studies. It is critical to understand the mechanisms of children with and without disabilities responding to different WBV conditions. This study aimed to systematically investigate the acute biomechanical and neuromuscular response in typically developing children aged 6–11 years to varying WBV frequencies and amplitudes. MethodsSeventeen subjects participated in this study (mean age 8.7 years, 10 M/7F). A total of six side-alternating WBV conditions combining three frequencies (20, 25, and 30 Hz) and two amplitudes (1 and 2 mm) were randomly presented for one minute. We estimated transmission of vertical acceleration across body segments during WBV as the average rectified acceleration of motion capture markers, as well as lower-body muscle activation using electromyography. Following WBV, subjects performed countermovement jumps to assess neuromuscular facilitation. FindingsVertical acceleration decreased from the ankle to the head across all conditions, with the greatest damping occurring from the ankle to the knee. Acceleration transmission was lower at the high amplitude than at the low amplitude across body segments, and the knee decreased acceleration transmission with increasing frequency. In addition, muscle activation generally increased with frequency during WBV. There were no changes in jump height or muscle activation following WBV. InterpretationWBV is most likely a safe intervention paradigm for typically developing children. Appropriate WBV intervention design for children with and without disabilities should consider WBV frequency and amplitude.

Force quantification and simulation of pedicle screw tract palpation using direct visuo-haptic volume rendering

PurposeWe present a feasibility study for the visuo-haptic simulation of pedicle screw tract palpation in virtual reality, using an approach that requires no manual processing or segmentation of the volumetric medical data set.MethodsIn a first experiment, we quantified the forces and torques present during the palpation of a pedicle screw tract in a real boar vertebra. We equipped a ball-tipped pedicle probe with a 6-axis force/torque sensor and a motion capture marker cluster. We simultaneously recorded the pose of the probe relative to the vertebra and measured the generated forces and torques during palpation. This allowed us replaying the recorded palpation movements in our simulator and to fine-tune the haptic rendering to approximate the measured forces and torques. In a second experiment, we asked two neurosurgeons to palpate a virtual version of the same vertebra in our simulator, while we logged the forces and torques sent to the haptic device.ResultsIn the experiments with the real vertebra, the maximum measured force along the longitudinal axis of the probe was 7.78 N and the maximum measured bending torque was 0.13 Nm. In an offline simulation of the motion of the pedicle probe recorded during the palpation of a real pedicle screw tract, our approach generated forces and torques that were similar in magnitude and progression to the measured ones. When surgeons tested our simulator, the distributions of the computed forces and torques were similar to the measured ones; however, higher forces and torques occurred more frequently.ConclusionsWe demonstrated the suitability of direct visual and haptic volume rendering to simulate a specific surgical procedure. Our approach of fine-tuning the simulation by measuring the forces and torques that are prevalent while palpating a real vertebra produced promising results.

Biofidelic Evaluation of the Large Omni-Directional Child Anthropomorphic Test Device in Low Speed Loading Conditions.

Motor vehicle crashes remain the leading cause of death for children. Traditionally, restraint design has focused on the crash phase of the impact with an optimally seated occupant. In order to optimize restrain design for real-world scenarios, research has recently expanded its focus to non-traditional loading conditions including pre-crash positioning and lower speed impacts. The goal of this study was to evaluate the biofidelity of the large omni-directional child (LODC) ATD in non-traditional loading conditions by comparing its response to pediatric volunteer data in low-speed sled tests. Low-speed (2-4 g, 1.9-3.0 m/s) frontal (0°), far-side oblique (60°), and far-side lateral (90º) sled tests, as well as lateral swerving (0.72 g, 0.5 Hz) tests, were conducted using the LODC. The LODC was restrained using a 3-point-belt with an electromechanical motorized seat belt retractor, or pre-pretensioner. Motion capture markers were placed on the head, torso, and belt. The LODC was compared to previously collected pediatric volunteer data as well as the HIII 10 and Q10. Significant difference between the pediatric volunteers and ATDs were identified by comparing the mean ATD response to the pediatric volunteer 95% CI. The LODC exhibited lower forward head excursion (262 mm) compared to pediatric volunteers (263 - 333 mm) in low-speed frontal sled tests (p<0.05), but was closer to the pediatric volunteers than the HIII 10 (179 mm) and Q10 (171 mm). In lateral swerving, the LODC (429 mm) exhibited greater lateral head excursion (p<0.05) compared to pediatric volunteers (115 - 171 mm). The LODC exhibited a greater reduction in kinematics compared to the pediatric volunteers in all loading conditions with a pre-pretensioner. These data provide valuable insight into the biofidelity of the LODC in non-traditional loading conditions, such as evaluating pre-crash maneuvers on occupant response.

СИСТЕМИ ЗАХОПЛЕННЯ РУХУ В ДОДАНІЙ РЕАЛЬНОСТІ: РІЗНОВИДИ ТА СПЕЦИФІКА ЇХ ЗАСТОСУВАННЯ У ПРАКТИЦІ ПРОМОЦІЙНИХ КОМУНІКАЦІЙ

&lt;div&gt;&lt;p&gt;&lt;em&gt;In this study there were identified the main varieties of existing motion capture systems (mocap) that can be used primarily to create three-dimensional animation for augmented reality; as well as established their specific features, and also demonstrated the examples of the practical use of certain types of such systems in promotional communications.&lt;/em&gt;&lt;/p&gt;&lt;/div&gt;&lt;p&gt;&lt;em&gt;This study unleashes the specificity of the functioning of non-marker and all types of marker motion capture systems – optical (optically passive and optically active, including «performance capture» as well as hybrid) and non-optical (acoustic, magnetic, mechanical and inertial).&lt;/em&gt;&lt;/p&gt;&lt;p&gt;&lt;em&gt;There were analyzed two practical promotional cases: the American social PR project «Love Has No Labels» and the Japanese commercial brand «ZozoTown» («ZozoSuit»).&lt;/em&gt;&lt;/p&gt;&lt;p&gt;&lt;em&gt;It has been found that in the practice of promotional communications inertial-type mocap systems with full magnetic interference are most actively used, since they can be used directly during mass AR-actions, primarily due to their portability and ability to function in a limited space.&lt;/em&gt;&lt;/p&gt;&lt;p&gt;&lt;em&gt;It has also been revealed that AR-actions using motion capture systems are conducted primarily to create positive WOM and media resonances, allowing to significantly diversify the arsenal of communication tools with the target audience, as well as to increase the quality and efficiency of promotional messages, which in sum boosts the publicity capital.&lt;/em&gt;&lt;/p&gt;&lt;p&gt;&lt;em&gt;Other varieties of mocap systems (with exception of non-marking one, which works through computer vision) are not used in real time regime for promotional events primarily due to their cumbersome nature. However, they can be employed to create realistic 3D animation for future utilization in promotional campaigns, projects, and actions using augmented reality technologies.&lt;/em&gt;&lt;/p&gt;&lt;p&gt;&lt;strong&gt;&lt;em&gt;Key words:&lt;/em&gt;&lt;/strong&gt;&lt;em&gt; motion capture systems (mocap), augmented reality (AR), promotion, empirical marketing.&lt;/em&gt;&lt;/p&gt;