RESUMEN

Autism spectrum disorders (ASD) are characterized by social and repetitive abnormalities. Although the ASD mouse model with Shank3b mutations is widely used in ASD research, the behavioral phenotype of this model has not been fully elucidated. Here, a 3D-motion capture system and linear discriminant analysis were used to comprehensively record and analyze the behavioral patterns of male and female Shank3b mutant mice. It was found that both sexes replicated the core and accompanied symptoms of ASD, with significant sex differences. Further, Shank3b heterozygous knockout mice exhibited distinct autistic behaviors, that were significantly different from those those observed in the wild type and homozygous knockout groups. Our findings provide evidence for the inclusion of both sexes and experimental approaches to efficiently characterize heterozygous transgenic models, which are more clinically relevant in autistic studies.

Asunto(s)

RESUMEN

Optical Motion Capture Systems (OMCSs) are considered the gold standard for kinematic measurement of human movements. However, in situations such as measuring wrist kinematics during a hairdressing activity, markers can be obscured, resulting in a loss of data. Other measurement methods based on non-optical data can be considered, such as magneto-inertial measurement units (MIMUs). Their accuracy is generally lower than that of an OMCS. In this context, it may be worth considering a hybrid system [MIMU + OMCS] to take advantage of OMCS accuracy while limiting occultation problems. The aim of this work was (1) to propose a methodology for coupling a low-cost MIMU (BNO055) to an OMCS in order to evaluate wrist kinematics, and then (2) to evaluate the accuracy of this hybrid system [MIMU + OMCS] during a simple hairdressing gesture. During hair cutting gestures, the root mean square error compared with the OMCS was 4.53° (1.45°) for flexion/extension, 5.07° (1.30°) for adduction/abduction, and 3.65° (1.19°) for pronation/supination. During combing gestures, they were significantly higher, but remained below 10°. In conclusion, this system allows for maintaining wrist kinematics in case of the loss of hand markers while preserving an acceptable level of precision (<10°) for ergonomic measurement or entertainment purposes.

Asunto(s)

RESUMEN

Previous studies often inferred the focus of a bird's attention from its head movements because it provides important clues about their perception and cognition. However, it remains challenging to do so accurately, as the details of how they orient their visual field toward the visual targets remain largely unclear. We thus examined visual field configurations and the visual field use of large-billed crows (Corvus macrorhynchos Wagler 1827). We used an established ophthalmoscopic reflex technique to identify the visual field configuration, including the binocular width and optical axes, as well as the degree of eye movement. A newly established motion capture system was then used to track the head movements of freely moving crows to examine how they oriented their reconstructed visual fields toward attention-getting objects. When visual targets were moving, the crows frequently used their binocular visual fields, particularly around the projection of the beak-tip. When the visual targets stopped moving, crows frequently used non-binocular visual fields, particularly around the regions where their optical axes were found. On such occasions, the crows slightly preferred the right eye. Overall, the visual field use of crows is clearly predictable. Thus, while the untracked eye movements could introduce some level of uncertainty (typically within 15 deg), we demonstrated the feasibility of inferring a crow's attentional focus by 3D tracking of their heads. Our system represents a promising initial step towards establishing gaze tracking methods for studying corvid behavior and cognition.

Asunto(s)

RESUMEN

This study aimed to investigate the essential role of the kicking action in front crawl. To achieve this objective, we examined the relationships of the hand propulsive force and trunk inclination with swimming velocity over a wide range of velocities from 0.75 m·s-1 to maximum effort, including the experimental conditions of arm stroke without a pull buoy. Seven male swimmers performed a 25 m front crawl at various speeds under three swimming conditions: arm stroke with a pull buoy, arm stroke without a pull buoy (AWOB) and arm stroke with a six-beat kick (SWIM). Swimming velocity, hand propulsive force and trunk inclination were calculated using an underwater motion-capture system and pressure sensors. Most notably, AWOB consistently exhibited greater values than SWIM for hand propulsive force across the range of observed velocities (p < 0.05) and for trunk inclination below the severe velocity (p < 0.05), and these differences increased with decreasing velocity. These results indicate that 1) the kicking action in front crawl has a positive effect on reducing the pressure drag acting on the trunk, thereby allowing swimmers to achieve a given velocity with less hand propulsive force, and 2) this phenomenon is significant in low-velocity ranges.

RESUMEN

BACKGROUND: Gait initiation is challenging for older individuals with poor physical function, particularly for those with frailty. Frailty is a geriatric syndrome associated with increased risk of illness, falls, and functional decline. This study examines whether spatial and temporal parameters of gait initiation differ between groups of older adults with different levels of frailty, and whether fear of falling, and balance ability are correlated with the height of lifting the food during gait initiation. METHODS: Sixty-one individuals aged > 65 years, classified by Fried frailty phenotype, performed five self-paced gait initiation trials. Data was collected using a three-dimensional passive optical motion capture system, consisting of 10 cameras with the ability to perceive reflective markers, and two force plates. The total duration of gait initiation and the duration of its four sub-phases, the first step length, and the maximum foot clearance during the first step were derived, and compared statistically between groups. Additionally, an association analysis was conducted between foot clearance and fear of falling, and confidence in balance in older individuals. RESULTS: Frail individuals had significantly longer unloading durations, and total durations of gait initiation compared to non-frail older adults. Additionally, they had shorter first step lengths compared to non-frail older adults. Pre-frail older adults also showed shorter steps compared to the non-frail group. However, there were no significant differences between groups for the maximum foot clearance during the first step. Nevertheless, the maximum foot clearance of older individuals correlated significantly with their fear of falling and confidence in balance. CONCLUSION: Older adults with reduced physical function and signs of frailty mainly display longer duration of gait initiation and decreased first step length compared to non-frail older adults. The release phase is decreased as the double support phase is prolonged in frail patients. This information can guide the development of specialized exercise programs to improve mobility in this challenging motion between static and dynamic balance.

RESUMEN

In recent years, researchers have focused on analyzing humans' daily living activities to study various performance metrics that humans subconsciously optimize while performing a particular task. In order to recreate these motions in robotic structures based on the human model, researchers developed a framework for robot motion planning which is able to use various optimization methods to replicate similar motions demonstrated by humans. As part of this process, it will be necessary to record the motions data of the human body and the objects involved in order to provide all the essential information for motion planning. This paper aims to provide a dataset of human motion performing activities of daily living that consists of detailed and accurate human whole-body motion data collected using a Vicon motion capture system. The data have been utilized to generate a subject-specific full-body model within OpenSim. Additionally, it facilitated the computation of joint angles within the OpenSim framework, which can subsequently be applied to the subject-specific robotic model developed MATLAB framework. The dataset comprises nine daily living activities and eight Range of Motion activities performed by ten healthy participants and with two repetitions of each variation of one action, resulting in 340 demonstrations of all the actions. A whole-body human motion database is made available to the public at the Center for Assistive, Rehabilitation, and Robotics Technologies (CARRT)-Motion Capture Data for Robotic Human Upper Body Model, which consists of raw motion data in .c3d format, motion data in .trc format for the OpenSim model, as well as post-processed motion data for the MATLAB-based model.

Asunto(s)

RESUMEN

Upper-limb paresis is common after stroke. An important tool to assess motor recovery is to use marker-based motion capture systems to measure the kinematic characteristics of patients' movements in ecological scenarios. These systems are, however, very expensive and not readily available for many rehabilitation units. Here, we explored whether the markerless hand motion capabilities of the cost-effective Oculus Quest head-mounted display could be used to provide clinically meaningful measures. A total of 14 stroke patients executed ecologically relevant upper-limb tasks in an immersive virtual environment. During task execution, we recorded their hand movements simultaneously by means of the Oculus Quest's and a marker-based motion capture system. Our results showed that the markerless estimates of the hand position and peak velocity provided by the Oculus Quest were in very close agreement with those provided by a marker-based commercial system with their regression line having a slope close to 1 (maximum distance: mean slope = 0.94 ± 0.1; peak velocity: mean slope = 1.06 ± 0.12). Furthermore, the Oculus Quest had virtually the same sensitivity as that of a commercial system in distinguishing healthy from pathological kinematic measures. The Oculus Quest was as accurate as a commercial marker-based system in measuring clinically meaningful upper-limb kinematic parameters in stroke patients.

Asunto(s)

RESUMEN

In golf swing analysis, high-speed cameras and Trackman devices are traditionally used to collect data about the club, ball, and putt. However, these tools are costly and often inaccessible to golfers. This research proposes an alternative solution, employing an affordable inertial motion capture system to record golf swing movements accurately. The focus is discerning the differences between motions producing straight and slice trajectories. Commonly, the opening motion of the body's left half and the head-up motion are associated with a slice trajectory. We employ the Hilbert-Huang transform (HHT) to examine these motions in detail to conduct a biomechanical analysis. The gathered data are then processed through HHT, calculating their instantaneous frequency and amplitude. The research found discernible differences between straight and slice trajectories in the golf swing's moment of impact within the instantaneous frequency domain. An average golfer, a single handicapper, and three beginner golfers were selected as the subjects in this study and analyzed using the proposed method, respectively. For the average golfer, the head and the left leg amplitudes of the swing motions increase at the moment of impact of the swings, resulting in the slice trajectory. These results indicate that an opening of the legs and head-up movements have been detected and extracted as non-linear frequency components, reviewing the biomechanical meaning in slice trajectory motion. For the single handicapper, the hip and left arm joints could be the target joints to detect the biomechanical motion that triggered the slice trajectory. For the beginners, since their golf swing forms were not finalized, the biomechanical motions regarding slice trajectory were different from each swing, indicating that beginner golfers need more practice to fix their golf swing form first. These results revealed that our proposed framework applied to different golf levels and could help golfers to improve their golf swing skills to achieve straight trajectories.

Asunto(s)

RESUMEN

BACKGROUND: Risk factors for throwing injuries related to pitching mechanics are unknown. Insufficient pelvic rotation during pitching may be a risk factor for shoulder and elbow injury. This cohort study aimed to identify biomechanics risk factors for throwing injuries in young baseball players. We hypothesized that excessive mechanical load and motion errors would be risk factors for throwing injuries. METHODS: Young baseball pitchers (aged 8-9 years) were recruited from regional baseball leagues between December 2016 and December 2019. Pitching measurements were performed before the start of each season and after the end of the last season in December 2019. The trunk tilt angular displacement, pelvic rotation angular displacement, and forearm rotation angle were calculated using a markerless motion capture system. We also measured elbow varus torque using an accelerometer. After the initial test session, each participant was followed up for 3 years to determine the occurrence of throwing injuries. Players with throwing shoulder and elbow injuries were categorized into the throwing injury group, and those without shoulder and elbow pain for 3 years were categorized into the noninjured group. RESULTS: In this study, 97 baseball pitchers completed a 3-year follow-up. Among those participants, 66 (68.0%) had throwing injuries. A significant difference was observed between the throwing injury and noninjured groups, whereby the injured players had less pelvic rotation angular displacement. CONCLUSION: Insufficient pelvic rotation during pitching is a newly discovered risk factor related to throwing injuries.

RESUMEN

Background: In kayaking, trunk motion is one of the important factors that prevent injury and improve performance. Kinematic studies in kayaking have been reported in laboratory settings using paddling simulators and ergometers. However, such studies do not reflect kayaking on water, the actual competitive environment. Therefore, we developed a video camera-type kayak motion capture system (KMCS) wherein action cameras were fixed to a kayak to capture images of markers attached to an athlete's body. This study aimed to compare the kinematic data between KMCS and an optical motion capture system (OMCS) in kayaking and to determine the accuracy of the KMCS analysis. Methods: In a competition, five elite junior female kayak athletes performed kayak paddling under the unloaded condition using a kayak. The kayak was secured using a tri-folding bench and a towel, and twenty strokes were recorded during maximal paddling. One stroke was defined as the period from right catch to left catch, and the first six strokes were used to evaluate the accuracy. Trunk angles (tilting, turning, and rotation) were examined with the simultaneous use of KMCS and OMCS, and the differences between these systems were evaluated. To ensure reliability, intraclass correlation coefficient (ICC; a two-way mixed model for absolute agreement) was calculated for each angle. Furthermore, Bland-Altman analysis was performed to understand the agreement between the two systems. Results: Root mean square errors (RMSEs) were 1.42° and 3.94° for turning and rotation, respectively, and mean absolute errors (MAEs) were 1.08° and 3.00° for turning and rotation, respectively. The RMSE and MAE for tilting were 2.43° and 1.76°, respectively, which indicated that the validity was comparable to that of other angles. However, the range of motion in tilting was lower than that in turning and rotation. Bland-Altman analysis showed good agreement in the total range of motion, with mean bias values of -0.84°, -0.07°, and -0.41° for tilting, turning, and rotation, respectively. The ICCs for tilting, turning, and rotation were 0.966, 0.985, and 0.973, respectively, and showed excellent reliability. Conclusions: The newly developed KMCS effectively measured the trunk motion with good accuracy in kayaking. In future studies, we intend to use KMCS to measure kayaking on water and collect data for performance improvement and injury prevention.

Asunto(s)

RESUMEN

The ability to count finger and wrist movements throughout the day with a nonobtrusive, wearable sensor could be useful for hand-related healthcare applications, including rehabilitation after a stroke, carpal tunnel syndrome, or hand surgery. Previous approaches have required the user to wear a ring with an embedded magnet or inertial measurement unit (IMU). Here, we demonstrate that it is possible to identify the occurrence of finger and wrist flexion/extension movements based on vibrations detected by a wrist-worn IMU. We developed an approach we call "Hand Activity Recognition through using a Convolutional neural network with Spectrograms" (HARCS) that trains a CNN based on the velocity/acceleration spectrograms that finger/wrist movements create. We validated HARCS with the wrist-worn IMU recordings obtained from twenty stroke survivors during their daily life, where the occurrence of finger/wrist movements was labeled using a previously validated algorithm called HAND using magnetic sensing. The daily number of finger/wrist movements identified by HARCS had a strong positive correlation to the daily number identified by HAND (R2 = 0.76, p < 0.001). HARCS was also 75% accurate when we labeled the finger/wrist movements performed by unimpaired participants using optical motion capture. Overall, the ringless sensing of finger/wrist movement occurrence is feasible, although real-world applications may require further accuracy improvements.

Asunto(s)

RESUMEN

CONTEXT: Early identification of incoming military personnel at elevated odds for bone stress injury (BSI) is important for the health and readiness of the US military. DESIGN: Prospective cohort study. METHODS: Knee kinematic data of the incoming US Military Academy cadets were collected while performing a jump-landing task (The Landing Error Scoring System) using a markerless motion capture system and depth camera. Data on incidence of lower-extremity injury, including BSI, were collected throughout the study period. RESULTS: A total of 1905 participants (452 females, 23.7%) were examined for knee valgus and BSI status. A total of 50 BSI occurred during the study period (incidence proportion = 2.6%). The unadjusted odds ratio for BSI at initial contact was 1.03 (95% confidence interval [CI], 0.94-1.14; P = .49). Adjusted for sex, the odds ratio for BSI at initial contact was 0.97 (95% CI, 0.87-1.06; P = .47). At the instant of maximum knee-flexion angle, the unadjusted odds ratio was 1.06 (95% CI, 1.02-1.10; P = .01), and the odds ratio was 1.02 (95% CI, 0.98-1.07; P = .29) after adjusting for sex. This suggests that there was not a significant enough association for an increase in the odds of BSI based on either degree of knee valgus. CONCLUSIONS: Our results did not demonstrate an association between knee valgus angle data during a jump-landing task and future increased odds of BSI in a military training population. Further analysis is warranted, but the results suggests the association between kinematics and BSI cannot be effectively screened by knee valgus angle data in isolation.

Asunto(s)

RESUMEN

Sports-related injuries are the most common in the lower extremities among physical regions. To evaluate impaired functional performance in sports training facilities and sports, a marker-less motion analysis system that can measure joint kinematics in bright indoor and outdoor environments is required. The aim of this study was to establish the concurrent and angle-trajectory validity and intra-trial reliability of a novel multi-view image-based motion analysis system with marker-less pose estimation during lower extremity tasks in healthy young men. Ten healthy young men participated voluntarily in this study. The hip and knee joint angles were collected using a multi-view image-based motion analysis system (marker-less) and a Vicon motion capture system (with markers) during the lower extremity tasks. Intraclass correlation coefficient (ICC) analyses were used to identify the concurrent and angle-trajectory validity and intra-trial reliability of the multi-view image-based motion analysis system. In the concurrent validity, the correlation analysis revealed that the ICC3, k values on the hip and knee flexions during knee bending in sitting, standing, and squat movements were from 0.747 to 0.936 between the two systems. In particular, the angle-trajectory validity was very high (ICC3, 1 = 0.859-0.998), indicating a high agreement between the two systems. The intra-trial reliability of each system was excellent (ICC3, 1 = 0.773-0.974), reflecting high reproducibility. We suggest that this novel marker-less motion analysis system is highly accurate and reliable for measuring joint kinematics of the lower extremities during the rehabilitation process and monitoring sports performance of athletes in training facilities.

RESUMEN

We attempted to find a subset model that would allow robust prediction of a swimmer's vertical body position during front crawl with fewer markers, which can reduce extra drag and time-consuming measurements. Thirteen male swimmers performed a 15-metre front crawl either with three different lung-volume levels or various speeds, or both, without taking a breath with 36 reflective markers. The vertical positions of the centre of mass (CoM) and four representative landmarks in the trunk segment over a stroke cycle were calculated using an underwater motion-capture system. We obtained 212 stroke cycles across trials and analysed the vertical position derived from 15 patterns as candidates for the subset models. Unconstrained optimisation minimises the root-mean-square error between the vertical CoM position and each subset model. The performance evaluated from the intra-class correlation coefficient (ICC) and weight parameters of each subset model were detected from the mean values across five-fold cross-validation. The subset model with four markers attached to the trunk segment showed good reliability (ICC: 0.776 ± 0.019). This result indicates that the subset model with few markers can robustly predict a male swimmer's vertical CoM position during front crawl under a wide range of speeds from 0.66 to 1.66 m · s-1.

Asunto(s)

RESUMEN

BACKGROUND: Excessive range of tibial rotation (rTR) may be a reason why athletes cannot return to sports after ACL reconstruction (ACLR). After ACLR, rTR is smaller in reconstructed knees compared to contralateral knees when measured during low-to-moderate-demand tasks. This may not be representative of the amount of rotational laxity during sports activities. The purpose of this study is to determine whether rTR is increased after ACL injury compared to the contralateral knee and whether it returns to normal after ACLR when assessed during high-demand hoptests, with the contralateral knee as a reference. METHODS: Ten ACL injured subjects were tested within three months after injury and one year after reconstruction. Kinematic motion analysis was conducted, analysing both knees. Subjects performed a level-walking task, a single-leg hop for distance and a side jump. A paired t-test was used to detect a difference between mean kinematic variables before and after ACL reconstruction, and between the ACL-affected knees and contralateral knees before and after reconstruction. RESULTS: RTR was greater during high-demand tasks compared to low-demand tasks. Pre-operative, rTR was smaller in the ACL-deficient knees compared to the contralateral knees during all tests. After ACLR, a greater rTR was seen in ACL-reconstructed knees compared to pre-operative, but a smaller rTR compared to the contralateral knees, even during high-demand tasks. CONCLUSION: The smaller rTR, compared to the contralateral knee, seen after a subacute ACL tear may be attributed to altered landing technique, neuromuscular adaptation and fear of re-injury. The continued reduction in rTR one year after ACLR may be a combination of this neuromuscular adaptation and the biomechanical impact of the reconstruction. TRIAL REGISTRATION: The trial was registered in the Dutch Trial Register (NTR: www.trialregister.nl , registration ID NL7686).

Asunto(s)

RESUMEN

Kinematics of the knee during gait has mostly been studied using optical motion capture systems (MCS). The presence of soft tissue artifacts (STA) between the skin markers and the underlying bone presents a major impediment to obtaining a reliable joint kinematics assessment. In this study, we determined the effects of STA on the calculation of knee joint kinematics during walking and running, through the combination of high-speed dual fluoroscopic imaging system (DFIS) and magnetic resonance imaging technique. Ten adults walked and ran while data was collected simultaneously from MCS and high-speed DFIS. The study showed that measured STA underestimated knee flexion angle, but overestimated knee external and varus rotation. The absolute error values of the skin markers derived from knee flexion-extension angle, internal-external rotation, and varus-valgus rotation during walking were -3.2 ± 4.3 deg, 4.6 ± 3.1 deg, and 4.5 ± 3.2 deg respectively, and during running were -5.8 ± 5.4 deg, 6.6 ± 3.7 deg, and 4.8 ± 2.5 deg respectively. Average errors relative to the DFIS for flexion-extension angle, internal-external rotation, and varus-valgus rotation were 78 %, 271 %, 265 % during walking respectively, and were 43 %, 106 %, 200 % during running respectively. This study offers reference for the kinematic differences between MCS and high-speed DFIS, and will contribute to optimizing methods for analyzing knee kinematics during walking and running.

Asunto(s)

RESUMEN

A treatment method for suppressing shoulder pain by reducing the secretion of neurotransmitters in the brain is being studied in compliance with domestic and international standards. A robot is being developed to assist physical therapists in shoulder rehabilitation exercise treatment. The robot used for rehabilitation therapy enables the training of patients to perform rehabilitation exercises repeatedly. However, the biomechanical movement (or motion) of the shoulder joint should be accurately designed to enhance efficiency using a shoulder rehabilitation robot. Furthermore, safely treating patients by accurately evaluating biomechanical movements in compliance with domestic and international standards is a major task. Therefore, an in-depth analysis of shoulder movement is essential for understanding the mechanism of shoulder rehabilitation using robots. This paper proposes a method for analyzing shoulder movements. The rotation angle and range of motion (ROM) of the shoulder joint are measured by attaching a marker to the body and analyzing the inverse kinematics. The first motion is abduction and adduction, and the second is external and internal rotation. The location information of the marker is transmitted to an application software through an infrared camera. For the analysis using an inverse kinematics solution, five males and five females participated in the motion capture experiment. The subjects did not have any disability, and abduction and adduction were repeated 10 times. As a result, ROM of the abduction and adduction were 148° with males and 138.7° in females. Moreover, ROM of the external and internal rotation were 111.2° with males and 106° in females. Because this study enables tracking of the center coordinates of the joint suitably through a motion capture system, inverse kinematics can be accurately calculated. Additionally, a mathematical inverse kinematics equation will utilize follow-up study for designing an upper rehabilitations robot. The proposed method is assessed to be able to contribute to the definition of domestic and international standardization of rehabilitation robots and motion capture for objective evaluation.

RESUMEN

The clinical assessment of the human hand is typically conducted through questionnaires or tests that include objective (e.g., time) and subjective (e.g., grasp quality) outcome measures. However, there are other important indicators that should be considered to quantify grasp and movement quality in addition to the time needed by a subject to execute a task, and this is essential for human and artificial hands that attempt to replicate the human hand properties. The correct estimation of hand kinematics is fundamental for computing these indicators with high fidelity, and a technical background is typically required to perform this analysis. In addition, to understand human motor control strategies as well as to replicate them on artificial devices, postural synergies were widely explored in recent years. Synergies should be analyzed not only to investigate possible modifications due to musculoskeletal and/or neuromuscular disorders, but also to test biomimetic hands. The aim of this work is to present an open source toolbox to perform all-in-one kinematic analysis and clinical assessment of the hand, as well as to perform postural synergies extraction. In the example provided in this work, the tool takes as input the position of 28 retroreflective markers with a diameter of 6 mm, positioned on specific anatomical landmarks of the hand and recorded with an optoelectronic motion capture system, and automatically performs 1) hand kinematic analysis (i.e., computation of 23 joint angles); 2) clinical assessment, by computing indicators that allow quantifying movement efficiency (Peak Grip Aperture), smoothness (Normalized Dimensionless Jerk Grasp Aperture) and speed (Peak Velocity of Grasp Aperture), planning capabilities (Time to Peak Grip Aperture), spatial posture (Wrist and Finger Joint Angles) and grasp stability (Posture of Hand Finger Joints), and 3) postural synergies extraction and analysis through the Pareto, Scree and Loadings plots. Two examples are described to demonstrate the applicability of the toolbox: the first one aiming at performing a clinical assessment of a volunteer and the second one aiming at extracting and analyzing the volunteer's postural synergies. The tool allows calculating joint angles with high accuracy (reconstruction errors below 4 mm and 3.2 mm for the fingers and wrist respectively) and automatically performing clinical assessment and postural synergies extraction. Results can be visually inspected, and data can be saved for any desired post processing analysis. Custom-made protocols to extract joint angles, based on different markersets, could be also integrated in the toolbox. The tool can be easily exploitable in clinical contexts, as it does not require any particular technical knowledge to be used, as confirmed by the usability evaluation conducted (perceived usability = 94.2 ± 5.4). In addition, it can be integrated with the SynGrasp toolbox to perform grasp analysis of underactuated virtual hands based on postural synergies.

RESUMEN

Background: Markerless (ML) motion capture systems have recently become available for biomechanics applications. Evidence has indicated the potential feasibility of using an ML system to analyze lower extremity kinematics. However, no research has examined ML systems' estimation of the lower extremity joint moments and powers. This study aimed to compare lower extremity joint moments and powers estimated by marker-based (MB) and ML motion capture systems. Methods: Sixteen volunteers ran on a treadmill for 120 s at 3.58 m/s. The kinematic data were simultaneously recorded by 8 infrared cameras and 8 high-resolution video cameras. The force data were recorded via an instrumented treadmill. Results: Greater peak magnitudes for hip extension and flexion moments, knee flexion moment, and ankle plantarflexion moment, along with their joint powers, were observed in the ML system compared to an MB system (p < 0.0001). For example, greater hip extension (MB: 1.42 ± 0.29 vs. ML: 2.27 ± 0.45) and knee flexion (MB: −0.74 vs. ML: −1.17 nm/kg) moments were observed in the late swing phase. Additionally, the ML system's estimations resulted in significantly smaller peak magnitudes for knee extension moment, along with the knee production power (p < 0.0001). Conclusions: These observations indicate that inconsistent estimates of joint center position and segment center of mass between the two systems may cause differences in the lower extremity joint moments and powers. However, with the progression of pose estimation in the markerless system, future applications can be promising.

RESUMEN

The Perception Neuron Studio (PNS) is a cost-effective and widely used inertial motion capture system. However, a comprehensive analysis of its upper-body motion capture accuracy is still lacking, before it is being applied to biomechanical research. Therefore, this study first evaluated the validity and reliability of this system in upper-body capturing and then quantified the system's accuracy for different task complexities and movement speeds. Seven participants performed simple (eight single-DOF upper-body movements) and complex tasks (lifting a 2.5 kg box over the shoulder) at fast and slow speeds with the PNS and OptiTrack (gold-standard optical system) collecting kinematics data simultaneously. Statistical metrics such as CMC, RMSE, Pearson's r, R2, and Bland-Altman analysis were utilized to assess the similarity between the two systems. Test-retest reliability included intra- and intersession relations, which were assessed by the intraclass correlation coefficient (ICC) as well as CMC. All upper-body kinematics were highly consistent between the two systems, with CMC values 0.73-0.99, RMSE 1.9-12.5°, Pearson's r 0.84-0.99, R2 0.75-0.99, and Bland-Altman analysis demonstrating a bias of 0.2-27.8° as well as all the points within 95% limits of agreement (LOA). The relative reliability of intra- and intersessions was good to excellent (i.e., ICC and CMC were 0.77-0.99 and 0.75-0.98, respectively). The paired t-test revealed that faster speeds resulted in greater bias, while more complex tasks led to lower consistencies. Our results showed that the PNS could provide accurate enough upper-body kinematics for further biomechanical performance analysis.

Asunto(s)