Gaze tracking of large-billed crows (Corvus macrorhynchos) in a motion capture system.

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.

Validity and Reliability of Upper Limb Kinematic Assessment Using a Markerless Motion Capture (MMC) System: A Pilot Study.

OBJECTIVE: To investigate the validity and test-retest reliability of a customized markerless motion capture (MMC) system that used iPad Pros with a Light Detection And Ranging scanner at two different viewing angles to measure the active range of motion (AROM) and the angular waveform of the upper-limb-joint angles of healthy adults performing functional tasks. DESIGN: Participants were asked to perform shoulder and elbow actions for the investigator to take AROM measurements, followed by four tasks that simulated daily functioning. Each participant attended 2 experimental sessions, which were held at least 2 days and at most 14 days apart. SETTING: A Vicon system and 2 iPad Pros installed with our MMC system were placed at 2 different angles to the participants and recorded their movements concurrently during each task. PARTICIPANTS: Thirty healthy adults (mean age: 28.9, M/F ratio: 40/60). INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: The AROM and the angular waveform of the upper-limb-joint angles. RESULTS: The iPad Pro MMC system underestimated the shoulder joint and elbow joint angles in all four simulated functional tasks. The MMC demonstrated good to excellent test-retest reliability for the shoulder joint AROM measurements in all 4 tasks. CONCLUSIONS: The maximal AROM measurements calculated by the MMC system had consistently smaller values than those measured by the goniometer. An MMC in iPad Pro system might not be able to replace conventional goniometry for clinical ROM measurements, but it is still suggested for use in home-based and telerehabilitation training for intra-subject measurements because of its good reliability, low cost, and portability. Further development to improve its performance in motion capture and analysis in disease populations is warranted.

Do 3-dimensional Spinopelvic Characteristics Normalize After THA? A Prospective, Comparative Study Using Motion Capture Analysis.

BACKGROUND: Spinopelvic stiffness (primarily in the sagittal plane) has been identified as a factor associated with inferior patient-reported outcomes (PROs) and increased dislocation risk after THA. Incorporating preoperative spinopelvic characteristics into surgical planning has been suggested to determine a patient-specific cup orientation that minimizes dislocation risk. Sagittal plane radiographic analysis of static postures indicates that patients exhibit a degree of normalization in their spinopelvic characteristics after THA. It is not yet known whether normalization is also evident during dynamic movement patterns, nor whether it occurs in the coronal and axial planes as well. QUESTIONS/PURPOSES: (1) Does motion capture analysis of sagittal spinopelvic motion provide evidence of normalization after THA? (2) Do changes in coronal and axial plane motion accompany those in the sagittal plane? METHODS: Between April 2019 and February 2020, 25 patients agreed to undergo motion capture movement analysis before THA for the treatment of hip osteoarthritis (OA). Of those, 20 underwent the same assessment between 8 and 31 months after THA. Five patients were excluded because of revision surgery (n = 1), contralateral hip OA (n = 1), and technical issues with a force plate during post-THA assessment (n = 3), leaving a cohort total of 15 (median age [IQR] 65 years [10]; seven male and eight female patients). A convenience sample of nine asymptomatic volunteers, who were free of hip and spinal pathology, was also assessed (median age 51 years [34]; four male and five female patients). Although the patients in the control group were younger than those in the patient group, this set a high bar for our threshold of spinopelvic normalization, reducing the possibility of false positive results. Three-dimensional motion capture was performed to measure spinal, pelvic, and hip motion while participants completed three tasks: seated bend and reach, seated trunk rotation, and gait on a level surface. ROM during each task was assessed and compared between pre- and post-THA conditions and between patients and controls. Statistical parametric mapping (SPM) was used to assess the timing of differences in motion during gait, and spatiotemporal gait parameters were also measured. RESULTS: After THA, patients demonstrated improvements in sagittal spinal (median [IQR] 32° [18°] versus 41° [14°]; difference of medians 9°; p = 0.004), pelvis (25° [21°] versus 30° [8°]; difference of medians 5°; p = 0.02), and hip ROM (21° [18°] versus 27° [10°]; difference of medians 6°; p = 0.02) during seated bend and reach as well in sagittal hip ROM during gait (30° [11°] versus 44° [7°]; difference of medians 14°; p < 0.001) compared with their pre-THA results, and they showed a high degree of normalization overall. These sagittal plane changes were accompanied by post-THA increases in coronal hip ROM (12° [9°] versus 18° [8°]; difference of medians 6°; p = 0.01) during seated trunk rotation, by both coronal (6° [4°] versus 9° [3°]; difference of medians 3°; p = 0.01) and axial (10° [8°] versus 16° [7°]; difference of medians 6°; p = 0.003) spinal ROM, as well as coronal (8° [3°] versus 13° [4°]; difference of medians 5°; p < 0.001) and axial hip ROM (21° [11°] versus 34° [24°]; difference of medians 13°; p = 0.01) during gait compared with before THA. The SPM analysis showed these improvements occurred during the late swing and early stance phases of gait. CONCLUSION: When restricted preoperatively, spinopelvic characteristics during daily tasks show normalization after THA, concurring with previous radiographic findings in the sagittal plane. Thus, spinopelvic characteristics change dynamically, and incorporating them into surgical planning would require predictive models on post-THA improvements to be of use. LEVEL OF EVIDENCE: Level II, prognostic study.

Motion capture device reveals a quick learning curve in vascular anastomosis training.

PURPOSE: Surgical procedures are often evaluated subjectively, and an objective evaluation has been considered difficult to make and rarely reported, especially in open surgery, where the range of motion is wide. This study evaluated the effectiveness of surgical suturing training as an educational tool using the Leap Motion Controller (LMC), which can capture hand movements and reproduce them as data comprising parametric elements. METHODS: We developed an off-the-job training system (Off-JT) in our department, mainly using prosthetic grafts and various anastomotic methodologies with graded difficulty levels. We recruited 50 medical students (novice group) and 6 vascular surgeons (expert group) for the study. We evaluated four parameters for intraoperative skills: suturing time, slope of the roll, smoothness, and rate of excess motion. RESULTS: All 4 parameters distinguished the skill of the novice group at 1 and 10 h off-JT. After 10 h of off-JT, all 4 parameters of the novices were comparable to those of the expert group. CONCLUSION: Our education system using the LMC is relatively inexpensive and easy to set up, with a free application for analyses, serving as an effective and ubiquitous educational tool for young surgeons.

A review of combined functional neuroimaging and motion capture for motor rehabilitation.

BACKGROUND: Technological advancements in functional neuroimaging and motion capture have led to the development of novel methods that facilitate the diagnosis and rehabilitation of motor deficits. These advancements allow for the synchronous acquisition and analysis of complex signal streams of neurophysiological data (e.g., EEG, fNIRS) and behavioral data (e.g., motion capture). The fusion of those data streams has the potential to provide new insights into cortical mechanisms during movement, guide the development of rehabilitation practices, and become a tool for assessment and therapy in neurorehabilitation. RESEARCH OBJECTIVE: This paper aims to review the existing literature on the combined use of motion capture and functional neuroimaging in motor rehabilitation. The objective is to understand the diversity and maturity of technological solutions employed and explore the clinical advantages of this multimodal approach. METHODS: This paper reviews literature related to the combined use of functional neuroimaging and motion capture for motor rehabilitation following the PRISMA guidelines. Besides study and participant characteristics, technological aspects of the used systems, signal processing methods, and the nature of multimodal feature synchronization and fusion were extracted. RESULTS: Out of 908 publications, 19 were included in the final review. Basic or translation studies were mainly represented and based predominantly on healthy participants or stroke patients. EEG and mechanical motion capture technologies were most used for biomechanical data acquisition, and their subsequent processing is based mainly on traditional methods. The system synchronization techniques at large were underreported. The fusion of multimodal features mainly supported the identification of movement-related cortical activity, and statistical methods were occasionally employed to examine cortico-kinematic relationships. CONCLUSION: The fusion of motion capture and functional neuroimaging might offer advantages for motor rehabilitation in the future. Besides facilitating the assessment of cognitive processes in real-world settings, it could also improve rehabilitative devices' usability in clinical environments. Further, by better understanding cortico-peripheral coupling, new neuro-rehabilitation methods can be developed, such as personalized proprioceptive training. However, further research is needed to advance our knowledge of cortical-peripheral coupling, evaluate the validity and reliability of multimodal parameters, and enhance user-friendly technologies for clinical adaptation.

Role of joint interactions in upper limb joint movements: a disability simulation study using wearable inertial sensors for 3D motion capture.

BACKGROUND: Restriction of movement at a joint due to disease or dysfunction can alter the range of motion (ROM) at other joints due to joint interactions. In this paper, we quantify the extent to which joint restrictions impact upper limb joint movements by conducting a disability simulation study that used wearable inertial sensors for three-dimensional (3D) motion capture. METHODS: We employed the Wearable Inertial Sensors for Exergames (WISE) system for assessing the ROM at the shoulder (flexion-extension, abduction-adduction, and internal-external rotation), elbow (flexion-extension), and forearm (pronation-supination). We recruited 20 healthy individuals to first perform instructed shoulder, elbow, and forearm movements without any external restrictions, and then perform the same movements with restriction braces placed to limit movement at the shoulder, elbow, and forearm, separately, to simulate disability. To quantify the extent to which a restriction at a non-instructed joint affected movement at an instructed joint, we computed average percentage reduction in ROM in the restricted versus unrestricted conditions. Moreover, we performed analysis of variance and post hoc Tukey tests (q statistic) to determine the statistical significance (p < 0.05 denoted using *) of the differences in ROM of an instructed joint in the unrestricted versus restricted conditions. RESULTS: Restricting movement at the shoulder led to a large reduction in the average ROM for elbow flexion-extension (21.93%, q = 9.34*) and restricting elbow movement significantly reduced the average ROM for shoulder flexion-extension (17.77%, q = 8.05*), shoulder abduction-adduction (19.80%, q = 7.60*), and forearm pronation-supination (14.04%, q = 4.96*). Finally, restricting the forearm significantly reduced the average ROM for shoulder internal-external rotation (16.71%, q = 3.81*) and elbow flexion-extension (10.01%, q = 4.27*). CONCLUSIONS: Joint interactions across non-instructed joints can reduce the ROM of instructed movements. Assessment of ROM in the real-world using 3D motion capture, for example using the WISE system, can aid in understanding movement limitations, informing interventions, and monitoring progress with rehabilitation.

Exploring stroke survivors' and physiotherapists' perspectives of the potential for markerless motion capture technology in community rehabilitation.

INTRODUCTION: Many stroke survivors do not receive optimal levels of personalised therapy to support their recovery. Use of technology for stroke rehabilitation has increased in recent years to help minimise gaps in service provision. Markerless motion capture technology is currently being used for musculoskeletal and occupational health screening and could offer a means to provide personalised guidance to stroke survivors struggling to access rehabilitation. AIMS: This study considered context, stakeholders, and key uncertainties surrounding the use of markerless motion capture technology in community stroke rehabilitation from the perspectives of stroke survivors and physiotherapists with a view to adapting an existing intervention in a new context. METHODS: Three focus groups were conducted with eight stroke survivors and five therapists. Data were analysed using reflexive thematic analysis. RESULTS: Five themes were identified: limited access to community care; personal motivation; pandemic changed rehabilitation practice; perceptions of technology; and role of markerless technology for providing feedback. CONCLUSIONS: Participants identified problems associated with the access of community stroke rehabilitation, exacerbated by Covid-19 restrictions. Participants were positive about the potential for the use of markerless motion capture technology to support personalised, effective stroke rehabilitation in the future, providing it is developed to meet stroke survivor specific needs.

Emotion in motion: perceiving fear in the behaviour of individuals from minimal motion capture displays.

The ability to quickly and accurately recognise emotional states is adaptive for numerous social functions. Although body movements are a potentially crucial cue for inferring emotions, few studies have studied the perception of body movements made in naturalistic emotional states. The current research focuses on the use of body movement information in the perception of fear expressed by targets in a virtual heights paradigm. Across three studies, participants made judgments about the emotional states of others based on motion-capture body movement recordings of those individuals actively engaged in walking a virtual plank at ground-level or 80 stories above a city street. Results indicated that participants were reliably able to differentiate between height and non-height conditions (Studies 1 & 2), were more likely to spontaneously describe target behaviour in the height condition as fearful (Study 2) and their fear estimates were highly calibrated with the fear ratings from the targets (Studies 1-3). Findings show that VR height scenarios can induce fearful behaviour and that people can perceive fear in minimal representations of body movement.

Validation of LEOMO inertial measurement unit sensors with marker-based three-dimensional motion capture during maximum sprinting in track cyclists.

LEOMO™ is a commercial inertial measurement unit system that provides cycling-specific motion performance indicators (MPIs) and offers a mobile solution for monitoring cyclists. We aimed to validate the LEOMO sensors during sprint cycling using gold-standard marker-based three-dimensional (3D) motion technology (Qualisys, AB). Our secondary aim was to explore the relationship between peak power during sprints and MPIs. Seventeen elite track cyclists performed 3 × 15s seated start maximum efforts on a cycle ergometer. Based on intraclass correlation coefficient (ICC3,1), the MPIs derived from 3D and LEOMO showed moderate agreement (0.50 < 0.75) for the right foot angular range (FAR); left foot angular range first quadrant (FARQ1); right leg angular range (LAR); and mean angle of the pelvis in the sagittal plane. Agreement was poor (ICC < 0.50) between MPIs derived from 3D and LEOMO for the left FAR, right FARQ1, left LAR, and mean range of motion of the pelvis in the frontal and transverse planes. Only one LEOMO-derived (pelvic rotation) and two 3D-derived (right FARQ1 and FAR) MPIs showed large positive significant correlations with peak power. Caution is advised regarding use of the LEOMO for short maximal cycling efforts and derived MPIs to inform peak sprint cycling power production.

Validity and reliability of trunk and lower-limb kinematics during squatting, hopping, jumping and side-stepping using OpenCap markerless motion capture application.

OpenCap is a web-based markerless motion capture platform that estimates 3D kinematics from videos recorded from at least two iOS devices. This study aimed to determine the concurrent validity and inter-session reliability of OpenCap for measuring trunk and lower-limb kinematics during squatting, hopping, countermovement jumping, and cutting. Nineteen participants (10 males, 9 females; age 27.7 ± 4.1 years) were included. Countermovement jump, single-leg triple vertical hop, single-leg squat, sidestep cutting and side hop tasks were assessed. For validity, OpenCap was compared to a marker-based motion capture system using root-mean-square error. Test-retest reliability of OpenCap was determined using intraclass correlations and minimum detectable change (MDC) from two testing sessions. The squat had the lowest RMSE across joint angles (mean = 7.0°, range = 2.9° to 13.6°). For peak angles, the countermovement jump (jump phase) (ICC = 0.62-0.93) and the squat (ICC = 0.60-0.92) had the best reliability across all joints. For initial contact, the side hop had the best inter-session reliability (ICC = 0.70-0.94) across all joint angles. As such, OpenCap validity and reliability are joint and task specific.

Estimating Compressive and Shear Forces at L5-S1: Exploring the Effects of Load Weight, Asymmetry, and Height Using Optical and Inertial Motion Capture Systems.

This study assesses the agreement of compressive and shear force estimates at the L5-S1 joint using inertial motion capture (IMC) within a musculoskeletal simulation model during manual lifting tasks, compared against a top-down optical motion capture (OMC)-based model. Thirty-six participants completed lifting and lowering tasks while wearing a modified Plug-in Gait marker set for the OMC and a full-body IMC set-up consisting of 17 sensors. The study focused on tasks with variable load weights, lifting heights, and trunk rotation angles. It was found that the IMC system consistently underestimated the compressive forces by an average of 34% (975.16 N) and the shear forces by 30% (291.77 N) compared with the OMC system. A critical observation was the discrepancy in joint angle measurements, particularly in trunk flexion, where the IMC-based model underestimated the angles by 10.92-11.19 degrees on average, with the extremes reaching up to 28 degrees. This underestimation was more pronounced in tasks involving greater flexion, notably impacting the force estimates. Additionally, this study highlights significant differences in the distance from the spine to the box during these tasks. On average, the IMC system showed an 8 cm shorter distance on the X axis and a 12-13 cm shorter distance on the Z axis during lifting and lowering, respectively, indicating a consistent underestimation of the segment length compared with the OMC system. These discrepancies in the joint angles and distances suggest potential limitations of the IMC system's sensor placement and model scaling. The load weight emerged as the most significant factor affecting force estimates, particularly at lower lifting heights, which involved more pronounced flexion movements. This study concludes that while the IMC system offers utility in ergonomic assessments, sensor placement and anthropometric modeling accuracy enhancements are imperative for more reliable force and kinematic estimations in occupational settings.

A Low-Cost Inertial Measurement Unit Motion Capture System for Operation Posture Collection and Recognition.

In factories, human posture recognition facilitates human-machine collaboration, human risk management, and workflow improvement. Compared to optical sensors, inertial sensors have the advantages of portability and resistance to obstruction, making them suitable for factories. However, existing product-level inertial sensing solutions are generally expensive. This paper proposes a low-cost human motion capture system based on BMI 160, a type of six-axis inertial measurement unit (IMU). Based on WIFI communication, the collected data are processed to obtain the displacement of human joints' rotation angles around XYZ directions and the displacement in XYZ directions, then the human skeleton hierarchical relationship was combined to calculate the real-time human posture. Furthermore, the digital human model was been established on Unity3D to synchronously visualize and present human movements. We simulated assembly operations in a virtual reality environment for human posture data collection and posture recognition experiments. Six inertial sensors were placed on the chest, waist, knee joints, and ankle joints of both legs. There were 16,067 labeled samples obtained for posture recognition model training, and the accumulated displacement and the rotation angle of six joints in the three directions were used as input features. The bi-directional long short-term memory (BiLSTM) model was used to identify seven common operation postures: standing, slightly bending, deep bending, half-squatting, squatting, sitting, and supine, with an average accuracy of 98.24%. According to the experiment result, the proposed method could be used to develop a low-cost and effective solution to human posture recognition for factory operation.

Detection and Evaluation for High-Quality Cardiopulmonary Resuscitation Based on a Three-Dimensional Motion Capture System: A Feasibility Study.

High-quality cardiopulmonary resuscitation (CPR) and training are important for successful revival during out-of-hospital cardiac arrest (OHCA). However, existing training faces challenges in quantifying each aspect. This study aimed to explore the possibility of using a three-dimensional motion capture system to accurately and effectively assess CPR operations, particularly about the non-quantified arm postures, and analyze the relationship among them to guide students to improve their performance. We used a motion capture system (Mars series, Nokov, China) to collect compression data about five cycles, recording dynamic data of each marker point in three-dimensional space following time and calculating depth and arm angles. Most unstably deviated to some extent from the standard, especially for the untrained students. Five data sets for each parameter per individual all revealed statistically significant differences (p < 0.05). The correlation between Angle 1' and Angle 2' for trained (rs = 0.203, p < 0.05) and untrained students (rs = -0.581, p < 0.01) showed a difference. Their performance still needed improvement. When conducting assessments, we should focus on not only the overall performance but also each compression. This study provides a new perspective for quantifying compression parameters, and future efforts should continue to incorporate new parameters and analyze the relationship among them.

Obesity-Specific Considerations for Assessing Gait with Inertial Measurement Unit-Based vs. Optokinetic Motion Capture.

Adults with obesity experience high rates of disability and rapid functional decline. Identifying movement dysfunction early can direct intervention and disrupt disability development; however, subtle changes in movement are difficult to detect with the naked eye. This study evaluated how a portable, inertial measurement unit (IMU)-based motion capture system compares to a laboratory-based optokinetic motion capture (OMC) system for evaluating gait kinematics in adults with obesity. Ten adults with obesity performed overground walking while equipped with the OMC and IMU systems. Fifteen gait cycles for each participant were extracted for the 150 total cycles analyzed. Kinematics were compared between OMC and IMU across the gait cycles (coefficient of multiple correlations), at clinically significant time points (interclass correlations), and over clinically relevant ranges (Bland-Altman plots). Sagittal plane kinematics were most similar between systems, especially at the knee. Sagittal plane joint angles at clinically meaningful timepoints were poorly associated except for ankle dorsiflexion at heel strike (ρ = 0.38) and minimum angle (ρ = 0.83). All motions except for ankle dorsiflexion and hip abduction had >5° difference between systems across the range of angles measured. While IMU-based motion capture shows promise for detecting subtle gait changes in adults with obesity, more work is needed before this method can replace traditional OMC. Future work should explore standardization procedures to improve consistency of IMU motion capture performance.

Accessibility of Motion Capture as a Tool for Sports Performance Enhancement for Beginner and Intermediate Cricket Players.

Motion Capture (MoCap) has become an integral tool in fields such as sports, medicine, and the entertainment industry. The cost of deploying high-end equipment and the lack of expertise and knowledge limit the usage of MoCap from its full potential, especially at beginner and intermediate levels of sports coaching. The challenges faced while developing affordable MoCap systems for such levels have been discussed in order to initiate an easily accessible system with minimal resources.

Comparison of Shoulder Range of Motion Quantified with Mobile Phone Video-Based Skeletal Tracking and 3D Motion Capture-Preliminary Study.

BACKGROUND: The accuracy of human pose tracking using smartphone camera (2D-pose) to quantify shoulder range of motion (RoM) is not determined. METHODS: Twenty healthy individuals were recruited and performed shoulder abduction, adduction, flexion, or extension, captured simultaneously using a smartphone-based human pose estimation algorithm (Apple's vision framework) and using a skin marker-based 3D motion capture system. Validity was assessed by comparing the 2D-pose outcomes against a well-established 3D motion capture protocol. In addition, the impact of iPhone positioning was investigated using three smartphones in multiple vertical and horizontal positions. The relationship and validity were analysed using linear mixed models and Bland-Altman analysis. RESULTS: We found that 2D-pose-based shoulder RoM was consistent with 3D motion capture (linear mixed model: R2 > 0.93) but was somewhat overestimated by the smartphone. Differences were dependent on shoulder movement type and RoM amplitude, with adduction the worst performer among all tested movements. All motion types were described using linear equations. Correction methods are provided to correct potential out-of-plane shoulder movements. CONCLUSIONS: Shoulder RoM estimated using a smartphone camera is consistent with 3D motion-capture-derived RoM; however, differences between the systems were observed and are likely explained by differences in thoracic frame definitions.

American Sign Language Recognition and Translation Using Perception Neuron Wearable Inertial Motion Capture System.

Sign language is designed as a natural communication method to convey messages among the deaf community. In the study of sign language recognition through wearable sensors, the data sources are limited, and the data acquisition process is complex. This research aims to collect an American sign language dataset with a wearable inertial motion capture system and realize the recognition and end-to-end translation of sign language sentences with deep learning models. In this work, a dataset consisting of 300 commonly used sentences is gathered from 3 volunteers. In the design of the recognition network, the model mainly consists of three layers: convolutional neural network, bi-directional long short-term memory, and connectionist temporal classification. The model achieves accuracy rates of 99.07% in word-level evaluation and 97.34% in sentence-level evaluation. In the design of the translation network, the encoder-decoder structured model is mainly based on long short-term memory with global attention. The word error rate of end-to-end translation is 16.63%. The proposed method has the potential to recognize more sign language sentences with reliable inertial data from the device.

Vertical Center-of-Mass Braking and Motor Performance during Gait Initiation in Young Healthy Adults, Elderly Healthy Adults, and Patients with Parkinson's Disease: A Comparison of Force-Plate and Markerless Motion Capture Systems.

BACKGROUND: This study tested the agreement between a markerless motion capture system and force-plate system ("gold standard") to quantify stability control and motor performance during gait initiation. METHODS: Healthy adults (young and elderly) and patients with Parkinson's disease performed gait initiation series at spontaneous and maximal velocity on a system of two force-plates placed in series while being filmed by a markerless motion capture system. Signals from both systems were used to compute the peak of forward center-of-mass velocity (indicator of motor performance) and the braking index (indicator of stability control). RESULTS: Descriptive statistics indicated that both systems detected between-group differences and velocity effects similarly, while a Bland-Altman plot analysis showed that mean biases of both biomechanical indicators were virtually zero in all groups and conditions. Bayes factor 01 indicated strong (braking index) and moderate (motor performance) evidence that both systems provided equivalent values. However, a trial-by-trial analysis of Bland-Altman plots revealed the possibility of differences >10% between the two systems. CONCLUSION: Although non-negligible differences do occur, a markerless motion capture system appears to be as efficient as a force-plate system in detecting Parkinson's disease and velocity condition effects on the braking index and motor performance.

A Flexible Wearable Sensor Based on Laser-Induced Graphene for High-Precision Fine Motion Capture for Pilots.

There has been a significant shift in research focus in recent years toward laser-induced graphene (LIG), which is a high-performance material with immense potential for use in energy storage, ultrahydrophobic water applications, and electronic devices. In particular, LIG has demonstrated considerable potential in the field of high-precision human motion posture capture using flexible sensing materials. In this study, we investigated the surface morphology evolution and performance of LIG formed by varying the laser energy accumulation times. Further, to capture human motion posture, we evaluated the performance of highly accurate flexible wearable sensors based on LIG. The experimental results showed that the sensors prepared using LIG exhibited exceptional flexibility and mechanical performance when the laser energy accumulation was optimized three times. They exhibited remarkable attributes, such as high sensitivity (~41.4), a low detection limit (0.05%), a rapid time response (response time of ~150 ms; relaxation time of ~100 ms), and excellent response stability even after 2000 s at a strain of 1.0% or 8.0%. These findings unequivocally show that flexible wearable sensors based on LIG have significant potential for capturing human motion posture, wrist pulse rates, and eye blinking patterns. Moreover, the sensors can capture various physiological signals for pilots to provide real-time capturing.

Inertial Motion Capture-Driven Digital Human for Ergonomic Validation: A Case Study of Core Drilling.

In the evolving realm of ergonomics, there is a growing demand for enhanced comfortability, visibility, and accessibility in the operation of engineering machinery. This study introduces an innovative approach to assess the ergonomics of a driller's cabin by utilizing a digital human. Through the utilization of inertial motion capture sensors, the method enables the operation of a virtual driller animated by real human movements, thereby producing more precise and realistic human-machine interaction data. Additionally, this study develops a simplified model for the human upper limbs, facilitating the calculation of joint forces and torques. An ergonomic analysis platform, encompassing a virtual driller's cabin and a digital human model, is constructed using Unity 3D. This platform enables the quantitative evaluation of comfortability, visibility, and accessibility. Its versatility extends beyond the current scope, offering substantial support for product development and enhancement.