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The assessment of color vision is crucial in both fundamental visual research and clinical diagnosis. However, existing tools for color vision assessment are limited by various factors. This study introduces a novel, efficient method for color vision assessment, which is based on a continuous motion tracking task and a Kalman filter model. The effectiveness of this new method was evaluated by assessing the color vision of both color-deficient observers and normal controls. The results from both a small sample (N = 29, Experiment 1) and a large sample (N = 171, Experiment 2) showed that color-deficient observers could be perfectly identified within 20 s using the tracking performance. We also compared the new method with a traditional psychophysical detection task to examine the consistency of perceptual noise estimation between the two methods, and the results showed a moderate correlation (Pearson's r =.59 ~.64). The results also demonstrated that the new method could measure individuals’ contrast response functions of both red–green and blue–yellow colors (e.g., the L–M and S–(L + M) axes in DKL color space) in just a few minutes, showing much higher efficiency than traditional methods. All the findings from this study indicate that the continuous motion tracking method is a promising tool for both rapid screening of color vision deficiencies and fundamental research on color vision. [ABSTRACT FROM AUTHOR]

The accurate assessment of cardiac motion is crucial for diagnosing and monitoring cardiovascular diseases. In this context, digital volume correlation (DVC) has emerged as a promising technique for tracking cardiac motion from cardiac computed tomography angiographic (CTA) images. This paper presents a comprehensive performance evaluation of the DVC method, specifically focusing on tracking the motion of the left atrium using cardiac CTA data. The study employed a comparative experimental approach while simultaneously optimizing the existing DVC algorithm. Multiple sets of controlled experiments were designed to conduct quantitative analyses on the parameters “radius” and “step”. The results revealed that the optimized DVC algorithm enhanced tracking accuracy within a reasonable computational time. These findings contributed to the understanding of the efficacy and limitations of the DVC algorithm in analyzing heart deformation. [ABSTRACT FROM AUTHOR]

This article describes a study exploring the expressive and creative potential of dance phrase onsets and endings in interactive dance, using an artistic research approach. After describing the context and background of interactive dance and relevant perceptual issues, the technical setup is presented, both in terms of the performance area, sensors and other hardware, and software. The main part of the article is concerned with the specific movement-sound mappings and their relation to the dancer's movement choices in four different sections in the performance that the project resulted in, entitled Beginnings and Endings - Study I. Subsequently, the process and performance are evaluated, specifically focusing on the performer's perspective. The most interesting points from the evaluation are then discussed with reference to the presented mappings, related movement choices, and relevant research literature. Findings include that the dancer experienced an increased awareness of beginnings and endings in different sections of the performance, that the affordances of different mappings were explored in different ways and to different degrees, and that some of this could be ascribed to a dynamic between liberation and restriction. [ABSTRACT FROM AUTHOR]

Accurate and efficient motion estimation is a crucial component of real-time ultrasound elastography (USE). However, obtaining radiofrequency ultrasound (RF) data in clinical practice can be challenging. In contrast, although B-mode (BM) data is readily available, elastographic data derived from BM data results in sub-optimal elastographic images. Furthermore, existing conventional ultrasound devices (e.g., portable devices) cannot provide elastography modes, which has become a significant obstacle to the widespread use of traditional ultrasound devices. To address the challenges above, we developed a teacher-student guided knowledge distillation for an unsupervised convolutional neural network (TSGUPWC-Net) to improve the accuracy of BM motion estimation by employing a well-established convolutional neural network (CNN) named modified pyramid warping and cost volume network (MPWC-Net). A pre-trained teacher model based on RF is utilized to guide the training of a student model using BM data. Innovations outlined below include employing spatial attention transfer at intermediate layers to enhance the guidance effect of the model. The loss function consists of smoothness of the displacement field, knowledge distillation loss, and intermediate layer loss. We evaluated our method on simulated data, phantoms, and in vivo ultrasound data. The results indicate that our method has higher signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) values in axial strain estimation than the model trained on BM. The model is unsupervised and requires no ground truth labels during training, making it highly promising for motion estimation applications. [ABSTRACT FROM AUTHOR]

Patients with motor impairments (e.g., stroke, bone fracture, Parkinson's) are sensitive to the wearing experience of rehabilitation devices, and they often have difficulty accurately positioning them at an accurate position. While solutions involving optical systems or IMUs could potentially help alleviate the issue, they often introduce other challenges such as privacy concerns or discomforting experiences. With the emergence of wearable soft sensors during the last few decades, researchers widely apply soft sensors in rehabilitation to improve the wearing experience. However, these approaches have primarily focused on analyzing the sensor readings to improve accuracy rather than addressing the needs of patients and healthcare providers, and there is a lack of comprehensive design investigation and need assessment based on soft sensor-based rehabilitation systems for motor-impaired patients and their doctors. In this study, we developed an application, RehabFAB, utilizing fabric sensors for rehabilitation purposes. Besides, we evaluated our application and device and investigated the needs of patients and doctors for potential home rehabilitation applications. The investigation was conducted through thematic analysis, correlation analysis and System Usability Scale. The experimental results validated the efficacy, reliability and usability of our approach, with a SUS score of 81.75. In addition, the RehabFAB meets the expectations of motor-impaired patients and medical professionals as a home rehabilitation tool. Our core contributions lie in a thorough evaluation of the needs of motor-impaired patients in order to design a stable and reliable motion-tracking device based on soft sensors for their recovery. [ABSTRACT FROM AUTHOR]

This study examined the relation between movement amplitude and tempo during self-paced rhythmic finger tapping to test a preferred velocity account of the preferred tempo construct. Preferred tempo refers to the concept that individuals have preferences for the pace of actions or events in their environment (e.g., the desired pace of walking or tempo of music). The preferred velocity hypothesis proposes that assessments of preferred tempo do not represent a pure time preference independent of spatial movement characteristics, but rather reflects a preference for an average movement velocity, predicting that preferred tempo will depend on movement amplitude. We tested this by having participants first perform a novel spontaneous motor amplitude (SMA) task in which they repetitively tapped their finger at their preferred amplitude without instructions about tapping tempo. Next, participants completed the spontaneous motor tempo (SMT) task in which they tapped their finger at their preferred tempo without instructions about tapping amplitude. Finally, participants completed a target amplitude version of the SMT task where they tapped at their preferred tempo at three target amplitudes (low, medium, and high). Participants (1) produced similar amplitudes and tempi regardless of instructions to produce either their preferred amplitude or preferred tempo, maintaining the same average movement velocity across SMA and SMT tasks and (2) altered their preferred tempo for different target amplitudes in the direction predicted by their estimated preferred velocity from the SMA and SMT tasks. Overall, results show the interdependence of movement amplitude and tempo in tapping assessments of preferred tempo. [ABSTRACT FROM AUTHOR]

Introduction: Treatment of both simple and complex patella fractures is a challenging clinical problem. Although tension band wiring has been the standard of care, it can be associated with high complication rates. The aim of this study was to investigate the biomechanical performance of recently developed lateral rim variable angle locking plates versus tension band wiring used for fixation of simple and complex patella fractures. Materials and methods: Sixteen pairs of human anatomical knees were used to simulate either two-part transverse simple AO/OTA 34-C1 or five-part complex AO/OTA 34-C3 patella fractures by means of osteotomies, with each fracture model created in eight pairs. The complex fracture pattern was characterized by a medial and a lateral proximal fragment, together with an inferomedial, an inferolateral, and an inferior (central distal) fragment mimicking comminution around the distal patellar pole. The specimens with simple fractures were pairwise assigned for fixation with either tension band wiring through two parallel cannulated screws or a lateral rim variable angle locking plate. The knees with complex fractures were pairwise treated with either tension band wiring through two parallel cannulated screws plus circumferential cerclage wiring or a lateral rim variable angle locking plate. Each specimen was tested over 5000 cycles by pulling on the quadriceps tendon, simulating active knee extension and passive knee flexion within the range of 90° flexion to full extension. Interfragmentary movements were captured via motion tracking. Results: For both fracture types, the articular displacements measured between the proximal and distal fragments at the central patella aspect between 1000 and 5000 cycles, together with the relative rotations of these fragments around the mediolateral axis were all significantly smaller following the lateral rim variable angle locked plating compared with tension band wiring, p ≤ 0.01. Conclusions: From a biomechanical perspective, lateral rim variable angle locked plating of both simple and complex patella fractures provides superior construct stability versus tension band wiring under dynamic loading. [ABSTRACT FROM AUTHOR]

Ultrasonic transit time (TT)-based local pulse wave velocity (PWV) measurement is defined as the distance between two beam positions on a segment of common carotid artery (CCA) divided by the TT in the pulse wave propagation. However, the arterial wall motions (AWMs) estimated from ultrasonic radio frequency (RF) signals with a limited number of frames using the motion tracking are typically discrete. In this work, we develop a method involving motion tracking combined with reconstructive interpolation (MTRI) to reduce the quantification errors in the estimated PWs, and thereby improve the accuracy of the TT-based local PWV measurement for CCA. For each beam position, normalized cross-correlation functions (NCCFs) between the reference (the first frame) and comparison (the remaining frames) RF signals are calculated. Thereafter, the reconstructive interpolation is performed in the neighborhood of the NCCFs' peak to identify the interpolation-deduced peak locations, which are more exact than the original ones. According to which, the improved AWMs are obtained to calculate their TT along a segment of the CCA. Finally, the local PWV is measured by applying a linear regression fit to the time-distance result. In ultrasound simulations based on the pulse wave propagation models of young, middle-aged, and elderly groups, the MTRI method with different numbers of interpolated samples was used to estimate AWMs and local PWVs. Normalized root mean squared errors (NRMSEs) between the estimated and preset values of the AWMs and local PWVs were calculated and compared with ones without interpolation. The means of the NRMSEs for the AWMs and local PWVs based on the MTRI method with one interpolated sample decrease from 1.14% to 0.60% and 7.48% to 4.61%, respectively. Moreover, Bland-Altman analysis and coefficient of variation were used to validate the performance of the MTRI method based on the measured local PWVs of 30 healthy subjects. In conclusion, the reconstructive interpolation for the pulse wave estimation improves the accuracy and repeatability of the carotid local PWV measurement. Ultrasonic transit time-based local pulse wave velocity (PWV) measurement is defined as the distance between two beam positions on a segment of common carotid artery (CCA) divided by the transit time of the pulse wave (PW). However, PWs estimated from ultrasonic radio frequency (RF) signals with a limited number of frames using the motion tracking are typically discontinuous. In this work, a method that involves motion tracking combined with reconstructive interpolation (MTRI) is proposed for PW estimation to improve local PWV measurement. For each beam position, normalized cross-correlation functions (NCCFs) between the reference (the first frame) and comparison (the remaining frames) RF signals are calculated. Thereafter, the reconstructive interpolation is performed in the neighborhood of the NCCFs' peak to identify the interpolation-deduced peak locations, which are more exact than the original ones. According to which, the improved PWs are obtained to calculate their transit time along a segment of the CCA. Finally, the local PWV is measured by applying a linear regression fit to the time-distance result. In ultrasound simulations based on the PW propagation models of young, middle-aged, and elderly groups, the MTRI method with different numbers of interpolated samples was used to estimate PWs and local PWVs. Normalized root mean squared errors (NRMSEs) between the estimated and preset values of the PWs and local PWVs were calculated and compared with ones without interpolation. The means of the NRMSEs for the PWs and local PWVs based on the MTRI method with one interpolated sample decrease from 1.14% to 0.60% and 7.48% to 4.61%, respectively. Moreover, Bland-Altman analysis and coefficient of variation were used to validate the performance of the MTRI method based on the measured local PWVs of 30 healthy subjects. In conclusion, the MTRI method can improve the PW estimation and thus afford more accurate local PWV measurement. [ABSTRACT FROM AUTHOR]

Background/Purpose: The surgical fixation of a symphyseal diastasis in partially or fully unstable pelvic ring injuries is an important element when stabilizing the anterior pelvic ring. Currently, open reduction and internal fixation (ORIF) by means of plating represents the gold standard treatment. Advances in percutaneous fixation techniques have shown improvements in blood loss, surgery time, and scar length. Therefore, this approach should also be adopted for treatment of symphyseal injuries. The technique could be important since failure rates, following ORIF at the symphysis, remain unacceptably high. The aim of this biomechanical study was to assess a semi-rigid fixation technique for treatment of such anterior pelvic ring injuries versus current gold standards of plate osteosynthesis. Methods: An anterior pelvic ring injury type III APC according to the Young and Burgess classification was simulated in eighteen composite pelvises, assigned to three groups (n = 6) for fixation with either a single plate, two orthogonally positioned plates, or the semi-rigid technique using an endobutton suture implant. Biomechanical testing was performed in a simulated upright standing position under progressively increasing cyclic loading at 2 Hz until failure or over 150,000 cycles. Relative movements between the bone segments were captured by motion tracking. Results: Initial quasi-static and dynamic stiffness, as well as dynamic stiffness after 100,000 cycles, was not significantly different among the fixation techniques (p ≥ 0.054).). The outcome measures for total displacement after 20,000, 40,000, 60,000, 80,000, and 100,000 cycles were associated with significantly higher values for the suture technique versus double plating (p = 0.025), without further significant differences among the techniques (p ≥ 0.349). Number of cycles to failure and load at failure were highest for double plating (150,000 ± 0/100.0 ± 0.0 N), followed by single plating (132,282 ± 20,465/91.1 ± 10.2 N), and the suture technique (116,088 ± 12,169/83.0 ± 6.1 N), with significantly lower values in the latter compared to the former (p = 0.002) and no further significant differences among the techniques (p ≥ 0.329). Conclusion: From a biomechanical perspective, the semi-rigid technique for fixation of unstable pubic symphysis injuries demonstrated promising results with moderate to inferior behaviour compared to standard plating techniques regarding stiffness, cycles to failure and load at failure. This knowledge could lay the foundation for realization of further studies with larger sample sizes, focusing on the stabilization of the anterior pelvic ring. [ABSTRACT FROM AUTHOR]

Data on surgical robots are not openly accessible, limiting further study of the operation trajectory of surgeons' hands. Therefore, a trajectory monitoring system should be developed to examine objective indicators reflecting the characteristic parameters of operations. 20 robotic experts and 20 first-year residents without robotic experience were included in this study. A dry-lab suture task was used to acquire relevant hand performance data. Novices completed training on the simulator and then performed the task, while the expert team completed the task after warm-up. Stitching errors were measured using a visual recognition method. Videos of operations were obtained using the camera array mounted on the robot, and the hand trajectory of the surgeons was reconstructed. The stitching accuracy, robotic control parameters, balance and dexterity parameters, and operation efficiency parameters were compared. Experts had smaller center distance (p < 0.001) and larger proximal distance between the hands (p < 0.001) compared with novices. The path and volume ratios between the left and right hands of novices were larger than those of experts (both p < 0.001) and the total volume of the operation range of experts was smaller (p < 0.001). The surgeon trajectory optical monitoring system is an effective and non-subjective method to distinguish skill differences. This demonstrates the potential of pan-platform use to evaluate task completion and help surgeons improve their robotic learning curve. [ABSTRACT FROM AUTHOR]

Purpose: During reconstructive surgery, knee and hip replacements, and orthognathic surgery, small misalignments in the pose of prosthesis and bones can lead to severe complications. Hence, the translational and angular accuracies are critical. However, traditional image-based surgical navigation lacks orientation data between structures, and imageless systems are unsuitable for cases of deformed anatomy. We introduce an open-source navigation system using a multiple registration approach that can track instruments, implants, and bones to precisely guide the surgeon in emulating a preoperative plan. Methods: We derived the analytical error of our method and designed a set of phantom experiments to measure its precision and accuracy. Additionally, we trained two classification models to predict the system reliability from fiducial points and surface matching registration data. Finally, to demonstrate the procedure feasibility, we conducted a complete workflow for a real clinical case of a patient with fibrous dysplasia and anatomical misalignment of the right femur using plastic bones. Results: The system is able to track the dissociated fragments of the clinical case and average alignment errors in the anatomical phantoms of 1.08 ± 0.68 mm and 1.49 ± 1. 19 ∘ . While the fiducial-points registration showed satisfactory results given enough points and covered volume, we acknowledge that the surface refinement step is mandatory when attempting surface matching registrations. Conclusion: We believe that our device could bring significant advantages for the personalized treatment of complex surgical cases and that its multi-registration attribute is convenient for intraoperative registration loosening cases. [ABSTRACT FROM AUTHOR]

The application of additive-manufactured cores and molds is of great interest for complex cast components. Nevertheless, several challenges still exist in utilizing binder jetting in the multi-step additive manufacturing process for foundry applications to its fullest extent. This contribution shows methods that facilitate the use of 3D-printed sand molds and cores in casting series applications. The binder jetting process itself is assessed from an overall process chain perspective to highlight the benefits of its application in series production. The challenges associated with automating mold cleaning for highly complex casting contours are depicted. In particular, employing the method of cleanable mold partitioning is shown to enhance the automation level of the overall process. Mold design tailored to 3D printing is demonstrated to contribute to overall cost and time savings in enhanced core packages. Topology-optimized, lightweight part designs involving complex freeform surfaces may require mold partitioning associated with laborious burr removal processes. A new approach in answer to the shortage of skilled workers in the harsh and hazardous foundry environment is shown. Implementing motion tracking technology is demonstrated to enable economical automated burr removal for minor quantities or high variant diversity in the future foundry. All the methods shown are of great importance for introducing printed core packages into series production. [ABSTRACT FROM AUTHOR]

New and interesting uses for portable devices include the creation and viewing of 3D models and 360-degree photos of real landscapes. To provide a 3D model and a 360-degree view of a scenario, these apps search for real-time rendering and presentation. This study examines the impact of real-time image processing on movements in camera view and the application of optical flow algorithms. The optical flows are affected by how the objects involved motion. The way the image is recorded and the camera movements affect the relative motion. As a consequence, camera motions are responsive to optical flow algorithms. To record an image, the camera may pan around, move in a straight path, or move randomly. We have captured datasets of videos produced in different contexts to better replicate real-world scenarios. Each dataset was captured in a variety of illumination situations, camera movements, and indoor and outdoor recording sites. Here, to determine the most effective optical flow algorithms for use in near real-time applications, such as augmented reality and virtual reality, we compare results based on quality and processing delay for each video frame. We conducted a comparison study to better understand how random camera motion affects real-time video processing. These methods can be used to handle a variety of real-world issues, such as object tracking, video segmentation, structure from motion, gesture tracking, and so on. [ABSTRACT FROM AUTHOR]

Background: Analysis of surgical instrument motion is applicable in surgical skill assessment and monitoring of the learning progress in laparoscopy. Current commercial instrument tracking technology (optical or electromagnetic) has specific limitations and is expensive. Therefore, in this study, we apply inexpensive, off-the-shelf inertial sensors to track laparoscopic instruments in a training scenario. Methods: We calibrated two laparoscopic instruments to the inertial sensor and investigated its accuracy on a 3D-printed phantom. In a user study during a one-week laparoscopy training course with medical students and physicians, we then documented and compared the training effect in laparoscopic tasks on a commercially available laparoscopy trainer (Laparo Analytic, Laparo Medical Simulators, Wilcza, Poland) and the newly developed tracking setup. Results: Eighteen participants (twelve medical students and six physicians) participated in the study. The student subgroup showed significantly poorer results for the count of swings (CS) and count of rotations (CR) at the beginning of the training compared to the physician subgroup (p = 0.012 and p = 0.042). After training, the student subgroup showed significant improvements in the rotatory angle sum, CS, and CR (p = 0.025, p = 0.004 and p = 0.024). After training, there were no significant differences between medical students and physicians. There was a strong correlation between the measured learning success (LS) from the data of our inertial measurement unit system (LSIMU) and the Laparo Analytic (LSLap) (Pearson's r = 0.79). Conclusion: In the current study, we observed a good and valid performance of inertial measurement units as a possible tool for instrument tracking and surgical skill assessment. Moreover, we conclude that the sensor can meaningfully examine the learning progress of medical students in an ex-vivo setting. [ABSTRACT FROM AUTHOR]

This study presents the validation of a multi-camera videogrammetry approach for measuring football helmet impact velocities, wherein the effect of camera angle, camera distance and impact speed were assessed. Helmet-to-ground impacts were simulated within two zones on a field using free fall drop tests of a helmeted head and neck assembly at heights of 1.04 m (slow: 4.52 m/s) and 1.83 m (fast: 5.99 m/s). Helmet motion was manually tracked using 3D motion analysis software for different camera combinations (e.g., orthogonal, coincident, overhead, and parallel camera pairs) in each zone. Maximum errors of the 3D calibrations were < 3 cm; mean maximum uncertainty (±) error for 3D tracking was ≤ 2.4 cm across all test conditions, except parallel angles (4.3–10.0 cm). Helmet impact velocities from orthogonal, coincident and overhead angles compared favorably to the reference velocities (slow: 4.50 ± 0.05 m/s; fast: 6.09 ± 0.06 m/s) with relatively low errors overall (relative error (RE), absolute error (AE): ≤ 3.39%; root-mean-square error (RMSE): ≤ 0.22 m/s). Parallel angles had the highest errors (RE, AE: 3.79–10.94%; RMSE: 0.18–0.55 m/s) due to inaccuracies with horizontal measurements in-line with the camera views. In general, increases in camera distance and impact speed did not appreciably influence video tracking accuracy. [ABSTRACT FROM AUTHOR]

Background/purpose: Pubic ramus fractures account for the most common types of pelvic fractures. The standard surgical approach for superior pubic ramus fractures (SPRF) is a minimally invasive percutaneous screw fixation. However, percutaneous closed reduction and internal fixation of anterior pelvic ring injuries have high failure rates of up to 15%. The aim of this biomechanical study was to evaluate the stability of SPRF following stabilization with retrograde placed cannulated compression headless screw (CCHS) versus conventional fully and partially threaded screws in an artificial pelvic bone model. Methods: SPRF type II as described by Nakatani et al. was created by means of osteotomies in eighteen anatomical composite hemi-pelvises. Specimens were stratified into three groups of six specimens each (n = 6) for fixation with either a 7.3 mm partially threaded cannulated screw (group RST), a 7.3 mm fully threaded cannulated screw (group RSV), or a 7.5 mm partially threaded cannulated CCHS (group CCS). Each hemi-pelvic specimen was tested in an inverted upright standing position under progressively increasing cyclic axial loading. The peak load, starting at 200 N, was monotonically increased at a rate of 0.1 N/cycle until 10 mm actuator displacement. Results: Total and torsional displacement were associated with higher values for RST versus CCS and RSV, with significant differences between RST and CCS for both these parameters (p ≤ 0.033). The differences between RST and RSV were significant for total displacement (p = 0.020), and a trend toward significance for torsional displacement (p = 0.061) was observed. For both failure criteria 2 mm total displacement and 5° torsional displacement, CCS was associated with significantly higher number of cycles compared to RST (p ≤ 0.040). Conclusion: CCHS fixation presented predominantly superior stability to the standard surgical treatment and could therefore be a possible alternative implant for retrograde SPRF screw fixation, whereas partially threaded screws in group RST were associated with inferior biomechanical stability. [ABSTRACT FROM AUTHOR]

Purpose: Autostereoscopic 3D visualization (ASV) forms a potentially appealing alternative to stereoscopic 3D displays to help surgeons regain depth perception during minimally invasive surgery (MIS). However, the feasibility of using single-viewer ASV has not yet been demonstrated in a clinical context. The purpose of the study is to analyze the current surgical workflow and display usage and assess the potential for using ASV in MIS applications. Additionally, the study seeks to acquire a better understanding of key design requirements, such as the eye-tracking performance and the lenticular lens 3D workspace. Methods: Two types of gynecologic interventions were investigated. A vision-based tracking system was developed, consisting of depth cameras mounted on the displays and ArUco markers placed on the hair caps of clinicians and the wall of the operating room. This allowed simultaneous tracking of the pose of operating staff and displays. Results: Overall 20 surgeries were recorded, where 4 clinicians operated using 3 displays. Users were typically standing at a mean distance of 1900 mm in a range from to 1200 to 2300 mm from the display. Left–right motion was from − 600 to 658 mm. Clinicians stood on average 1000 mm from each other. The head roll angle was below 16 ∘ . Conclusion: Surgeons were looking predominantly (99%) to the same display. Observations took place from fairly well-defined places and with sufficient potential to differentiate between clinicians, suggesting that single-viewer ASV would be feasible. [ABSTRACT FROM AUTHOR]

Introduction: Surgical skill assessment utilises direct observation and feedback by an expert which is potentially subjective, therefore obtaining objective data for hand and eye tracking is essential. Our aim was to evaluate a wearable mixed reality (MR) headset in these domains. Methods: Participants with differing levels of surgical expertise [novice (N), intermediate (I) & expert (E)] performed 4 simulated surgical tasks; 2 general dexterity (tasks 1&2) and 2 surgical skills (tasks 3&4) wearing the MR headset capturing their hand and eye movements (median & range). Metrics included hand path length and the speed of each index or thumb tip. Gaze data were also captured. Participant demographics, prior expertise and current experience were captured with an electronic survey. Data were analysed with a Shapiro-Wilk test or ANOVA as appropriate. A p-value of < 0.05 was significant. Results: Thirty-six participants were analysed (N = 18, I = 8, E = 8). Tasks 1&2 revealed 2 speed outcomes (left index and left-hand speed) which were significant. For tasks 3&4, various outcomes were significant: path length for left hand (N:45 cm vs. I:31 cm vs. E:27 cm, p = 0.03) and right hand (N:48 cm vs. I:29 cm vs. E:28 cm, p = 0.01) and total time (N:456s vs. I:292 vs. E: 245, p = 0.0002). With left-hand-tying, average path length (N:61 cm vs. I:39 vs. E:36, p = 0.04), average speed (N:11 cm/s vs. I:23 vs. E:24, p = 0.03), and total time (N:156s vs. I:43 vs. E:37, p = 0.003) were significant. The gaze-tracking was not statistically significant. Conclusion: The MR headset can be utilised as a valid tool for surgical performance assessment. Outcomes including path length and speed can be valuable metrics captured by the MR Headset during the task completion for detecting surgical proficiency. [ABSTRACT FROM AUTHOR]

In everyday life, sound localization entails more than just the extraction and processing of auditory cues. When determining sound position in three dimensions, the brain also considers the available visual information (e.g., visual cues to sound position) and resolves perceptual ambiguities through active listening behavior (e.g., spontaneous head movements while listening). Here, we examined to what extent spontaneous head movements improve sound localization in 3D—azimuth, elevation, and depth—by comparing static vs. active listening postures. To this aim, we developed a novel approach to sound localization based on sounds delivered in the environment, brought into alignment thanks to a VR system. Our system proved effective for the delivery of sounds at predetermined and repeatable positions in 3D space, without imposing a physically constrained posture, and with minimal training. In addition, it allowed measuring participant behavior (hand, head and eye position) in real time. We report that active listening improved 3D sound localization, primarily by ameliorating accuracy and variability of responses in azimuth and elevation. The more participants made spontaneous head movements, the better was their 3D sound localization performance. Thus, we provide proof of concept of a novel approach to the study of spatial hearing, with potentials for clinical and industrial applications. [ABSTRACT FROM AUTHOR]

In this study, resistive-type stretch sensors based on embroidered conductive threads were investigated to determine the best combinations of various conductive threads and fabrics, as well as the ideal embroidery patterns and their optimal geometric parameters. Among various conductive threads, a silver-plated nylon fiber of 280 denier was selected as the best conductive thread, because it featured the highest gauge factor and excellent stretchability and reliability. Among the various tested fabrics, the poly fine brushed knit fabric could endure high repetitive stretching without any permanent deformation, thus guaranteeing an apparent electrical resistance-strain curve. Zigzag, couching, overcasting, and decorative patterns were embroidered on this poly fine brushed knit fabric using the 280 denier silver-plated nylon fiber. The electrical resistance curves of the embroidered conductive threads were measured as functions of the applied strain and frequency. The zigzag pattern exhibited the best resistancestrain response and the highest gauge factor. The electrical resistance-strain curve was also measured through a cyclic loading test involving 100000 cycles. Results indicated that the hysteresis behavior and drift in electrical resistance may have hindered accurate measurements of the strain during the stretching and releasing process, which needs to be corrected by using a compensation algorithm. To demonstrate the proposed stretch sensor, knee motions were monitored using a resistive-type stretch sensor implemented on athletic cloth. [ABSTRACT FROM AUTHOR]

Commonly available digital image correlation (DIC) tools are designed to evaluate displacement/deformation fields using well-optimized correlation functions and computational procedures. However, real-time monitoring at high sampling rates or tracking motion at predefined locations from large sequence images can be hardly accomplished due to extreme computational costs. As shown in this paper, a lightweight approach based on the registration of subpixel subset shifts using discrete Fourier transform (DFT) can easily tackle large sets of images if the measurement is limited to discrete locations. A simple open-source python software designed for evaluation of displacements using virtual extensometers is described in this paper, along with the analysis of its performance. It is shown that the DFT-based algorithms outperform a commonly used DIC package in terms of computational efficiency and required user interactions, without sacrificing precision and accuracy. [ABSTRACT FROM AUTHOR]

Purpose: Posterior spinal fusion surgery is required to correct severe idiopathic scoliosis. The surgery involves insertion of screws which requires high accuracy to prevent neurologic damage to the spinal cord. Although conventional CT navigation can reduce this risk, 3D-ultrasound-based navigation could achieve this without added ionizing radiation and usage of expensive and bulky equipment. This study aimed to evaluate the accuracy of a 3D ultrasound navigation system for posterior spine surgery. Methods: A custom 3D ultrasound (3DUS) with model-to-surface registration algorithm was developed and integrated into a 3D navigation environment. A CT scan of an adolescent spine (T3-T11) was segmented and 3D printed for experiments. A probe with reflective markers was placed in vertebral pedicles 684 times in varying levels, positions in the capture space and orientation of vertebra, and the entrypoint and trajectory accuracies were measured. Results: Among 684 probe placements in vertebral levels T3 to T11 in the phantom spine, 95.5% were within 1 mm and 5° of accuracy, with an average accuracy of 0.4 ± 0.4 mm and 2.1 ± 0.9°, requiring 8.8 s to process. Accuracies were statistically significantly affected by vertebral orientation and position in the capture volume, though this was still within the targeted accuracies of 1 mm and 5°. Conclusion: This preliminary ultrasound-based navigation system is accurate and fast enough for guiding placement of pedicle screws into the spine in posterior fusion surgery. The current results are limited to phantom spines, and future study in animal or human cadavers is needed to investigate soft tissue effects on registration accuracy. [ABSTRACT FROM AUTHOR]

This paper describes an educational experience realized in the form of extracurricular workshops involving music technology students of the "V. Gambara" music high school in Brescia (Italy). By means of a participatory prototyping experience, the project aimed at fostering the students awareness and understanding of technological means and their utility. The Discovery of Interactive Spaces project focuses on motion tracking technologies in connection with sound and visual production, as means to provoke reflections on their cultural and societal impact on social utility and inclusion, and artistic expression. To this end, students proposed design concepts, and prototyped sonic interactive experiences. The Discovery of Interactive Spaces is framed within the broader themes of computational thinking and creativity, learning by design, and technology awareness. These themes represent the pillars of technological citizenship, which is considered crucial for the twenty-first century student. [ABSTRACT FROM AUTHOR]

Patients after surgical repair of Tetralogy of Fallot (rTOF) may suffer a decrease in left ventricular (LV) function. The aim of our study is to evaluate a novel method of assessing LV torsion in patients with rTOF, as an early indicator of systolic LV dysfunction. Motion tracking based on image registration regularized by the equilibrium gap principle, known as equilibrated warping, was employed to assess LV torsion. Seventy-six cases of rTOF and ten normal controls were included. The group of controls was assessed for reproducibility using both equilibrated warping and standard clinical tissue tracking software (CVI42, version 5.10.1, Calgary, Canada). Patients were dichotomized into two groups: normal vs. loss of torsion. Torsion by equilibrated warping was successfully obtained in 68 of 76 (89%) patients and 9 of 10 (90%) controls. For equilibrated warping, the intra- and interobserver coefficients of variation were 0.095 and 0.117, respectively, compared to 0.260 and 0.831 for tissue tracking by standard clinical software. The intra- and inter-observer intraclass correlation coefficients for equilibrated warping were 0.862 and 0.831, respectively, compared to 0.992 and 0.648 for tissue tracking. Loss of torsion was noted in 32 of the 68 (47%) patients with rTOF. There was no difference in LV or RV volumes or ejection fraction between these groups. The assessment of LV torsion by equilibrated warping is feasible and shows good reliability. Loss of torsion is common in patients with rTOF and its robust assessment might contribute into uncovering heart failure in an earlier stage. [ABSTRACT FROM AUTHOR]

Purpose: Respiratory motion of thoracic organs poses a severe challenge for the administration of image-guided radiotherapy treatments. Providing online and up-to-date volumetric information during free breathing can improve target tracking, ultimately increasing treatment efficiency and reducing toxicity to surrounding healthy tissue. In this work, a novel population-based generative network is proposed to address the problem of 3D target location prediction from 2D image-based surrogates during radiotherapy, thus enabling out-of-plane tracking of treatment targets using images acquired in real time. Methods: The proposed model is trained to simultaneously create a low-dimensional manifold representation of 3D non-rigid deformations and to predict, ahead of time, the motion of the treatment target. The predictive capabilities of the model allow correcting target location errors that can arise due to system latency, using only a baseline volume of the patient anatomy. Importantly, the method does not require supervised information such as ground-truth registration fields, organ segmentation, or anatomical landmarks. Results: The proposed architecture was evaluated on both free-breathing 4D MRI and ultrasound datasets. Potential challenges present in a realistic therapy, like different acquisition protocols, were taken into account by using an independent hold-out test set. Our approach enables 3D target tracking from single-view slices with a mean landmark error of 1.8 mm, 2.4 mm and 5.2 mm in volunteer MRI, patient MRI and US datasets, respectively, without requiring any prior subject-specific 4D acquisition. Conclusions: This model presents several advantages over state-of-the-art approaches. Namely, it benefits from an explainable latent space with explicit respiratory phase discrimination. Thanks to the strong generalization capabilities of neural networks, it does not require establishing inter-subject correspondences. Once trained, it can be quickly deployed with an inference time of only 8 ms. The results show the capability of the network to predict future anatomical changes and track tumors in real time, yielding statistically significant improvements over related methods. [ABSTRACT FROM AUTHOR]

Common social behaviors, such as having a conversation, dancing, or playing a team sport, require precise interpersonal coordination of action. One question that emerges in research on interpersonal coordination is to what extent individuals implicitly mimic the spatial characteristics of movements for tasks that emphasize movement timing. To investigate this question, we conducted two experiments using an interpersonal synchronization-continuation tapping paradigm in which pairs of individuals tapped with their index finger on a table in synchrony with an auditory metronome and then continued tapping at the same tempo when the metronome stopped. Pairs of individuals tapped either together with the instruction to maintain synchrony with each other (interpersonal tapping) or tapped alone (solo tapping). Solo tapping conditions either occurred with their tapping partner present in the testing room (Experiment 1) or absent (Experiment 2). We used motion capture to examine both the spatial and temporal aspects of movement dynamics during task performance. In both experiments, participants implicitly mimicked subtle aspects of spatial elements of their partner's movements. The extent of finger extension (tap amplitude) and, in Experiment 1, duration of finger contact with the surface (dwell time) were correlated between tapping partners when they tapped together. In some cases, this spatial mimicry extended to solo tapping conditions, but only during solo tapping conditions that followed the interpersonal tapping task, and, to a lesser degree, when solo tapping after having observed the other participant solo tapping. [ABSTRACT FROM AUTHOR]

In human face-to-face communication, speech is frequently accompanied by visual signals, especially communicative hand gestures. Analyzing these visual signals requires detailed manual annotation of video data, which is often a labor-intensive and time-consuming process. To facilitate this process, we here present SPUDNIG (SPeeding Up the Detection of Non-iconic and Iconic Gestures), a tool to automatize the detection and annotation of hand movements in video data. We provide a detailed description of how SPUDNIG detects hand movement initiation and termination, as well as open-source code and a short tutorial on an easy-to-use graphical user interface (GUI) of our tool. We then provide a proof-of-principle and validation of our method by comparing SPUDNIG's output to manual annotations of gestures by a human coder. While the tool does not entirely eliminate the need of a human coder (e.g., for false positives detection), our results demonstrate that SPUDNIG can detect both iconic and non-iconic gestures with very high accuracy, and could successfully detect all iconic gestures in our validation dataset. Importantly, SPUDNIG's output can directly be imported into commonly used annotation tools such as ELAN and ANVIL. We therefore believe that SPUDNIG will be highly relevant for researchers studying multimodal communication due to its annotations significantly accelerating the analysis of large video corpora. [ABSTRACT FROM AUTHOR]

We presents a novel method to improve the accuracy of 3D motion tacking. In contrast to the state-of-the-art tracking approaches, where the 3D structure of target is commonly approximated by a CAD model, the proposed method establishes the target model by an online improved Structure-from-Motion technique. Furthermore, the tracking is implemented by three sequential trackers (feature-based tracker, image-alignment-based tracker and Particle Filter), which continually refine the tracking results. This coarse-to-fine method increases the accuracy of tracking. Moreover, our approach uses keyframe strategy to prevent tracking drift, the new keyframe insertion is determined by a criterion which can ensure a correct update. Thorough evaluations are performed on two public databases, the Biwi Head Pose dataset and the UPNA Head Pose Database. Comparisons illustrate that the proposed method achieves better performance with respect to other state-of-the-art tracking approaches. [ABSTRACT FROM AUTHOR]

Hand gestures are a natural and intuitive form for human-environment interaction and can be used as an input alternative in human-computer interaction (HCI) to enhance usability and naturalness. Many existing approaches have employed vision -based systems to detect and recognize hand gestures. However, vision-based systems usually require users to move their hands within restricted space, where the optical device can capture the motion of hands. Also, vision-based systems may suffer from self-occlusion issues due to sophisticated finger movements. In this work, we use a sensor-based motion tracking system to capture 3D hand and finger motions. To detect and recognize hand gestures, we propose a novel angular-velocity method, which is directly applied to real-time 3D motion data streamed by the sensor-based system. Our approach is capable of recognizing both static and dynamic gestures in real-time. We assess the recognition accuracy and execution performance with two interactive applications that require gesture input to interact with the virtual environment. Our experimental results show high recognition accuracy, high execution performance, and high-levels of usability. [ABSTRACT FROM AUTHOR]

There is increasing evidence that hand gestures and speech synchronize their activity on multiple dimensions and timescales. For example, gesture's kinematic peaks (e.g., maximum speed) are coupled with prosodic markers in speech. Such coupling operates on very short timescales at the level of syllables (200 ms), and therefore requires high-resolution measurement of gesture kinematics and speech acoustics. High-resolution speech analysis is common for gesture studies, given that field's classic ties with (psycho)linguistics. However, the field has lagged behind in the objective study of gesture kinematics (e.g., as compared to research on instrumental action). Often kinematic peaks in gesture are measured by eye, where a "moment of maximum effort" is determined by several raters. In the present article, we provide a tutorial on more efficient methods to quantify the temporal properties of gesture kinematics, in which we focus on common challenges and possible solutions that come with the complexities of studying multimodal language. We further introduce and compare, using an actual gesture dataset (392 gesture events), the performance of two video-based motion-tracking methods (deep learning vs. pixel change) against a high-performance wired motion-tracking system (Polhemus Liberty). We show that the videography methods perform well in the temporal estimation of kinematic peaks, and thus provide a cheap alternative to expensive motion-tracking systems. We hope that the present article incites gesture researchers to embark on the widespread objective study of gesture kinematics and their relation to speech. [ABSTRACT FROM AUTHOR]

Motion tracking software for assessing laparoscopic surgical proficiency has been proven to be effective in differentiating between expert and novice performances. However, with several indices that can be generated from the software, there is no set threshold that can be used to benchmark performances. The aim of this study was to identify the best possible algorithm that can be used to benchmark expert, intermediate and novice performances for objective evaluation of psychomotor skills. 12 video recordings of various surgeons were collected in a blinded fashion. Data from our previous study of 6 experts and 23 novices was also included in the analysis to determine thresholds for performance. Video recording were analyzed both by the Kinovea 0.8.15 software and a blinded expert observer using the CAT form. Multiple algorithms were tested to accurately identify expert and novice performances. ½ L + 1 3 A + 1 6 J scoring of path length, average movement and jerk index respectively resulted in identifying 23/24 performances. Comparing the algorithm to CAT assessment yielded in a linear regression coefficient R2 of 0.844. The value of motion tracking software in providing objective clinical evaluation and retrospective analysis is evident. Given the prospective use of this tool the algorithm developed in this study proves to be effective in benchmarking performances for psychomotor skills evaluation. [ABSTRACT FROM AUTHOR]

Accurate tracking of organ motion during treatment is needed to improve the efficacy of radiation therapy. This work investigates the feasibility of tracking an uncontoured target using the motion detected within a moving treatment aperture. Tracking was achieved with a weighted optical flow algorithm, and three different techniques for updating the reference image were evaluated. The accuracy and susceptibility of each approach to the accumulation of position errors were verified using a 3D-printed tumor (mounted on an actuator) and a virtual treatment aperture. Tumor motion up to 15.8 mm (peak-to-peak) taken from the breathing patterns of seven lung cancer patients was acquired using an amorphous silicon portal imager at ~ 7.5 frames/s. The first approach (INI) used the initial image detected, as a fixed reference, to determine the target motion for each new incoming image, and performed the best with the smallest errors. This method was also the most robust against the accumulation of position errors. Mean absolute errors of 0.16, 0.32, and 0.38 mm were obtained for the three methods, respectively. Although the errors are comparable to other tracking methods, the proposed method does not require prior knowledge of the tumor shape and does not need a tumor template or contour for tracking. Graphical abstract. [ABSTRACT FROM AUTHOR]

Action, gesture, and sign represent unique aspects of human communication that use form and movement to convey meaning. Researchers typically use manual coding of video data to characterize naturalistic, meaningful movements at various levels of description, but the availability of markerless motion-tracking technology allows for quantification of the kinematic features of gestures or any meaningful human movement. We present a novel protocol for extracting a set of kinematic features from movements recorded with Microsoft Kinect. Our protocol captures spatial and temporal features, such as height, velocity, submovements/strokes, and holds. This approach is based on studies of communicative actions and gestures and attempts to capture features that are consistently implicated as important kinematic aspects of communication. We provide open-source code for the protocol, a description of how the features are calculated, a validation of these features as quantified by our protocol versus manual coders, and a discussion of how the protocol can be applied. The protocol effectively quantifies kinematic features that are important in the production (e.g., characterizing different contexts) as well as the comprehension (e.g., used by addressees to understand intent and semantics) of manual acts. The protocol can also be integrated with qualitative analysis, allowing fast and objective demarcation of movement units, providing accurate coding even of complex movements. This can be useful to clinicians, as well as to researchers studying multimodal communication or human–robot interactions. By making this protocol available, we hope to provide a tool that can be applied to understanding meaningful movement characteristics in human communication. [ABSTRACT FROM AUTHOR]

Zebrafish (Danio rerio) is a powerful animal model used in many areas of genetics and disease research. Despite its advantages for cardiac research, the heartbeat pattern of zebrafish larvae under different stress conditions is not well documented quantitatively. Several effective automated heartbeat detection methods have been developed to reduce the workload for larva heartbeat analysis. However, most require complex experimental setups and necessitate direct observation of the larva heart. In this paper, we propose the Zebrafish Heart Rate Automatic Method (Z-HRAM), which detects and tracks the heartbeats of immobilized, ventrally positioned zebrafish larvae without direct larva heart observation. Z-HRAM tracks localized larva body deformation that is highly correlated with heart movement. Multiresolution dense optical flow-based motion tracking and principal component analysis are used to identify heartbeats. Here, we present results of Z-HRAM on estimating heart rate from video recordings of seizure-induced larvae, which were of low resolution (1024 × 760) and low frame rate (3 to 4 fps). Heartbeats detected from Z-HRAM were shown to correlate reliably with those determined through corresponding electrocardiogram and manual video inspection. We conclude that Z-HRAM is a robust, computationally efficient, and easily applicable tool for studying larva cardiac function in general laboratory conditions. Graphical abstract Flowchart of the automatic zebrafish heartbeat detection. [ABSTRACT FROM AUTHOR]

Camera-based monitoring systems have a wide range of applications in traffic management, since they can collect more informative data in contrast to other sensors. An increasing number of traffic camera systems collect a large volume of traffic video data daily, forming the Big Data of traffic video. One of the challenges for traffic video processing is their high cost of resources and time, which seriously block the development of intelligent transportation systems. This paper proposes a spectrum analysis method for traffic video synopsis, including motion detection and tracking. Our method can largely remove the background noises and correctly extract motion information. Spatial and temporal spectrum analysis (Fourier transformation) are jointly used to detect objects and their motions in traffic videos. Further, the detected motions are tracked by the particle filter, generating trajectories of motions. Motion detection and tracking results given by our method can provide a synopsis for Big Data of traffic videos. The outperformance of our method is demonstrated comparing to the state of art video analysis methods. [ABSTRACT FROM AUTHOR]

Background: The use of motion tracking has been proved to provide an objective assessment in surgical skills training. Current systems, however, require the use of additional equipment or specialised laparoscopic instruments and cameras to extract the data. The aim of this study was to determine the possibility of using a software-based solution to extract the data.Methods: 6 expert and 23 novice participants performed a basic laparoscopic cholecystectomy procedure in the operating room. The recorded videos were analysed using Kinovea 0.8.15 and the following parameters calculated the path length, average instrument movement and number of sudden or extreme movements.Results: The analysed data showed that experts had significantly shorter path length (median 127 cm vs. 187 cm, p = 0.01), smaller average movements (median 0.40 cm vs. 0.32 cm, p = 0.002) and fewer sudden movements (median 14.00 vs. 21.61, p = 0.001) than their novice counterparts.Conclusion: The use of software-based video motion tracking of laparoscopic cholecystectomy is a simple and viable method enabling objective assessment of surgical performance. It provides clear discrimination between expert and novice performance. [ABSTRACT FROM AUTHOR]

Locomotion of insects is exceptionally efficient and this efficiency is partially due to the kinematics within leg joints, which in different movement scenarios depends on their inner contacting conditions. The investigation of functionality of the leg joints can potentially provide new innovative problem solutions in robotics. The previously published information about the shape of the joints is not sufficient, because without knowledge about the movements of the articulating surfaces within the joint, the kinematics cannot be understood. To understand the joint movements, we have performed motion tracking experiments in the beetle Pachnoda marginata (Scarabaeidae, Cetoniinae) in different locomotory scenarios. We aimed at understanding the range of motion within single leg joints depending on their function in the entire leg movement scenario. For this purpose, we combined the motion analysis of living beetles with the results of the simulation of a multi-body system. The results of the multi-body simulation allowed the kinematic characterization of articulating joints by their degrees of freedom and the identification of the rotation axes. The simulated range of motion predicted by the limitations of the exoskeleton of the joints partially matched those obtained from the motion analysis of the living beetle. We showed that the range of motion of the single leg joints depends strongly on the type of the beetle locomotory scenario. It is also concluded that the simulation of multi-body systems is a powerful tool for the kinematic analysis of insect tribological systems. [ABSTRACT FROM AUTHOR]

This paper develops and experimentally validates a 3D-printed snake robot prototype. Its structure is designed to allocate limited room for each functional module (including an external power module, battery power module, the wireless control and transmission module and some detective sensors), so as to ensure the snake robot works in different environments. In order to control and track the snake robot, a low-cost MEMS-IMU (micro-electro-mechanical systems inertial measurement unit)-based snake robot motion tracking system is developed. Three algorithms (low-pass filter, baseline calibration, and Kalman filter) are used to eliminate noise from IMU's acceleration data, thus minimizing the noise influence to tracking accuracy. Through signal processing, the IMU acceleration data can be effectively used for motion tracking. The result from the video tracking software is employed as a reference for comparison, so as to evaluate the motion tracking algorithm efficiency. The comparison results demonstrate high efficiency of the proposed IMU-based motion tracking algorithm. [ABSTRACT FROM AUTHOR]

The purpose of this work is to present and validate a novel approach for ultra-sound-based speckle tracking to measure the carotid artery longitudinal displacement, and to assess the apparent sliding between of Intima-Media Complex (IMC) and Adventitia (Ad) layers. This method utilizes feature detectors and descriptors to localize and track keypoints for local motion quantification. The procedure was tested and validated on an in silico dataset and on 18 heathy volunteers and 16 patients. Accuracy measured on in silico data gave a mean ± standard deviation of 23 ± 15 and 19 ± 18 μm for IMC and Ad respectively, and thus smaller than the pixel size (0.0925 mm). Robustness analysis was performed on in vivo images, obtaining a maximum variation coefficient, over 5 repeated measures, of 9.5 and 13.8% for IMC and Ad, respectively. The novel method capability for detecting the relative motion of IMC vs. Ad was compared with visual assessment performed by 2 physicians, leading to a correlation coefficient R of 0.7 in the worst case. (Healthy group scored by rater #1.) In conclusion, our results provide evidence that the novel method is able to accurately and reliably track carotid artery layer motion and that it overcomes limitations currently present in the literature, therefore providing an automatic tool for clinical evaluation of IMC vs. Ad relative displacement. [ABSTRACT FROM AUTHOR]

We are living in the middle of media era's turning point. Old media may change largely. Recently the growth of Tablet PC and Smartphone has brought the digital media, New media, expand. Companies are likely to use the Augmented reality applied marketing, based on mobile display. This research proposes augmented reality based techniques to enhance promotional videos for cultural arts organizations. Specifically, it aims to propose editing techniques based on augmented reality and the Popcode mobile application. Currently, Popcode is not widely utilized; however, it has potential value for promotional videos by working in concert with augmented reality systems. To achieve this goal, we enhanced Popcode's features and capabilities, applied them to promotional videos, and concluded that these techniques would create a synergistic effect for marketing campaigns. Based on related Popcode research conducted by the University of Cambridge, we implemented Popcode technology into a video, focusing on a motion tracking technique that incorporates the Adobe After Effects program. Augmented reality and Popcode aren't just a technology. Now we are going to find out the meaning of augmented reality as a means of media. As well as analyze the interactive effect as a role of advertising. [ABSTRACT FROM AUTHOR]

The aim of this study was to compare the computational performances of two direct methods for solving large-scale, nonlinear, optimal control problems in human movement. Direct shooting and direct collocation were implemented on an 8-segment, 48-muscle model of the body (24 muscles on each side) to compute the optimal control solution for maximum-height jumping. Both algorithms were executed on a freely-available musculoskeletal modeling platform called OpenSim. Direct collocation converged to essentially the same optimal solution up to 249 times faster than direct shooting when the same initial guess was assumed (3.4 h of CPU time for direct collocation vs. 35.3 days for direct shooting). The model predictions were in good agreement with the time histories of joint angles, ground reaction forces and muscle activation patterns measured for subjects jumping to their maximum achievable heights. Both methods converged to essentially the same solution when started from the same initial guess, but computation time was sensitive to the initial guess assumed. Direct collocation demonstrates exceptional computational performance and is well suited to performing predictive simulations of movement using large-scale musculoskeletal models. [ABSTRACT FROM AUTHOR]

Since the advent of electromyogram recording, precise measures of tremor and gait have been used to study movement disorders such as Parkinson's disease. Now, a wide range of accelerometers and other motion-tracking technologies exist to better inform researchers and clinicians, yet such systems are rarely tested for accuracy or suitability before use. Our inexpensive test-rig can produce sinusoidal displacements using a simple cantilever system driven by a subwoofer. Controlled sinusoids were generated using computer software, and the displacement amplitudes of the test-rig were verified with fiducial marker tracking. To illustrate the use of the test-rig, we evaluated an accelerometer and an electromagnetic motion tracker. Accelerometry recordings were accurate to within ±0.09 g of actual peak-to-peak amplitude with a frequency response close to unity gain between 1 and 20 Hz. The electromagnetic sensor underestimated peak displacement by 2.68 mm, which was largely due to a diminishing gain with increasing frequency. Both sensors had low distortion. Overall sensitivity was limited by noise for the accelerometer and quantisation resolution for the electromagnetic sensor. Our simple and low-cost test-rig can be used to bench-test sensors used in movement disorders research. It was able to produce reliable sinusoidal displacements and worked across the 1- to 20-Hz frequency range. [ABSTRACT FROM AUTHOR]

Identification of oblique lines of a particular slope is needed for various applications such as motion tracking for smart cameras. Wavelets and gradient-based techniques, such as Sobel and Canny, do not classify edges based on their slopes. The Hough transform (HT) does classify edges based on their slopes but with high computational complexity, even using its most improved versions. This paper presents a computationally efficient technique for detecting edges of a particular slope. The angle of the required edges is converted into pixel increments over rows and columns. Using these two simple parameters, parallel, oblique lines of a particular slope are formed. A first-order, orthonormal Haar low-pass filter (LPF) is used over the formed lines to filter out undesired edges. The hardware architecture of the proposed technique is fully described, including processing time, based on the number of clock cycles, and fixed-point implementation. A line-based memory mechanism was used to minimize the memory requirements to two simple registers. To demonstrate the computational advantage of the proposed technique, it is compared to the Sobel, Canny and HT detectors. [ABSTRACT FROM AUTHOR]

Shake table testing is a viable validation tool for bench-marking the analytically computed seismic response of under-water structural models with fluid-structure interaction effects. Conventional displacement sensors like LVDTs (linearly variable differential transformer) cannot be used for under-water response measurements as they require a stationary platform near the measurement point as a reference. This rather limiting application of LVDTs in several situations warrants the use of high speed camera as a potential measurement tool. This article presents the vision based displacement measurement of an under-water model tested on a shake table. High speed video camera is used to record the motion during shaking. The video images are processed using a special motion tracking algorithm and displacements are measured. The sloshing effect of water on the test model and their free vibration at the end of the shaking are studied to calculate natural frequency and damping. Vital information on the allowable under-water motion of the test model is obtained and discussed. [ABSTRACT FROM AUTHOR]

In this paper, we present a parallel 4D vessel reconstruction algorithm that simultaneously recovers 3D structure, shape, and motion based on multiple views of X-ray angiograms. The fundamental goal is to assist the analysis and diagnosis of interventional surgery in the most efficient way towards interactive and accurate performance. We start with a fully parallelized algorithm to extract vessels as well as their skeletons and topologies from dynamic image sequences. Then, instead of resorting to registration, we present an algorithm to formulate the reconstruction problem as an energy minimization problem with color, coherence, and topology constraints to reconstruct the 3D vessel initially, which is robust to combat noise and incomplete information in images. Next, we incorporate temporal information into our energy optimization framework to track and reconstruct 4D kinematics of the dynamic vessels, which is also capable of recovering previous incomplete and misleading shapes acquired from static images otherwise. We demonstrate our system in coronary arteries reconstruction and movement tracking for percutaneous coronary intervention surgery to help medical practitioners learn about the 3D shapes and their motions of the coronary arteries of specific patient. We envision that our system would be of high assistance for diagnosis and therapy to treat vessel-related diseases in a clinical setting in the near future. [ABSTRACT FROM AUTHOR]

We describe WeaVR, a computer simulation system that takes virtual reality technology beyond specialized laboratories and research sites and makes it available in any open space, such as a gymnasium or a public park. Novel hardware and software systems enable HMD-based immersive virtual reality simulations to be conducted in any arbitrary location, with no external infrastructure and little-to-no setup or site preparation. The ability of the WeaVR system to provide realistic motion-tracked navigation for users, to improve the study of large-scale navigation, and to generate usable behavioral data is shown in three demonstrations. First, participants navigated through a full-scale virtual grocery store while physically situated in an open grass field. Trajectory data are presented for both normal tracking and for tracking during the use of redirected walking that constrained users to a predefined area. Second, users followed a straight path within a virtual world for distances of up to 2 km while walking naturally and being redirected to stay within the field, demonstrating the ability of the system to study large-scale navigation by simulating virtual worlds that are potentially unlimited in extent. Finally, the portability and pedagogical implications of this system were demonstrated by taking it to a regional high school for live use by a computer science class on their own school campus. [ABSTRACT FROM AUTHOR]