Motion Tracking Research Articles

Enhancing Radar Image Classification with Autoencoder-CNN Hybrid System

The tracking, analysis, and classification of human movements can be crucial, particularly in areas such as elderly care, healthcare, and infant care. Typically, such tracking is done remotely with cameras. However, radar systems have emerged as significant methods and tools for these tasks due to their advantages such as privacy, wireless operation, and the ability to work through walls. By converting reflected radar signals from targets into images, human activities can be classified using powerful classification tools like deep learning. In this study, range-Doppler images of behind-the-wall human movements obtained with a radar system consisting of one transmitter and four receiver antennas were classified. Since the data collected from the four receiver antennas are in different positions, the collected reflection signals also differ. The signals collected with the range-time matrix content were divided into positive and negative parts, resulting in eight images from the four antennas. Instead of using all the data in CNN training, the images were first subjected to a reconstruction process with an autoencoder to reduce differences. As a result, it was observed that reconstructing the images with an autoencoder before classification with CNN increased the classification success. In conclusion, it was observed that the classification success of radar images can be increased by using a hybrid system with an autoencoder to reconstruct the images before classification with CNN.

Dynamic Programming-Based Track-before-Detect Algorithm for Weak Maneuvering Targets in Range–Doppler Plane

This paper focuses on detecting and tracking maneuvering weak targets in the range–Doppler (RD) plane with the track-before-detect (TBD) algorithm based on dynamic programming (DP). Traditional DP-TBD algorithms integrate target detection and tracking in their framework while searching the paths provided by a predefined model of the kinematic properties within the constraints allowed. However, both the approximate motion model used in the RD plane and the model mismatch caused when the target undergoes a maneuver can degrade the TBD performance sharply. To address these issues, this paper accurately describes the evolution of the RD equation based on Constant Acceleration (CA) and Coordinated Turn (CT) motion models with the process noise in the Cartesian coordinate system, and it also employs a recursive method to estimate the parameters in the equations for efficient energy accumulation and path searches. Facing the situation that targets energy accumulation during the DP iteration process will lead to an expansion of the target energy accumulation process. This paper designs a more efficient Optimization Function (OF) to inhibit the expansion effect, improve the resolution of the nearby targets, and increase the detection probability of the weak targets simultaneously. In addition, to search the trajectory more efficiently and accurately, we improved the process of DP multi-frame accumulation, thus reducing the computation amount of large-scale searches. Finally, the effectiveness of the proposed method for CA and CT motion target detection and tracking is verified by many of the simulation experiments that were conducted in this paper.

Digital-assisted multidisciplinary treatment for complex occlusal rehabilitation: an 18-month follow-up case report

BackgroundThis case report highlights the importance of standardized and fully digital sequential treatment in complex occlusal rehabilitation cases. To fully resolve the patient’s dental needs, such cases often require multidisciplinary interventions including periodontal therapy, endodontic treatment, anterior esthetics, implant restoration, and prosthetic rehabilitation. A fully digital workflow (including facial scanners, intraoral scanners, jaw motion tracking systems, virtual articulators, and computer-aided design software) streamlined the complex treatment, enhancing workflow simplicity, efficiency, visibility, and precision.Case presentationThe patient presented with decreased chewing efficiency of the upper and lower prostheses, along with unsatisfactory esthetic appearance of the anterior teeth. After physical examination and radiological assessment, this complex occlusal rehabilitation case required periodontal therapy, anterior esthetic enhancement, implant restoration, and fixed prosthetic rehabilitation. Therefore, a fully digital workflow was adopted. Full-crown prostheses were placed on teeth 13, 23, and 34; a fixed bridge encompassed positions 32 to 42, and single implant crowns were placed on teeth 35 and 36. Implant-supported fixed bridges were constructed for teeth 12 to 22 and 44 to 46, anchored by implants at teeth 12, 22, 44, and 46. All definitive prostheses were fabricated from zirconia ceramics, chosen for their durability and esthetic characteristics. Finally, restorations with satisfactory esthetic and functional characteristics were seated, preserving the tooth and its supporting structures. During treatment and follow-up, the T-scan occlusal analysis system was utilized to continuously monitor and guide the adjustment of occlusal distribution across the patient’s dental arches. After 18 months, the patient remains satisfied with the definitive restorations.ConclusionsThis report is intended to help dentists understand and implement standardized and fully digital workflows during the management of complex occlusal rehabilitation cases; it may also facilitate harmonious integration of esthetic and functional characteristics.

Neural mechanisms for secondary suppression of emotional distractors: Evidence from concurrent electroencephalography-magnetoencephalography data.

Distractor suppression allows us to remain on-task in the presence of distractions by filtering task-irrelevant information from ongoing cognitive processing and responding. Electrophysiological studies have revealed that this key feature of selective attention is a dynamic process that involves at least two distinct stages of processing. Two important aspects of these processing stages remain unclear: Whether the processing of emotional distractors at an earlier stage is automatic, as reflected in the N2/early posterior negativity (EPN) component; and what functional-anatomical brain systems are recruited in each stage. The present study addresses these issues by measuring brain activity with concurrent electroencephalography-magnetoencephalography (MEG) recordings while participants performed a combined rapid serial visual presentation and motion tracking task. Event-related potentials (ERP) showed significant effects of attentional capture and attentional modulation during two time windows marked by the N2/EPN and P3b ERP components. Source reconstruction of concurrent MEG measurements revealed activation of the left visual association cortex and anterior cingulate cortex during the N2/EPN time window, activation of the insula during the early phase of the P3b and anterior cingulate cortex activity during the later phase of the P3b. The findings provide novel evidence establishing a connection between the increased N2 response to negative pictures and the activation of the cingulate gyrus, which facilitates the suppression of distractions during demanding cognitive tasks. In addition, distinct activation patterns were observed in the insula and anterior cingulate cortex during the P3b time window, indicating that attentional control mediated by the anterior cingulate cortex operates to suppress the processing of distracting emotional stimuli. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Stretchable Iontronic Tactile Sensing Fabric.

The iontronic tactile sensing modality has garnered significant attention due to its exceptional sensitivity, immunity to noise, and versatility in materials. Recently, various formats of iontronic tactile sensors have been developed, including droplets, polymer films, paper, ionic gels, and fabrics. However, the stretchability of the current iontronic pressure sensing fabric is inadequate, hindered by the limited stretchiness of the ionic functional fabric. Incorporating a stretchable tactile sensing implement could enhance the wear comfortability by preventing relative movement and ensuring intimate contact between the sensor and the skin. The research focuses on the development of a stretchable iontronic pressure sensing (SIPS) fabric for monitoring diverse aspects of body health and movement in wearable applications. The tactile sensing structure is generated at the iontronic interface between highly stretchable ionic and conductive fabrics. In particular, the ionic fabric is prepared by coating a layer of polyurethane/ionic liquid gel onto a Spandex fabric. To showcase its remarkable sensitivity, stretchability, and ability to detect diverse body information, several application scenarios have been demonstrated including an elastic wristband for precise pulse wave detection, a flexible belt with multitactile sensing channels for respiration and motion tracking purposes, and a stretchable fabric cuff equipped with a high-resolution sensing array comprising 32 × 32 units for accurate gesture recognition.

Tracking movements of meagre (Argyrosomus regius) during the spawning season: Preliminary indications of off estuary spawning.

Understanding the spawning behavior of meagre (Argyrosomus regius) is crucial for fisheries management and conservation. Meagre forms large spawning aggregations in estuaries, yet details of its spawning grounds remain elusive. We tagged 41 individuals and monitored their movements throughout several spawning seasons. Detections inside estuaries were limited. Fish detected inside the Tejo estuary during the spawning season performed regular movements toward coastal areas, suggesting potential spawning outside estuaries. Our findings underscore the significance of understanding meagre's migratory patterns for effective fisheries management and conservation strategies, supporting the establishment of spatial and seasonal closures during the spawning season.

The Sliding Mode Control for Piezoelectric Tip/Tilt Platform on Precision Motion Tracking

This paper presents the design of a sliding mode controller to compensate hysteresis nonlinearity and achieve precision motion tracking for a novel piezoelectric tip/tilt platform driven by a PZT actuator. The sliding mode control scheme is based on the unique physical characteristics of the piezoelectric tip/tilt platform. The proposed scheme effectively guides the platform state onto a predefined sliding surface and ensures its sustained movement along this manifold. This approach reduces tracking errors compared to conventional methodologies. The stability of the sliding mode control scheme is demonstrated by the Lyapunov theory framework. It achieves precise motion control with minimal tracking error on a piezoelectric tip/tilt platform. The properties of the controller have been confirmed through experimental tests. The proposed control scheme enhances the robust tracking and stability performance on the piezoelectric tip/tilt platform, outperforming traditional control schemes. Compared with the P562.6CD produced by PI Germany, the proposed innovative approach not only boosts the platform’s resolution by 32% but also implements a 33% reduction in cost.

Real-time body movement tracking of athletes via a CNN-based approach

Sports injuries frequently stem from improper poses and movements. This paper explores the potential of using video and deep neural network model in mitigating such risks. A novel real-time body movement tracking system is designed to enable athletes to analyze and refine their techniques without the need for intrusive sensors. Central to our approach is the development of a user-friendly graphical interface, facilitating the effortless display and examination of tracked movements. This system not only enhances athletic performance but also aims to significantly reduce the sports injuries.

Real-time body movement tracking of athletes via a CNN-based approach

Sports injuries frequently stem from improper poses and movements. This paper explores the potential of using video and deep neural network model in mitigating such risks. A novel real-time body movement tracking system is designed to enable athletes to analyze and refine their techniques without the need for intrusive sensors. Central to our approach is the development of a user-friendly graphical interface, facilitating the effortless display and examination of tracked movements. This system not only enhances athletic performance but also aims to significantly reduce the sports injuries.

Impact evaluation of development plans in the Egyptian harbors on morphological changes using numerical simulation (case study: Damietta harbor, northeastern coast of Egypt)

The Egyptian government is grappling with the challenge of sedimentation in Damietta Harbor (DH), leading to expensive and recurring dredging operations for safe vessel navigation. This research examined the changes in the region's coastline, both before and after the port was established between 1977 and 1995. The impact of the government's policy to halt backfilling in the navigation lane on adjacent beaches until 2023 was also assessed using remote sensing (RS) and the Digital Shoreline Analysis System (DSAS) program, revealing varying yearly accretion and erosion rates. Following a shoreline movement tracking procedure, in the period from 1985 to 2023, the total areas undergoing erosion and accretion amounted to −1.36 km2 and +2.21 km2, respectively.To address the issue, the research team developed scenarios reflecting regional realities and conducted a numerical simulation using the Coastal Modeling System (CMS). Morphological alterations in the approach channel and pre- and post-port regions were monitored to assess the scenarios. The study also explored how deepening the navigation channel affected the annual sediment volume. Results showed that Scenario 5, involving breakwaters extension and the new western breakwater (NWBW), effectively controlled sediment. However, sedimentation increased with the deepening of the navigation channel. Scenario 7, with a 19 m deepening, exhibited slightly higher sediment volume by 21.75% but stood out for its capacity to handle large vessels. Additionally, the sedimentation in the navigation channel experienced a notable 72.1% decrease in Scenario 8, which portrays the anticipated final state of DH compared to the benchmark case.The study noted morphological changes from planned coastal constructions on the eastern side, including detached breakwaters (DBW) and Y-groins (Y-gs). Despite significant development costs, these structures were deemed insufficient to stabilize the shoreline. In summary, the research highlights the complexity of addressing sedimentation in DH, emphasizing the need for nuanced approaches in coastal management, and considering the consequences of deepening navigation channels.

Soft Sensor-Based Deep Temporal-Graph Convolutional Network for Applications in Human Motion Tracking

Soft Sensor-Based Deep Temporal-Graph Convolutional Network for Applications in Human Motion Tracking

Fish 3D Locomotion app: a user-friendly computer application package for automatic data calculation and endpoint extraction for novel tank behavior in fish.

This paper introduces the Fish 3D Locomotion app (F3LA), a Python-based, Graphical User Interface (GUI)-equipped tool designed to automate behavioral endpoint extraction in zebrafish locomotion assays. Building on our previous work, which utilized a specialized aquatic tank with a mirror and a single camera for fish movement tracking in three dimensions, F3LA significantly enhances data processing efficiency. Its accuracy was tested by reanalyzing and comprehensively comparing the calculated data with the previously published data from prior publications. From the comparison results, 90% of endpoints showed a similar statistical difference result. These minor differences were due to the different starting points for the dataset and updated calculation formulas that are implemented in F3LA. In addition, shoaling area or shoaling volume calculations are also included in F3LA as a new feature that can serve as sensitive indicators of social cohesion, group dynamics, or stress responses, offering insights into neuropsychological conditions or the effects of pharmacological interventions. Furthermore, F3LA offers a marked improvement over manual operations, being at least five times faster, while maintaining consistent accuracy as it reduces human-induced errors, ensuring a higher degree of reliability in the results. Finally, the potency of F3LA was tested to evaluate the toxicities of 14 rare earth elements (REEs) to the adult zebrafish behaviors. Based on the results, our findings suggested that each tested REE altered fish behaviors in different patterns and magnitudes to each other. However, among the tested light rare earth elements (LREEs), neodymium was demonstrated to cause more relatively severe behavior alterations than other LREEs, indicated by the statistically higher value of entropy (0.2695 ± 0.04977 (mean with a standard deviation)) than the control group (0.2352 ± 0.05896). Meanwhile, in terms of heavy rare earth elements (HREEs), erbium seemed to lead to more distinct behavior toxicities than other HREEs, which was shown by the statistically lower level of fractal dimension (2.022 ± 0.3412) than the untreated group (2.255 ± 0.1661). Taken together, F3LA's development marks a significant advance in high-throughput toxicological and pharmacological assessments in zebrafish, leveraging three-dimensional locomotion data for a more comprehensive analysis of fish behavior performance, providing a significant contribution to research in various fields.

Intraoral scanner-based virtual facebow transferring: A chairside dental technique.

Accurately mounting dental casts on an articulator is an essential step in prosthetic treatments. In digital dentistry, virtual articulator mounting procedures rely on virtual facebow records. However, virtual facebow records usually require devices like face scanners or jaw motion tracking systems that are not commonly available in most dental practices. The present technique report describes a straightforward intraoral scanner-based virtual facebow transfer approach. In this technique, a reference facebow joint support was first scanned and aligned with a virtual articulator. Then, a patient's facebow joint support and bite fork assembly were scanned chairside with an intraoral scanner and aligned with the virtual articulator by matching common features with the reference facebow joint support. After aligning the patient's intraoral scans with the patient's bite fork scan that was already superimposed on the virtual articulator, a virtual mounting process was achieved. Once the corresponding reference facebow joint supports have been generated, this technique can be easily implemented with most facebow systems and be seamlessly integrated into daily clinical practice as only an intraoral scanner and a conventional facebow were required.

Foveolar Drusen Decrease Fixation Stability in Pre-Symptomatic AMD.

This study aims at linking subtle changes of fixational eye movements (FEM) in controls and in patients with foveal drusen using adaptive optics retinal imaging in order to find anatomo-functional markers for pre-symptomatic age-related macular degeneration (AMD). We recruited 7 young controls, 4 older controls, and 16 patients with presymptomatic AMD with foveal drusen from the Silversight Cohort. A high-speed research-grade adaptive optics flood illumination ophthalmoscope (AO-FIO) was used for monocular retinal tracking of fixational eye movements. The system allows for sub-arcminute resolution, and high-speed and distortion-free imaging of the foveal area. Foveal drusen position and size were documented using gaze-dependent imaging on a clinical-grade AO-FIO. FEM were measured with high precision (RMS-S2S = 0.0015degrees on human eyes) and small foveal drusen (median diameter = 60 µm) were detected with high contrast imaging. Microsaccade amplitude, drift diffusion coefficient, and ISOline area (ISOA) were significantly larger for patients with foveal drusen compared with controls. Among the drusen participants, microsaccade amplitude was correlated to drusen eccentricity from the center of the fovea. A novel high-speed high-precision retinal tracking technique allowed for the characterization of FEM at the microscopic level. Foveal drusen altered fixation stability, resulting in compensatory FEM changes. Particularly, drusen at the foveolar level seemed to have a stronger impact on microsaccade amplitudes and ISOA. The unexpected anatomo-functional link between small foveal drusen and fixation stability opens up a new perspective of detecting oculomotor signatures of eye diseases at the presymptomatic stage.

High-spatiotemporal resolution microwave-induced thermoacoustic tomography for imaging biological dynamics in deep tissue

Biological systems undergo constant dynamic changes across various spatial and temporal scales. To investigate the intricate biological dynamics in living organisms, there is a strong need for high-speed and high-resolution imaging capabilities with significant imaging depth. In this work, we present high-spatiotemporal resolution microwave-induced thermoacoustic tomography (HR-MTAT) as a method for imaging biological dynamics in deep tissues. HR-MTAT utilizes nanosecond pulsed microwave excitation and ultrasound detection, with appropriate spatial configurations, to achieve high coupling of the sample to the microwaves, to produce images in soft tissue with dielectric contrast and sub-millimeter spatial resolution (230 μm), to a depth of a few centimeters. Notably, by employing a 128-channel parallel signal acquisition and digitization strategy, the field programmable gate array module manages data synthesis, and GPU-based parallel pixel reconstruction facilitates HR-MTAT to accomplish single-frame image reconstruction in an impressive 50 μs. The practical feasibility of HR-MTAT was evaluated in live mice. The results show that HR-MTAT can noninvasively image whole-body small animals (up to 60 mm in depth) with clear resolution of internal organ structures at a frame rate of 100 Hz, without the need for labeling. At this high spatiotemporal resolution, HR-MTAT can capture respiration, heartbeat, and arterial pulse propagation without motion artifacts and track bio-nanoprobes in livers and tumors. These findings demonstrate HR-MTAT's ability to perform dynamic imaging with high contrast and resolution in deep tissues.

Protocol to record and analyze primate leaping in three dimensions in the wild.

Several studies comparing primate locomotion under lab versus field conditions have shown the importance of implementing both types of studies, as each has their advantages and disadvantages. However, three-dimensional (3D) motion capture of primates has been challenging under natural conditions. In this study, we provide a detailed protocol on how to collect 3D biomechanical data on primate leaping in their natural habitat that can be widely implemented. To record primate locomotion in the dense forest we use modified GoPro Hero Black cameras with zoom lenses that can easily be carried around and set up on tripods. We outline details on how to obtain camera calibrations at greater heights and how to process the collected data using the MATLAB camera calibration app and the motion tracking software DLTdv8a. We further developed a new MATLAB application "WildLeap3D" to generate biomechanical performance metrics from the derived x, y, z coordinates of the leaps. We provide details on how to collect data on support diameter, compliance, and orientation, and combine these with the jumps to study locomotor performance in an ecological context. We successfully reconstructed leaps of wild primates in the 3D space under natural conditions and provided data on four representative leaps. We provide exemplar data on primate velocity and acceleration during a leap and show how our protocol can be used to analyze segmental kinematics. This study will help to make motion capture of freely moving animals more accessible and help further our knowledge about animal locomotion and movement.

Flexible circuit-based spatially aware modular optical brain imaging system for high-density measurements in natural settings.

Functional near-infrared spectroscopy (fNIRS) presents an opportunity to study human brains in everyday activities and environments. However, achieving robust measurements under such dynamic conditions remains a significant challenge. The modular optical brain imaging (MOBI) system is designed to enhance optode-to-scalp coupling and provide a real-time probe three-dimensional (3D) shape estimation to improve the use of fNIRS in everyday conditions. The MOBI system utilizes a bendable and lightweight modular circuit-board design to enhance probe conformity to head surfaces and comfort for long-term wearability. Combined with automatic module connection recognition, the built-in orientation sensors on each module can be used to estimate optode 3D positions in real time to enable advanced tomographic data analysis and motion tracking. Optical characterization of the MOBI detector reports a noise equivalence power of 8.9 and at 735 and 850nm, respectively, with a dynamic range of 88dB. The 3D optode shape acquisition yields an average error of 4.2mm across 25 optodes in a phantom test compared with positions acquired from a digitizer. Results for initial in vivo validations, including a cuff occlusion and a finger-tapping test, are also provided. To the best of our knowledge, the MOBI system is the first modular fNIRS system featuring fully flexible circuit boards. The self-organizing module sensor network and automatic 3D optode position acquisition, combined with lightweight modules ( ) and ergonomic designs, would greatly aid emerging explorations of brain function in naturalistic settings.

Head tracking using an optical soft tactile sensing surface.

This research proposes a sensor for tracking the motion of a human head via optical tactile sensing. It implements the use of a fibrescope a non-metal alternative to a webcam. Previous works have included robotics grippers to mimic the sensory features of human skin, that used monochrome cameras and depth cameras. Tactile sensing has shown advantages in feedback-based interactions between robots and their environment. The methodology in this paper is utilised to track motion of objects in physical contact with these sensors to replace external camera based motion capture systems. Our immediate application is related to detection of human head motion during radiotherapy procedures. The motion was analysed in two degrees of freedom, respective to the tactile sensor (translational in z-axis, and rotational around y-axis), to produce repeatable and accurate results. The movements were stimulated by a robot arm, which also provided ground truth values from its end-effector. The fibrescope was implemented to ensure the device's compatibility with electromagnetic waves. The cameras and the ground truth values were time synchronised using robotics operating systems tools. Image processing methods were compared between grayscale and binary image sequences, followed by motion tracking estimation using deterministic approaches. These included Lukas-Kanade Optical Flow and Simple Blob Detection, by OpenCV. The results showed that the grayscale image processing along with the Lukas-Kanade algorithm for motion tracking can produce better tracking abilities, although further exploration to improve the accuracy is still required.

CRISPR-array-mediated imaging of non-repetitive and multiplex genomic loci in living cells.

Dynamic imaging of genomic loci is key for understanding gene regulation, but methods for imaging genomes, in particular non-repetitive DNAs, are limited. We developed CRISPRdelight, a DNA-labeling system based on endonuclease-deficient CRISPR-Cas12a (dCas12a), with an engineered CRISPR array to track DNA location and motion. CRISPRdelight enables robust imaging of all examined 12 non-repetitive genomic loci in different cell lines. We revealed the confined movement of the CCAT1 locus (chr8q24) at the nuclear periphery for repressed expression and active motion in the interior nucleus for transcription. We uncovered the selective repositioning of HSP gene loci to nuclear speckles, including a remarkable relocation of HSPH1 (chr13q12) for elevated transcription during stresses. Combining CRISPR-dCas12a and RNA aptamers allowed multiplex imaging of four types of satellite DNA loci with a single array, revealing their spatial proximity to the nucleolus-associated domain. CRISPRdelight is a user-friendly and robust system for imaging and tracking genomic dynamics and regulation.

Development of a multi-level feature fusion model for basketball player trajectory tracking

To solve the problems of low matching degree, long tracking time, and low accuracy of multi-target tracking in the process of athlete motion trajectory tracking using deep learning technology, a new athlete motion trajectory tracking model was proposed in this study. The study first optimized the current object detection algorithm in basketball, utilized a hybrid attention mechanism to extract object features, and improved the non-maximum suppression strategy. Then, a hybrid branch network was introduced to improve the residual network and a new athlete identity recognition model was proposed. Finally, a new trajectory tracking model was designed by combining the object detection model and the athlete identity recognition model. The research results indicated that in the object detection experiment, the detection time of the proposed object detection algorithm was always below 0.4 s, and its average accuracy reached up to 0.63. In trajectory tracking testing, the final built tracking model had a multi-target tracking accuracy of up to 0.98, and its tracking overlap rate was as low as 0.02. This study has the following two contributions. Firstly, a new model of athlete trajectory tracking is proposed, which improves the accuracy and efficiency of multi-target tracking by optimizing object detection algorithm and introducing hybrid branch network. Second, the model has excellent performance in both object detection and track tracking, which can not only provide a new solution for athletes' motion trajectory tracking, but also significantly improve the effect of motion tracking.