Analysis of Factors Influencing the Precision of Body Tracking Outcomes in Industrial Gesture Control.

The body tracking systems on the current market offer a wide range of options for tracking the movements of objects, people, or extremities. The precision of this technology is often limited and determines its field of application. This work aimed to identify relevant technical and environmental factors that influence the performance of body tracking in industrial environments. The influence of light intensity, range of motion, speed of movement and direction of hand movement was analyzed individually and in combination. The hand movement of a test person was recorded with an Azure Kinect at a distance of 1.3 m. The joints in the center of the hand showed the highest accuracy compared to other joints. The best results were achieved at a luminous intensity of 500 lx, and movements in the x-axis direction were more precise than in the other directions. The greatest inaccuracy was found in the z-axis direction. A larger range of motion resulted in higher inaccuracy, with the lowest data scatter at a 100 mm range of motion. No significant difference was found at hand velocity of 370 mm/s, 670 mm/s and 1140 mm/s. This study emphasizes the potential of RGB-D camera technology for gesture control of industrial robots in industrial environments to increase efficiency and ease of use.

[Lower limb joint contact forces and ground reaction forces analysis based on Azure Kinect motion capture].

Traditional gait analysis systems are typically complex to operate, lack portability, and involve high equipment costs. This study aims to establish a musculoskeletal dynamics calculation process driven by Azure Kinect. Building upon the full-body model of the Anybody musculoskeletal simulation software and incorporating a foot-ground contact model, the study utilized Azure Kinect-driven skeletal data from depth videos of 10 participants. The in-depth videos were prepossessed to extract keypoint of the participants, which were then adopted as inputs for the musculoskeletal model to compute lower limb joint angles, joint contact forces, and ground reaction forces. To validate the Azure Kinect computational model, the calculated results were compared with kinematic and kinetic data obtained using the traditional Vicon system. The forces in the lower limb joints and the ground reaction forces were normalized by dividing them by the body weight. The lower limb joint angle curves showed a strong correlation with Vicon results (mean ρ values: 0.78 ~ 0.92) but with root mean square errors as high as 5.66°. For lower limb joint force prediction, the model exhibited root mean square errors ranging from 0.44 to 0.68, while ground reaction force root mean square errors ranged from 0.01 to 0.09. The established musculoskeletal dynamics model based on Azure Kinect shows good prediction capabilities for lower limb joint forces and vertical ground reaction forces, but some errors remain in predicting lower limb joint angles.

A Study on the 3D Reconstruction Strategy of a Sheep Body Based on a Kinect v2 Depth Camera Array.

Non-contact measurement based on the 3D reconstruction of sheep bodies can alleviate the stress response in sheep during manual measurement of body dimensions. However, data collection is easily affected by environmental factors and noise, which is not conducive to practical production needs. To address this issue, this study proposes a non-contact data acquisition system and a 3D point cloud reconstruction method for sheep bodies. The collected sheep body data can provide reference data for sheep breeding and fattening. The acquisition system consists of a Kinect v2 depth camera group, a sheep passage, and a restraining pen, synchronously collecting data from three perspectives. The 3D point cloud reconstruction method for sheep bodies is implemented based on C++ language and the Point Cloud Library (PCL). It processes noise through pass-through filtering, statistical filtering, and random sample consensus (RANSAC). A conditional voxel filtering box is proposed to downsample and simplify the point cloud data. Combined with the RANSAC and Iterative Closest Point (ICP) algorithms, coarse and fine registration are performed to improve registration accuracy and robustness, achieving 3D reconstruction of sheep bodies. In the base, 135 sets of point cloud data were collected from 20 sheep. After 3D reconstruction, the reconstruction error of body length compared to the actual values was 0.79%, indicating that this method can provide reliable reference data for 3D point cloud reconstruction research of sheep bodies.

Concurrent Validity of Motion Parameters Measured With an RGB-D Camera-Based Markerless 3D Motion Tracking Method in Children and Young Adults.

OBJECTIVE: Low-cost, portable RGB-D cameras with integrated motion tracking functionality enable easy-to-use 3D motion analysis without requiring expensive facilities and specialized personnel. However, the accuracy of existing systems is insufficient for most clinical applications, particularly when applied to children. In previous work, we developed an RGB-D camera-based motion tracking method and showed that it accurately captures body joint positions of children and young adults in 3D. In this study, the validity and accuracy of clinically relevant motion parameters that were computed from kinematics of our motion tracking method are evaluated in children and young adults. METHODS: Twenty-three typically developing children and healthy young adults (5-29 years, 110-189 cm) performed five movement tasks while being recorded simultaneously with a marker-based Vicon system and an Azure Kinect RGB-D camera. Motion parameters were computed from the extracted kinematics of both methods: time series measurements, i.e., measurements over time, peak measurements, i.e., measurements at a single time instant, and movement smoothness. The agreement of these parameter values was evaluated using Pearson's correlation coefficients r for time series data, and mean absolute error (MAE) and Bland-Altman plots with limits of agreement for peak measurements and smoothness. RESULTS: Time series measurements showed strong to excellent correlations (r-values between 0.8 and 1.0), MAE for angles ranged from 1.5 to 5 degrees and for smoothness parameters (SPARC) from 0.02-0.09, while MAE for distance-related parameters ranged from 9 to 15 mm. CONCLUSION: Extracted motion parameters are valid and accurate for various movement tasks in children and young adults, demonstrating the suitability of our tracking method for clinical motion analysis. CLINICAL IMPACT: The low-cost portable hardware in combination with our tracking method enables motion analysis outside of specialized facilities while providing measurements that are close to those of the clinical gold-standard.

Grape Maturity Estimation Using Time-of-Flight and LiDAR Depth Cameras.

This article investigates the potential for using low-cost depth cameras to estimate the maturity of green table grapes after they have been harvested. Time-of-flight (Kinect Azure) and LiDAR (Intel L515) depth cameras were used to capture depth scans of green table grape berries over time. The depth scans of the grapes are distorted due to the diffused scattering of the light emitted from the cameras within the berries. This causes a distance bias where a grape berry appears to be further from the camera than it is. As the grape aged, the shape of the peak corresponding to the grape became increasingly flattened in shape, resulting in an increased distance bias over time. The distance bias variation with time was able to be fitted with an R2 value of 0.969 for the Kinect Azure and an average of 0.904 for the Intel L515. This work shows that there is potential to use time-of-flight and LIDAR cameras for estimating grape maturity postharvest in a non-contact and nondestructive manner.

Estimation of human body 3D pose for parent-infant interaction settings using azure Kinect and OpenPose.

Automatic pose estimation has become a valuable tool for the study of human behavior, including dyadic interactions. It allows researchers to analyze the nuanced dynamics of interactions more effectively, and facilitates the integration of behavioral data with other modalities (EEG, etc.). However, many technical difficulties remain. Particularly, for parent-infant interactions, automatic pose estimation for infants is unpredictable; the immature proportions and smaller bodies of children may cause misdetections. OpenPose is one tool that has shown high performance in pose tracking from video, even in infants. However, OpenPose is limited to 2D (i.e., coordinates relative to the image space). This may be undesirable in a multitude of paradigms (e.g., naturalistic settings). We developed a method for expanding the functionality of OpenPose to 3D, tailored to parent-infant interaction paradigms. This method merges the estimations from OpenPose with the depth information from a depth camera to obtain a 3D pose that works even for young infants.•Video recordings of interactions of parents and infants are taken using a dual color-depth camera.•2D-positions of parents and their infants are estimated from the color video.•Using the depth camera, we transform the 2D estimations into real-world 3D positions, allowing movement analysis in full-3D space.

Test-Retest Reliability of Movement Displacement during a 20-s Stepping-in-Place Test in Community-Dwelling Older Adults with and without Supportive Care.

INTRODUCTION: Our recent reports have shown that movement pattern and displacement assessed with an infrared depth sensor during a 20-s stepping-in-place test (ST) correlates with measures of balance and need for assistance in older individuals. This study investigated ST test-retest reliability in community-dwelling older adults with and without supportive care. METHODS: Two groups were included: those not participating (HO: n = 25, 74.7 ± 5.2 years) and those participating (DSU: n = 41, 78.8 ± 5.8 years) in regular senior day services (supportive care). HO completed three ST trials, separated by 1 week, while DSU completed two ST trials during the same half-day supportive care visit. Testing was conducted with eyes open. ST measures included head movement path distance (TMD), maximum movement displacement (MMD), knee movement path length (KMD), and stepping rate (STEP). TMD×KMD-1 ratio indicated upper-body sway relative to lower-body. Test-retest reliability (intra-class correlation coefficients, ICCs) and between-trial and between group differences (ANCOVA, adjusting for age) were assessed. RESULTS: After adjusting for age, TMD, KMD, TMD×KMD-1 were lesser and STEP was greater in HO than DUS. HO ST variables did not differ across testing days. HO ICC (1, 3) for TMD (0.911 [95% confidence interval: 0.827-0.958]), MMD (0.918 [0.814-0.961]), KMD (0.838 [0.685-0.923]), and TMD×KMD-1 (0.940 [0.884-0.872]) showed strong to very strong reliability. Similarly, DSU ST variables did not differ across same day trials and ICC (1, 2) for TMD, KMD, and TMD×KMD-1 displayed very strong reliability. CONCLUSION: These ST variables exhibited excellent test-retest reliability of discriminating between community-dwelling older adults with and without supportive care.

Kinematic synergies show good consistency when extracted with a low-cost markerless device and a marker-based motion tracking system.

Recently, markerless tracking systems, such as RGB-Depth cameras, have spread to overcome some of the limitations of the gold standard marker-based tracking systems. Although these systems are valuable substitutes for human motion analysis, as they guarantee higher flexibility, faster setup time and lower costs, their tracking accuracy is lower with respect to marker-based systems. Many studies quantified the error made by markerless systems in terms of body segment length estimation, articular angles, and biomechanics, concluding that they are appropriate for many clinical applications related to motion analysis. We propose an innovative approach to compare a markerless tracking system (Kinect V2) with a gold standard marker-based system (Vicon), based on motor control assessment. We quantified kinematic synergies from the tracking data of fifteen participants performing multi-directional upper limb movements. Kinematic synergy analysis decomposes the kinematic data into a reduced set of motor primitives that describe how the central nervous system coordinates motion at spatial and temporal level. Synergies were extracted with the recently released mixed-matrix factorization algorithm. Four synergies were extracted from both marker-based and markerless datasets and synergies were grouped in 6 clusters for each dataset. Cosine similarity in each cluster was ⩾0.60 in both systems, showing good consistency of synergies. Good matching was found between synergies extracted from markerless and from marker-based data, with a cosine similarity between matched synergies ⩾0.60 in 5 out 6 synergies. These results showed that the markerless sensor can be feasible for kinematic synergy analysis for gross movements, as it correctly estimates the number of synergies and in most cases also their spatial and temporal organization.

Inclusion of a skeletal model partly improves the reliability of lower limb joint angles derived from a markerless depth camera.

A single depth camera provides a fast and easy approach to performing biomechanical assessments in a clinical setting; however, there are currently no established methods to reliably determine joint angles from these devices. The primary aim of this study was to compare joint angles as well as the between-day reliability of direct kinematics to model-constrained inverse kinematics recorded using a single markerless depth camera during a range of clinical and athletic movement assessments.A secondary aim was to determine the minimum number of trials required to maximize reliability. Eighteen healthy participants attended two testing sessions one week apart. Tasks included treadmill walking, treadmill running, single-leg squats, single-leg countermovement jumps, bilateral countermovement jumps, and drop vertical jumps. Keypoint data were processed using direct kinematics as well as in OpenSim using a full-body musculoskeletal model and inverse kinematics. Kinematic methods were compared using statistical parametric mapping and between-day reliability was calculated using intraclass correlation coefficients, mean absolute error, and minimal detectable change. Keypoint-derived inverse kinematics resulted in significantly smaller hip flexion (range = -9 to -2°), hip abduction (range = -3 to -2°), knee flexion (range = -5° to -2°), and greater dorsiflexion angles (range = 6-15°) than direct kinematics. Both markerless kinematic methods had high between-day reliability (inverse kinematics ICC 95 %CI = 0.83-0.90; direct kinematics ICC 95 %CI = 0.80-0.93). For certain tasks and joints, keypoint-derived inverse kinematics resulted in greater reliability (up to 0.47 ICC) and smaller minimal detectable changes (up to 13°) than direct kinematics. Performing 2-4 trials was sufficient to maximize reliability for most tasks. A single markerless depth camera can reliably measure lower limb joint angles, and skeletal model-constrained inverse kinematics improves lower limb joint angle reliability for certain tasks and joints.

Developing a Motion Sensor-Based Game to Support Frozen Shoulder Rehabilitation in Older Adults through a Participatory Design Approach.

Objective: Although some serious games have been developed for physical therapy, little work has been conducted through a participatory design approach. Therefore, a game prototype was developed, which involved related stakeholders in the design process. Materials and Methods: The iterative participatory design process was adopted with the input of 18 patients with frozen shoulder symptoms, 4 health professionals, 2 game designers, and 5 researchers in an iterative process to design, test, and evaluate the game prototype. In total, 17 patients participated in the interviews to explore their needs and desires for a serious game. The health professionals participated in the interviews to understand the medical requirement and experience pertaining to frozen shoulder and were included in the workshop to give feedback on the game prototype. At the conclusion of the iterative design process, a Kinect-based prototype game with three levels was used for a case study with one patient who was diagnosed with frozen shoulder and has been receiving medical treatment in the hospital. Results: Based on the outcomes derived from data collected among diverse stakeholders, the prototype game underwent iterative development by the team and was assessed by a participant with frozen shoulder symptoms. Findings revealed that the participant demonstrated enhanced shoulder mobility and a reduction in pain intensity, despite the lack of significant improvement for health-related quality of life. Nevertheless, the participant reported a positive experience with the prototype game. Conclusion: This study underscores the importance of involving diverse stakeholders in the development process to create more effective and user-centric serious games for rehabilitation. The participatory approach, exemplified by the prototype game, demonstrates potential improvements in both user experience and overall effectiveness during the rehabilitation process.

Evaluating Desk-Assisted Standing Techniques for Simulated Pregnant Conditions: An Experimental Study Using a Maternity-Simulation Jacket.

Lower back pain, a common issue among pregnant women, often complicates daily activities like standing up from a chair. Therefore, research into the standing motion of pregnant women is important, and many research studies have already been conducted. However, many of these studies were conducted in highly controlled environments, overlooking everyday scenarios such as using a desk for support when standing up, and their effects have not been adequately tested. To address this gap, we measured multimodal signals for a sit-to-stand (STS) movement with hand assistance and verified the changes using a t-test. To avoid imposing strain on pregnant women, we used 10 non-diseased young adults who wore jackets designed to simulate pregnancy conditions, thus allowing for more comprehensive and rigorous experimentation. We attached surface electromyography (sEMG) sensors to the erector spinae muscles of participants and measured changes in muscle activity, skeletal positioning, and center of pressure both before and after wearing a Maternity-Simulation Jacket. Our analysis showed that the jacket successfully mimicked key aspects of the movement patterns typical in pregnant women. These results highlight the possibility of developing practical strategies that more accurately mirror the real-life scenarios met by pregnant women, enriching the current research on their STS movement.

Curve Walking Reveals More Gait Impairments in Older Adults with Mild Cognitive Impairment than Straight Walking: A Kinect Camera-Based Study.

Background: Mild cognitive impairment (MCI) can be an early sign of Alzheimer's disease and other types of dementia detectable through gait analysis. Curve walking, which demands greater cognitive and motor skills, may be more sensitive in MCI detection than straight walking. However, few studies have compared gait performance in older adults with and without MCI in these conditions. Objective: To compare the capability of curve and straight walking tests for the detection of MCI among older adults. Methods: We employed a Kinect v.2 camera to record the gait of 55 older adults (30 healthy controls, 25 with MCI) during single-task straight and curve walking tests. We examined 50 gait markers and conducted statistical analyses to compare groups and conditions. The trail was approved with protocol No. IR.SEMUMS.REC.1398.237 by the ethics committee of Semnan University of Medical Sciences in Iran. Results: Older adults with MCI exhibited more compromised gait performance, particularly during curve walking. Curve walking outperformed straight walking in MCI detection, with several gait markers showing significant differences between healthy controls and MCI patients. These markers encompass average velocity, cadence, temporal markers (e.g., gait cycle subphase durations), spatial markers (e.g., foot position changes during gait subphases), and spatiotemporal markers (e.g., step and stride velocities). Conclusions: Our study suggests curve walking as a more informative and challenging test for MCI detection among older adults, facilitating early diagnosis using non-invasive, cost-effective tools like the Kinect v.2 camera, complementing cognitive assessments in early diagnosis, and tracking MCI progression to dementia.

Simulation of Human Movement in Zero Gravity.

In the era of expanding manned space missions, understanding the biomechanical impacts of zero gravity on human movement is pivotal. This study introduces a novel and cost-effective framework that demonstrates the application of Microsoft's Azure Kinect body tracking technology as a motion input generator for subsequent OpenSim simulations in weightlessness. Testing rotations, locomotion, coordination, and martial arts movements, we validate the results' realism under the constraints of angular and linear momentum conservation. While complex, full-body coordination tasks face limitations in a zero gravity environment, our findings suggest possible approaches to device-free exercise routines for astronauts and reveal insights into the feasibility of hand-to-hand combat in space. However, some challenges remain in distinguishing zero gravity effects in the simulations from discrepancies in the captured motion input or forward dynamics calculations, making a comprehensive validation difficult. The paper concludes by highlighting the framework's practical potential for the future of space mission planning and related research endeavors, while also providing recommendations for further refinement.

Development and Validation of a Method of Body Volume and Fat Mass Estimation Using Three-Dimensional Image Processing with a Mexican Sample.

Body composition assessment using instruments such as dual X-ray densitometry (DXA) can be complex and their use is often limited to research. This cross-sectional study aimed to develop and validate a densitometric method for fat mass (FM) estimation using 3D cameras. Using two such cameras, stereographic images, and a mesh reconstruction algorithm, 3D models were obtained. The FM estimations were compared using DXA as a reference. In total, 28 adults, with a mean BMI of 24.5 (±3.7) kg/m2 and mean FM (by DXA) of 19.6 (±5.8) kg, were enrolled. The intraclass correlation coefficient (ICC) for body volume (BV) was 0.98-0.99 (95% CI, 0.97-0.99) for intra-observer and 0.98 (95% CI, 0.96-0.99) for inter-observer reliability. The coefficient of variation for kinetic BV was 0.20 and the mean difference (bias) for BV (liter) between Bod Pod and Kinect was 0.16 (95% CI, -1.2 to 1.6), while the limits of agreement (LoA) were 7.1 to -7.5 L. The mean bias for FM (kg) between DXA and Kinect was -0.29 (95% CI, -2.7 to 2.1), and the LoA was 12.1 to -12.7 kg. The adjusted R2 obtained using an FM regression model was 0.86. The measurements of this 3D camera-based system aligned with the reference measurements, showing the system's feasibility as a simpler, more economical screening tool than current systems.

Practical application of interactive AI technology based on visual analysis in professional system of physical education in universities.

Currently, physical education teaching in universities tends to adopt the traditional model of one teacher for multiple students, which has high requirements for teachers and is difficult to consider students' strengths. On this basis, an interactive system has been established, including three modules: behavior information, user data collection, and behavior evaluation. Taking the 400 m running physical education teaching as an example, Kinectv2 was used to collect students' movements and contours while running, and ORB (Oriented FAST and Rotated BRIEF) feature extraction algorithm was used to extract students' movement features. After importing the data into the interactive system, students and teachers could view it in the system and provide guidance based on the students' actions. This article took 10 students as examples to test their performance changes in the 400 m running before and after systematic training. The results showed that the evaluation score after receiving systematic instruction increased by 6-7 s compared to the score without receiving instruction, with a significant change. This indicated that the interactive AI (artificial intelligence) system constructed in this article can play a significant role in sports teaching of 400 m running.

Assessment of ADHD Subtypes Using Motion Tracking Recognition Based on Stroop Color-Word Tests.

Attention-Deficit/Hyperactivity Disorder (ADHD) is a neurodevelopmental disorder known for its significant heterogeneity and varied symptom presentation. Describing the different subtypes as predominantly inattentive (ADHD-I), combined (ADHD-C), and hyperactive-impulsive (ADHD-H) relies primarily on clinical observations, which can be subjective. To address the need for more objective diagnostic methods, this pilot study implemented a Microsoft Kinect-based Stroop Color-Word Test (KSWCT) with the objective of investigating the potential differences in executive function and motor control between different subtypes in a group of children and adolescents with ADHD. A series of linear mixture modeling were used to encompass the performance accuracy, reaction times, and extraneous movements during the tests. Our findings suggested that age plays a critical role, and older subjects showed improvements in KSWCT performance; however, no significant divergence in activity level between the subtypes (ADHD-I and ADHD-H/C) was established. Patients with ADHD-H/C showed tendencies toward deficits in motor planning and executive control, exhibited by shorter reaction times for incorrect responses and more difficulty suppressing erroneous responses. This study provides preliminary evidence of unique executive characteristics among ADHD subtypes, advances our understanding of the heterogeneity of the disorder, and lays the foundation for the development of refined and objective diagnostic tools for ADHD.

A multifactorial fall risk assessment system for older people utilizing a low-cost, markerless Microsoft Kinect.

Falls among older people are a major health concern. This study aims to develop a multifactorial fall risk assessment system for older people using a low-cost, markerless Microsoft Kinect. A Kinect-based test battery was designed to comprehensively assess major fall risk factors. A follow-up experiment was conducted with 102 older participants to assess their fall risks. Participants were divided into high and low fall risk groups based on their prospective falls over a 6-month period. Results showed that the high fall risk group performed significantly worse on the Kinect-based test battery. The developed random forest classification model achieved an average classification accuracy of 84.7%. In addition, the individual's performance was computed as the percentile value of a normative database to visualise deficiencies and targets for intervention. These findings indicate that the developed system can not only screen out 'at risk' older individuals with good accuracy, but also identify potential fall risk factors for effective fall intervention.Practitioner summary: Falls are the leading cause of injuries in older people. We newly developed a multifactorial fall risk assessment system for older people utilising a low-cost, markerless Kinect. Results showed that the developed system can screen out 'at risk' individuals and identify potential risk factors for effective fall intervention.

Enzymatic activity of bone markers on Lithobates catesbeianus (Shaw, 1802) growth during the ossification process / Atividade enzimática de marcadores ósseos no crescimento de Lithobates catesbeianus (Shaw, 1802) durante o processo de ossificação

Abstract In order to better understand the ossification processes in anurans our study was carried out on tadpoles and adults of Lithobates catesbeianus. In this sense, we characterized the kinetic properties of alkaline phosphatase with p-nitrophenylphosphatase (pNPP) and pyrophosphate (PPi) and evaluated the activities of tartrate-resistant acid phosphatase and acid phosphatase. The enzyme extracts were obtained from tadpoles and adult femurs, which were divided into epiphysis and diaphysis. After homogenization, the samples were submitted to differential centrifugation to obtain cell membranes and, further, to phospholipase C (PIPLC) treatment, to remove membrane-bound proteins anchored by phosphatidylinositol. The average of specific activity for pNPP hydrolysis (at pH 10.5) by alkaline phosphatase released by phosphatidylinositol-specific phospholipase C (PIPLC) from Bacillus cereus among different bone regions at different animal ages was 1,142.57 U.mg-1, while for PPi hydrolysis (at pH 8.0), it was 1,433.82 U.mg-1. Among the compounds tested for enzymatic activity, the one that influenced the most was EDTA, with approximately 67% of inhibition for pNPPase activity and 77% for PPase activity. In the case of kinetic parameters, the enzyme showed a "Michaelian" behavior for pNPP and PPi hydrolysis. The Km value was around 0.6mM for pNPPase activity and ranged from 0.01 to 0.11mM for PPase activity, indicating that the enzyme has a higher affinity for this substrate. The study of pNPP and PPi hydrolysis by the enzyme revealed that the optimum pH of actuation for pNPP was 10.5, while for PPi, which is considered the true substrate of alkaline phosphatase, was 8.0, close to the physiological value. The results show that regardless of the ossification type that occurs, the same enzyme or isoenzymes act on the different bone regions and different life stages of anurans. The similarity of the results of studies with other vertebrates shows that anurans can be considered excellent animal models for the study of biological calcification.

Resumo Para melhor compreender o processo de ossificação em anuros, nosso estudo foi conduzido em girinos e adultos de Lithobates catesbeianus. Nesse sentido, as propriedades cinéticas da fosfatase alcalina com p-nitrofenilfosfato (pNPP) e pirofosfato (PPi) foram caracterizadas, e as atividades enzimáticas das fosfatases ácida e ácida tartarato resistente foram avaliadas. Os extratos enzimáticos foram obtidos de fêmur de girinos e adultos, divididos em epífise e diáfise. Após a homogeneização as amostras foram submetidas à centrifugação diferencial para obter membrana celular e, em seguida, ao tratamento com fosfolipase C (PIPLC), para remover as proteínas de membrana ancoradas por fosfatidilinositol. A média da atividade específica da fosfatase alcalina, liberada pela PIPLC de Bacillus cereus, para a hidrólise de pNPP (pH 10,5) nas diferentes regiões do fêmur e idades dos animais foi de 1.142,57 U.mg-1, enquanto para a hidrólise do PPi (pH 8,0) foi de 1.433,82 U.mg-1. Entre os compostos testados para a atividade enzimática, o de maior influência foi o EDTA, inibindo aproximadamente 67% e 77% das atividades de pNPPase e PPase, respectivamente. Quanto aos parâmetros cinéticos, a enzima apresentou comportamento Michaeliano para a hidrólise dos dois substratos. O valor de Km foi de 0,6 mM para a atividade de pNPPase e variou de 0,01 a 0,11 para a atividade de PPase, indicando uma maior afinidade por esse substrato. O estudo da hidrólise de pNPP e PPi revelou que o pH ótimo aparente de atuação foi de 10,5 para o pNPP e 8,0 para o PPi, próximo ao fisiológico, sendo que esse é considerado o substrato natural da fosfatase alcalina. Os resultados demonstram que, apesar do tipo de ossificação que ocorre, a mesma enzima ou isoenzimas, atuam nos diferentes locais do osso e estágios de vida dos anuros. A similaridade dos estudos com os realizados com outros vertebrados apontam que os anuros podem ser considerados excelentes modelos animais para o estudo da calcificação biológica.

Enzymatic activity of bone markers on Lithobates catesbeianus (Shaw, 1802) growth during the ossification process

Abstract In order to better understand the ossification processes in anurans our study was carried out on tadpoles and adults of Lithobates catesbeianus. In this sense, we characterized the kinetic properties of alkaline phosphatase with p-nitrophenylphosphatase (pNPP) and pyrophosphate (PPi) and evaluated the activities of tartrate-resistant acid phosphatase and acid phosphatase. The enzyme extracts were obtained from tadpoles and adult femurs, which were divided into epiphysis and diaphysis. After homogenization, the samples were submitted to differential centrifugation to obtain cell membranes and, further, to phospholipase C (PIPLC) treatment, to remove membrane-bound proteins anchored by phosphatidylinositol. The average of specific activity for pNPP hydrolysis (at pH 10.5) by alkaline phosphatase released by phosphatidylinositol-specific phospholipase C (PIPLC) from Bacillus cereus among different bone regions at different animal ages was 1,142.57 U.mg-1, while for PPi hydrolysis (at pH 8.0), it was 1,433.82 U.mg-1. Among the compounds tested for enzymatic activity, the one that influenced the most was EDTA, with approximately 67% of inhibition for pNPPase activity and 77% for PPase activity. In the case of kinetic parameters, the enzyme showed a Michaelian behavior for pNPP and PPi hydrolysis. The Km value was around 0.6mM for pNPPase activity and ranged from 0.01 to 0.11mM for PPase activity, indicating that the enzyme has a higher affinity for this substrate. The study of pNPP and PPi hydrolysis by the enzyme revealed that the optimum pH of actuation for pNPP was 10.5, while for PPi, which is considered the true substrate of alkaline phosphatase, was 8.0, close to the physiological value. The results show that regardless of the ossification type that occurs, the same enzyme or isoenzymes act on the different bone regions and different life stages of anurans. The similarity of the results of studies with other vertebrates shows that anurans can be considered excellent animal models for the study of biological calcification.

Resumo Para melhor compreender o processo de ossificação em anuros, nosso estudo foi conduzido em girinos e adultos de Lithobates catesbeianus. Nesse sentido, as propriedades cinéticas da fosfatase alcalina com p-nitrofenilfosfato (pNPP) e pirofosfato (PPi) foram caracterizadas, e as atividades enzimáticas das fosfatases ácida e ácida tartarato resistente foram avaliadas. Os extratos enzimáticos foram obtidos de fêmur de girinos e adultos, divididos em epífise e diáfise. Após a homogeneização as amostras foram submetidas à centrifugação diferencial para obter membrana celular e, em seguida, ao tratamento com fosfolipase C (PIPLC), para remover as proteínas de membrana ancoradas por fosfatidilinositol. A média da atividade específica da fosfatase alcalina, liberada pela PIPLC de Bacillus cereus, para a hidrólise de pNPP (pH 10,5) nas diferentes regiões do fêmur e idades dos animais foi de 1.142,57 U.mg-1, enquanto para a hidrólise do PPi (pH 8,0) foi de 1.433,82 U.mg-1. Entre os compostos testados para a atividade enzimática, o de maior influência foi o EDTA, inibindo aproximadamente 67% e 77% das atividades de pNPPase e PPase, respectivamente. Quanto aos parâmetros cinéticos, a enzima apresentou comportamento Michaeliano para a hidrólise dos dois substratos. O valor de Km foi de 0,6 mM para a atividade de pNPPase e variou de 0,01 a 0,11 para a atividade de PPase, indicando uma maior afinidade por esse substrato. O estudo da hidrólise de pNPP e PPi revelou que o pH ótimo aparente de atuação foi de 10,5 para o pNPP e 8,0 para o PPi, próximo ao fisiológico, sendo que esse é considerado o substrato natural da fosfatase alcalina. Os resultados demonstram que, apesar do tipo de ossificação que ocorre, a mesma enzima ou isoenzimas, atuam nos diferentes locais do osso e estágios de vida dos anuros. A similaridade dos estudos com os realizados com outros vertebrados apontam que os anuros podem ser considerados excelentes modelos animais para o estudo da calcificação biológica.

Indoor Human Action Recognition Based on Dual Kinect V2 and Improved Ensemble Learning Method.

Indoor human action recognition, essential across various applications, faces significant challenges such as orientation constraints and identification limitations, particularly in systems reliant on non-contact devices. Self-occlusions and non-line of sight (NLOS) situations are important representatives among them. To address these challenges, this paper presents a novel system utilizing dual Kinect V2, enhanced by an advanced Transmission Control Protocol (TCP) and sophisticated ensemble learning techniques, tailor-made to handle self-occlusions and NLOS situations. Our main works are as follows: (1) a data-adaptive adjustment mechanism, anchored on localization outcomes, to mitigate self-occlusion in dynamic orientations; (2) the adoption of sophisticated ensemble learning techniques, including a Chirp acoustic signal identification method, based on an optimized fuzzy c-means-AdaBoost algorithm, for improving positioning accuracy in NLOS contexts; and (3) an amalgamation of the Random Forest model and bat algorithm, providing innovative action identification strategies for intricate scenarios. We conduct extensive experiments, and our results show that the proposed system augments human action recognition precision by a substantial 30.25%, surpassing the benchmarks set by current state-of-the-art works.