Gait analysis is an essential tool for detecting biomechanical irregularities, designing personalized rehabilitation plans, and enhancing athletic performance. Currently, gait assessment depends on either visual observation, which lacks consistency between raters and requires clinical expertise, or instrumented evaluation, which is costly, invasive, time-consuming, and requires specialized equipment and trained personnel. Markerless gait analysis using 2D pose estimation techniques has emerged as a potential solution, but it still requires significant computational resources and human involvement, making it challenging to use. This research proposes an automated method for temporal gait analysis that employs the MediaPipe Pose, a low-computational-resource pose estimation model. The study validated this approach against the Vicon motion capture system to evaluate its reliability. The findings reveal that this approach demonstrates good (ICC_(2,1) > 0.75) to excellent (ICC_(2,1) > 0.90) agreement in all temporal gait parameters except for double support time (right leg switched to left leg) and swing time (right), which only exhibit a moderate (ICC_(2,1) > 0.50) agreement. Additionally, this approach produces temporal gait parameters with low mean absolute error. It will be useful in monitoring changes in gait and evaluating the effectiveness of interventions such as rehabilitation or training programs in the community.

This study aims to investigate the burnout levels of the educators with respect to gender, teaching experience, and educational level. The subjects of the study are 31 educators. A survey design using a questionnaire was utilized to collect data within three burnout dimensions, i.e., emotional exhaustion (EE), depersonalization (DP), and reduced personal accomplishment (PA). The study has found that the educators are emotionally exhausted and experience reduced personal accomplishment levels with high levels of depersonalization. Both genders regardless of years of experience with Bachelor, Master, and PhD degrees demonstrated high levels of emotional exhaustion. The educators who are troubled by depersonalization are mainly Bachelor degree holders with less than 5 years of experience. This indicates that these educators have negative attitudes towards the people they are working with including students and parents. This may be attributed to their lack of working experience. Nevertheless, female educators with Master degrees and 6 to 10 years of experience are highly affected by reduced personal accomplishment levels. The lack of fulfillment felt by these educators can lead to weak performance in class. The findings from this study are essential to give an overview on the burnout levels among educators and identify alternative solutions to overcome this situation. In addition, school authorities and administrators can take these factors into account when making recruitment decisions.

Nanocarriers loaded with anticancer agents strategically intervene to block cell signaling pathways in glioblastoma.

This paper examines the exponentially weighted moving average (EWMA) chart with estimated process parameters. As the run length distribution is skewed when the process is in-control or slightly out-of-control, the average run length (ARL) provides less meaningful interpretation of a chart’s performance. Therefore, in this paper, the median run length (MRL) and expected MRL (EMRL) are used as alternative performance criteria. Additionally, the methodology for computing the EMRL of the EWMA chart with known process parameters is presented. Since the performance of the EWMA chart is affected by estimation error, a study on the minimum number of Phase-I samples required so that the chart with estimated parameters has a desired performance is conducted. As this study reveals that a large number of Phase-I samples are needed, optimal design procedures for minimising the out-of-control MRL and EMRL of the EWMA chart with estimated process parameters are suggested. By using these proposed procedures, the EWMA chart with estimated parameters will have a closer performance to its known parameters counterpart, even with a reasonable number of Phase-I samples. The construction of the MRL based EWMA chart with estimated parameters is illustrated using real data and compared with the corresponding chart based on ARL.

In physical therapy, exercises improve range of motion, muscle strength, and flexibility, where motion-tracking devices record motion data during exercises to improve treatment outcomes. Cameras and inertial measurement units (IMUs) are the basis of these devices. However, issues such as occlusion, privacy, and illumination can restrict vision-based systems. In these circumstances, IMUs may be employed to focus on a patient’s progress quantitatively during their rehabilitation. In this study, a 3D rigid body that can substitute a human arm was developed, and a two-stage algorithm was designed, implemented, and validated to estimate the elbow joint angle of that rigid body using three IMUs and incorporating the Madgwick filter to fuse multiple sensor data. Two electro-goniometers (EGs) were linked to the rigid body to verify the accuracy of the joint angle measuring algorithm. Additionally, the algorithm’s stability was confirmed even in the presence of external acceleration. Multiple trials using the proposed algorithm estimated the elbow joint angle of the rigid body with a maximum RMSE of 0.46°. Using the IMU manufacturer’s (WitMotion) algorithm (Kalman filter), the maximum RMSE was 1.97°. For the fourth trial, joint angles were also calculated with external acceleration, and the RMSE was 0.996°. In all cases, the joint angles were within therapeutic limits.