Local Application of Honey for Postoperative Pain Management and Associated Outcomes Following Tonsillectomy in Children: A Systematic Review and Meta-Analysis.

Background: This study investigates the effect of locally applied honey on pain intensity, analgesia consumption, pain relief and nighttime awakenings in children following tonsillectomy, addressing conflicting evidence and the lack of differentiation between adult and paediatric populations in previous reviews.

Methods: A systematic search was conducted across multiple databases, including Cochrane Library, ClinicalTrials.gov, MEDLINE, Web of Science and Google Scholar.

Exploring the Well-being Experiences of Patients Following Heart Valve Replacement Surgery through the Biopsychosocial-spiritual Model: A Qualitative Content Analysis.

Background: Heart valve replacement (HVR) surgery represents a significant life event that can potentially impact the well-being (WB) of patients; however, there is a shortage of research on the understanding of WB in HVR patients. This study aims to elucidate the WB experiences of patients who have undergone HVR surgery.

Methods: A qualitative directed content analysis approach was employed, focusing on patients who had undergone HVR surgery at hospitals affiliated with Mashhad University of Medical Sciences in Iran from March 2021 to June 2022.

Investigating the impact of patient-centered peer counseling on anxiety and pain among burn patients: A randomized controlled trial.

Objective: Pain and anxiety are common complications in burn patients, significantly impacting treatment effectiveness and overall patient well-being. Peer counseling, a form of patient education provided by individuals with shared experiences, may hold potential to alleviate this pain and anxiety. This study seeks to investigate the effectiveness of patient-centered education through peer counseling on background pain and state anxiety levels in these patients.

The efficacy of technology-based devices on the first-attempt success rate for difficult intravenous access in pediatrics: A systematic review and network meta-analysis.

Introduction: Previous studies have compared various technology-based devices, such as ultrasonography (USG), near-infrared (NIR), and transilluminator (TI), with standard care (SC) to facilitate peripheral intravenous cannulation (PIVC) in pediatric patients. This study aims to investigate the efficacy of these interventions on the first-attempt success rate (FASR) of PIVC in pediatric patients with difficult intravenous access (DIVA) using network meta-analysis (NMA).

Methods: We conducted a comprehensive literature search in databases to identify randomized clinical trials comparing the effects of different devices on the FASR of PIVC from inception until August 2023.

Dual Tasking Affects the Outcomes of Instrumented Timed up and Go, Sit-to-Stand, Balance, and 10-Meter Walk Tests in Stroke Survivors.

Stroke can impair mobility, with deficits more pronounced while simultaneously performing multiple activities. In this study, common clinical tests were instrumented with wearable motion sensors to study motor-cognitive interference effects in stroke survivors (SS). A total of 21 SS and 20 healthy controls performed the Timed Up and Go (TUG), Sit-to-Stand (STS), balance, and 10-Meter Walk (10MWT) tests under single and dual-task (counting backward) conditions.

Post-Stroke Functional Changes: In-Depth Analysis of Clinical Tests and Motor-Cognitive Dual-Tasking Using Wearable Sensors.

Clinical tests like Timed Up and Go (TUG) facilitate the assessment of post-stroke mobility, but they lack detailed measures. In this study, 21 stroke survivors and 20 control participants underwent TUG, sit-to-stand (STS), and the 10 Meter Walk Test (10MWT). Tests incorporated single tasks (STs) and motor-cognitive dual-task (DTs) involving reverse counting from 200 in decrements of 10.

A machine learning model to predict heart failure readmission: toward optimal feature set.

Background: Hospital readmissions for heart failure patients remain high despite efforts to reduce them. Predictive modeling using big data provides opportunities to identify high-risk patients and inform care management. However, large datasets can constrain performance.

Smart wearable insoles in industrial environments: A systematic review.

Background And Purpose: Industrial environments present unique challenges in ensuring worker safety and optimizing productivity. The emergence of smart wearable technologies such as smart insoles has provided new opportunities to address these challenges through accurate unobtrusive monitoring and analysis of workers' activities and physical parameters. This systematic review aims to analyze the utilization of smart wearable insoles in industrial environments, focusing on their applications, employed analysis methods, and potential future directions.

Unlocking human-robot synergy: The power of intent communication in warehouse robotics.

As autonomous mobile robots (AMR) are introduced into workspace environments shared with people, effective human-robot communication is critical to the prevention of injury while maintaining a high level of productivity. This research presents an empirical study that evaluates four alternative methods for communicating between an autonomous mobile robot and a human at a warehouse intersection. The results demonstrate that using an intent communication system for human-AMR interaction improves objective measures of productivity (task time) and subjective metrics of trust and comfort.

Fall Risk Assessment in Stroke Survivors: A Machine Learning Model Using Detailed Motion Data from Common Clinical Tests and Motor-Cognitive Dual-Tasking.

Background: Falls are common and dangerous for stroke survivors. Current fall risk assessment methods rely on subjective scales. Objective sensor-based methods could improve prediction accuracy.

Mentoring as an Appropriate Strategy for Medical Faculty Member Development in Higher Education: A Systematic Review.

Introduction: Human resources development, especially faculty members who play a substantial role in education, is of great importance and can lead to enhanced competence and participation of employees in university affairs. Mentoring is one of the programs that have attracted the attention of activists in this field today. This review aims to integrate the evidence about the goals, methods, implementation steps, and consequences of the mentoring methods for faculty member development in higher education institutions.

Recovering from Laboratory-Induced slips and trips causes high levels of lumbar muscle activity and spine loading.

Slips, trips, and falls are some of the most substantial and prevalent causes of occupational injuries and fatalities, and these events may contribute to low-back problems. We quantified lumbar kinematics (i.e.

A Systematic Review of Fall Risk Factors in Stroke Survivors: Towards Improved Assessment Platforms and Protocols.

To prevent falling, a common incident with debilitating health consequences among stroke survivors, it is important to identify significant fall risk factors (FRFs) towards developing and implementing predictive and preventive strategies and guidelines. This review provides a systematic approach for identifying the relevant FRFs and shedding light on future directions of research. A systematic search was conducted in 5 popular research databases.

A Systematic Review on Evaluation Strategies for Field Assessment of Upper-Body Industrial Exoskeletons: Current Practices and Future Trends.

With rising manual work demands, physical assistance at the workplace is crucial, wherein the use of industrial exoskeletons (i-EXOs) could be advantageous. However, outcomes of numerous laboratory studies may not be directly translated to field environments. To explore this discrepancy, we conducted a systematic review including 31 studies to identify and compare the approaches, techniques, and outcomes within field assessments of shoulder and back support i-EXOs.

Why multi-tier surgical instrument table matters? An ergonomic analysis from mento-physical demand perspectives.

Using traditional back tables (BT) in operating rooms (OR) can lead to high physical/cognitive demand on nurses due to repetitive manual material handling activities. A multi-tier table (MTT) has been developed to relieve such stressors by providing extra working surfaces to avoid stacking the instrument trays and facilitate access to surgical tools. In this study, sixteen participants performed lifting/lowering and instrument findings tasks on each table, where kinematics, kinetics, subjective, and performance-related measures were recorded.

Kinematic Analysis of 360° Turning in Stroke Survivors Using Wearable Motion Sensors.

Background: A stroke often bequeaths surviving patients with impaired neuromusculoskeletal systems subjecting them to increased risk of injury (e.g., due to falls) even during activities of daily living.

Kinematic Assessment of Turning and Walking Tasks Among Stroke Survivors by Employing Wearable Sensors and Pressure Platform.

Stroke survivors often experience reduced movement capabilities due to alterations in their neuromusculoskeletal systems. Modern sensor technologies and motion analyses can facilitate the determination of these changes. Our work aims to assess the potential of using wearable motion sensors to analyze the movement of stroke survivors and identifying the affected functions.

Biomechanical modeling of spinal ligaments: finite element analysis of L4-L5 spinal segment.

The complex mechanical structure of spine is usually simplified in finite element (FE) modes. In this study, different 3D models of L4-L5 spinal segment distinguished by their ligament modelling were developed (1D truss, 2D shell and 3D space truss elements). All models could be considered validated with respect to range of motion and intradiscal pressure, although their ligament stresses/forces were substantially different.

Smartphone-based human fatigue level detection using machine learning approaches.

Human muscle fatigue is the main result of diminishing muscle capability, leading to reduced performance and increased risk of falls and injury. This study provides a classification model to identify the human fatigue level based on the motion signals collected by a smartphone. 24 participants were recruited and performed the fatiguing exercise (i.

Using a Motion Sensor to Categorize Nonspecific Low Back Pain Patients: A Machine Learning Approach.

Nonspecific low back pain (NSLBP) constitutes a critical health challenge that impacts millions of people worldwide with devastating health and socioeconomic consequences. In today's clinical settings, practitioners continue to follow conventional guidelines to categorize NSLBP patients based on subjective approaches, such as the STarT Back Screening Tool (SBST). This study aimed to develop a sensor-based machine learning model to classify NSLBP patients into different subgroups according to quantitative kinematic data, i.

Processing of Near Real Time Land Surface Temperature and Its Application in Forecasting Forest Fire Danger Conditions.

Near real time (NRT) remote sensing derived land surface temperature (Ts) data has an utmost importance in various applications of natural hazards and disasters. Space-based instrument MODIS (moderate resolution imaging spectroradiometer) acquired NRT data products of Ts are made available for the users by LANCE (Land, Atmosphere Near real-time Capability) for Earth Observing System (EOS) of NASA (National Aeronautics and Space Administration) free of cost. Such Ts products are swath data with 5 min temporal increments of satellite acquisition, and the average latency is 60-125 min to be available in public domain.

Relationship between big five personality factors, problem solving and medical errors.

Background: Human behavior is recognized as the main factor in the occurrence of accidents (70-90 percent), with human personality and problem solving ability as two related factors in the occurrence of medical errors (annually 42.7 million in the world). The objectives of this study were to investigate the relationship between personality factors, problem solving ability and medical errors.

A novel approach to spinal 3-D kinematic assessment using inertial sensors: Towards effective quantitative evaluation of low back pain in clinical settings.

This paper presents a novel approach for evaluating LBP in various settings. The proposed system uses cost-effective inertial sensors, in conjunction with pattern recognition techniques, for identifying sensitive classifiers towards discriminate identification of LB patients. 24 healthy individuals and 28 low back pain patients performed trunk motion tasks in five different directions for validation.

A regenerative approach towards recovering the mechanical properties of degenerated intervertebral discs: Genipin and platelet-rich plasma therapies.

Degenerative disc disease, associated with discrete structural changes in the peripheral annulus and vertebral endplate, is one of the most common pathological triggers of acute and chronic low back pain, significantly depreciating an individual's quality of life and instigating huge socioeconomic costs. Novel emerging therapeutic techniques are hence of great interest to both research and clinical communities alike. Exogenous crosslinking, such as Genipin, and platelet-rich plasma therapies have been recently demonstrated encouraging results for the repair and regeneration of degenerated discs, but there remains a knowledge gap regarding the quantitative degree of effectiveness and particular influence on the mechanical properties of the disc.

A model for flexi-bar to evaluate intervertebral disc and muscle forces in exercises.

This study developed and validated a lumped parameter model for the FLEXI-BAR, a popular training instrument that provides vibration stimulation. The model which can be used in conjunction with musculoskeletal-modeling software for quantitative biomechanical analyses, consists of 3 rigid segments, 2 torsional springs, and 2 torsional dashpots. Two different sets of experiments were conducted to determine the model's key parameters including the stiffness of the springs and the damping ratio of the dashpots.