Diagnostics of Articular Cartilage Damage Based on Generated Acoustic Signals Using ANN-Part I: Femoral-Tibial Joint

The Development and Implementation of Innovative Blind Source Separation Techniques for Real-Time Extraction and Analysis of Fetal and Maternal Electrocardiogram Signals

This article presents an innovative approach to analyzing and extracting electrocardiogram (ECG) signals from the abdomen and thorax of pregnant women, with the primary goal of isolating fetal ECG (fECG) and maternal ECG (mECG) signals. To resolve the difficulties related to the low amplitude of the fECG, various noise sources during signal acquisition, and the overlapping of R waves, we developed a new method for extracting ECG signals using blind source separation techniques. This method is based on independent component analysis algorithms to detect and accurately extract fECG and mECG signals from abdomen and thorax data. To validate our approach, we carried out experiments using a real and reliable database for the evaluation of fECG extraction algorithms. Moreover, to demonstrate real-time applicability, we implemented our method in an embedded card linked to electronic modules that measure blood oxygen saturation (SpO2) and body temperature, as well as the transmission of data to a web server. This enables us to present all information related to the fetus and its mother in a mobile application to assist doctors in diagnosing the fetus's condition. Our results demonstrate the effectiveness of our approach in isolating fECG and mECG signals under difficult conditions and also calculating different heart rates (fBPM and mBPM), which offers promising prospects for improving fetal monitoring and maternal healthcare during pregnancy.

Cemented vs. Cementless Fixation in Primary Knee Replacement: A Narrative Review

Knee osteoarthritis (OA) is one of the leading causes of disability around the globe. Osteoarthritis is mainly considered a disease affecting the elderly. However, more and more studies show that sports overuse, obesity, or congenital disorders can initiate a pathologic cascade that leads to OA changes in the younger population. Nevertheless, OA mostly affects the elderly, and with increasing life expectancy, the disease will develop in more and more individuals. To date, the golden standard in the treatment of the end-stage of the disease is total joint replacement (TJR), which restores painless knee motion and function. One of the weakest elements in TJR is its bonding with the bone, which can be achieved by bonding material, such as poly methyl-methacrylate (PMMA), or by cementless fixation supported by bone ingrowth onto the endoprosthesis surface. Each technique has its advantages; however, the most important factor is the revision rate and survivor time. In the past, numerous articles were published regarding TJR revision rate, but no consensus has been established yet. In this review, we focused on a comparison of cemented and cementless total knee replacement surgeries. We introduced PICO rules, including population, intervention, comparison and outcomes of TJR in a PubMed search. We identified 783 articles published between 2010 and 2023, out of which we included 14 in our review. Our review reveals that there is no universally prescribed approach to fixate knee prostheses. The determination of the most suitable method necessitates an individualized decision-making process involving the active participation and informed consent of each patient.

Descriptive Analysis of Trauma Admission Trends before and during the COVID-19 Pandemic

INTRODUCTION

Traumatic injuries are a significant global health concern, with profound medical and socioeconomic impacts. This study explores the patterns of trauma-related hospitalizations in the Lublin Province of Poland, with a particular focus on the periods before and during the COVID-19 pandemic.

AIM OF THE STUDY

The primary aim of this research was to assess the trends in trauma admissions, the average length of hospital stays, and mortality rates associated with different types of injuries, comparing urban and rural settings over two distinct time periods: 2018-2019 and 2020-2021.

METHODS

This descriptive study analyzed trauma admission data from 35 hospitals in the Lublin Province, as recorded in the National General Hospital Morbidity Study (NGHMS). Patients were classified based on the International Classification of Diseases Revision 10 (ICD-10) codes. The data were compared for two periods: an 11-week span during the initial COVID-19 lockdown in 2020 and the equivalent period in 2019.

RESULTS

The study found a decrease in overall trauma admissions during the pandemic years (11,394 in 2020-2021 compared to 17,773 in 2018-2019). Notably, the average length of hospitalization increased during the pandemic, especially in rural areas (from 3.5 days in 2018-2019 to 5.5 days in 2020-2021 for head injuries). Male patients predominantly suffered from trauma, with a notable rise in female admissions for abdominal injuries during the pandemic. The maximal hospitalization days were higher in rural areas for head and neck injuries during the pandemic.

CONCLUSIONS

The study highlights significant disparities in trauma care between urban and rural areas and between the pre-pandemic and pandemic periods. It underscores the need for healthcare systems to adapt to changing circumstances, particularly in rural settings, and calls for targeted strategies to address the specific challenges faced in trauma care during public health crises.

The Influence of Weather Conditions on the Diurnal Variation in Range of Motion in Older Adults with Knee Osteoarthritis

(1) Background: This study investigated the relationship between weather conditions, diurnal patterns, and total knee range of motion (ROM), as well as the severity of symptoms (pain and stiffness) in older adults with knee osteoarthritis. (2) Methods: An exploratory longitudinal study was conducted on 28 older adults with knee osteoarthritis (mean age 71.86 ± 4.49 years; 46.4% men, 53.6% women). We used as assessment tools the Visual Analog Scales (VAS) for self-reported local knee pain and stiffness, and goniometry for ROM. Measurements were taken twice, six months apart, in winter and summer, in the morning and evening of each selected day. Recorded weather factors comprised temperature, relative humidity, barometric pressure, and maximum wind speed. (3) Results: The study revealed significant effects of season and time of day on pain and stiffness, respectively (p < 0.001). Additionally, a significant interaction between season and time influenced total knee ROM (p < 0.001). Moreover, there was a statistically significant relationship between time and total knee ROM (p < 0.001). (4) Conclusions: This research underscores the complex link between seasonal fluctuations and daily variations in some symptomatic and functional aspects of knee osteoarthritis in older adults.

Impact of the Body Composition on Knee Osteoarthritis Assessed Using Bioimpedance Analysis

Osteoarthritis (OA) ranks among the most prevalent inflammatory diseases affecting the musculoskeletal system and is a leading cause of disability globally, impacting approximately 250 million individuals. This study aimed to assess the relationship between the severity of knee osteoarthritis (KOA) and body composition in postmenopausal women using bioimpedance analysis (BIA). The study included 58 postmenopausal females who were candidates for total knee arthroplasty. The control group consisted of 25 postmenopausal individuals with no degenerative knee joint changes. The anthropometric analysis encompassed the body mass index (BMI), mid-arm and mid-thigh circumferences (MAC and MTC), and triceps skinfold thickness (TSF). Functional performance was evaluated using the 30 s sit-to-stand test. During the BIA test, electrical parameters such as membrane potential, electrical resistance, capacitive reactance, impedance, and phase angle were measured. Additionally, body composition parameters, including Total Body Water (TBW), Extracellular Water (ECW), Intracellular Water (ICW), Body Cellular Mass (BCM), Extracellular Mass (ECM), Fat-Free Mass (FFM), and Fat Mass (FM), were examined. The study did not find any statistically significant differences in the electrical parameters between the control (0-1 grade on the K-L scale) and study groups (3-4 grade on the K-L scale). However, statistically significant differences were observed in BMI, fat mass (FM), arm circumference, triceps skinfold thickness, and sit-to-stand test results between the analyzed groups. In conclusion, the association between overweight and obesity with KOA in postmenopausal women appears to be primarily related to the level of adipose tissue and its metabolic activity.

Intraoperative Acoustic Evaluation of Living Human Knee Cartilage-Comparison with Respect to Cartilage Degeneration and Aging

OBJECTIVE

The objective of the study was to evaluate the mechanical properties of living human knee cartilage using our ultrasonic device, and to compare the measurements with respect to cartilage degeneration and aging.

DESIGN

A total of 95 knees which had undergone arthroscopic knee surgery, from 88 patients, were included in the study, with informed consent. All procedures were reviewed and approved by the ethical committee of our hospital. In the study group, there were 41 men, 47 women, 39 right knees, and 56 left knees. The conditions primarily included knee osteoarthritis and anterior cruciate ligament rupture. The mean operative age was 44.1 years old (range = 10-83). We compared mechanical properties of the knee cartilage with respect to aging and gender, in comparison with normal cartilage. A P value of <0.05 represented statistical significance.

RESULTS

In the context of the International Cartilage Repair Society (ICRS) classification of cartilage degeneration (grade 0-3), the signal intensity in grade 0 was significantly larger than that in grade 1, 2, or 3. The thickness in grade 0 was significantly higher than that in grade 1, 2, or 3. Normal cartilage in older women had the lowest signal intensity and the least cartilage thickness among all the groups.

CONCLUSION

The ultrasonic system we developed was able to detect early degenerative changes in living cartilage in knees. The lowest signal intensity and least cartilage thickness in normal cartilage among older women were correlated to a large prevalence of knee osteoarthritis in women.

LEVEL OF EVIDENCE

Level IV, case series.

Evaluating Changes in Trauma Epidemiology during the COVID-19 Lockdown: Insights and Implications for Public Health and Disaster Preparedness

The COVID-19 pandemic demanded changes in healthcare systems worldwide. The lockdown brought about difficulties in healthcare access. However, trauma still required further attention considering its modifications. The presented study aims to investigate the variances in epidemiological patterns of trauma during the lockdown and the previous year, with a view to better understand the modifications in healthcare provision. The authors analyzed data from the first lockdown in 2020 (12 March-30 May) and the same period in 2019 from 35 hospitals in Lublin Province. A total of 10,806 patients in 2019 and 5212 patients in 2020 were included in the research. The uncovered changes adhered to the total admissions and mortality rate, the frequency of injuries in particular body regions, and injury mechanisms. The lockdown period resulted in a reduction in trauma, requiring an altered approach to healthcare provision. Our research indicates that the altered approach facilitated during such periods is essential for delivering tailored help to trauma patients.

Crashworthiness Analysis of Thin-Walled Square Columns with a Hole Trigger

Thin-walled structures dynamically loaded with an axial force are the subject of this study. The structures work as passive energy absorbers by progressive harmonic crushing. The absorbers were made of AA-6063-T6 aluminum alloy and subjected to both numerical and experimental tests. Experimental tests were performed on an INSTRON 9350 HES bench, while numerical analyses were performed using Abaqus software. The energy absorbers tested had crush initiators in the form of drilled holes. The variable parameters were the number of holes and their diameter. The holes were located in a line 30 mm away from the base. This study shows a significant effect of the hole diameter on the values of the stroke efficiency indicator and mean crushing force.

Knee Osteoarthritis: Epidemiology, Pathogenesis, and Mesenchymal Stem Cells: What Else Is New? An Update

Osteoarthritis (OA) is a chronic disease and the most common orthopedic disorder. A vast majority of the social OA burden is related to hips and knees. The prevalence of knee OA varied across studies and such differences are reflected by the heterogeneity of data reported by studies conducted worldwide. A complete understanding of the pathogenetic mechanisms underlying this pathology is essential. The OA inflammatory process starts in the synovial membrane with the activation of the immune system, involving both humoral and cellular mediators. A crucial role in this process is played by the so-called “damage-associated molecular patterns” (DAMPs). Mesenchymal stem cells (MSCs) may be a promising option among all possible therapeutic options. However, many issues are still debated, such as the best cell source, their nature, and the right amount. Further studies are needed to clarify the remaining doubts. This review provides an overview of the most recent and relevant data on the molecular mechanism of cartilage damage in knee OA, including current therapeutic approaches in regenerative medicine.

Recent Advancements in Sensor Technologies for Healthcare and Biomedical Applications

Biomedical sensors are the key units of medical and healthcare systems [...].

Assessment of the Impact of Physical Activity on the Musculoskeletal System in Early Degenerative Knee Joint Lesions in an Animal Model

Osteoarthritis (OA) is one of the most prevalent diseases of the osteoarticular system. Progressive destruction of joints is accompanied by development of pathological changes in the muscle tissue, i.e., weakening, atrophy, and remodelling (sarcopenia). The aim of the present study is to assess the impact of physical activity on the musculoskeletal system in an animal model of early degenerative lesions in the knee joint. The study involved 30 male Wistar rats. The animals were allocated to three subgroups of 10 animals each. Each animal from the three subgroups received sodium iodoacetate by injection into the patellar ligament of the right knee joint, whereas saline was administered through the patellar ligament in the left knee joint. The rats in the first group were stimulated to exercise on a treadmill. The animals in the second group were allowed to lead a natural lifestyle (no treadmill stimulation). In the third group, all parts of the right hind limb muscle were injected with Clostridium botulinum toxin type A. The study demonstrated that, compared to the active rats, bone density in the immobilised rats decreased, as indicated by the densitometric assessment of the whole body and the examination of rats' hind limbs and knee joints alone. This clearly evidenced the impact of physical activity on bone mineralisation. The weight of both fat and muscle tissues in the physically inactive rats was reduced. Additionally, the adipose tissue had higher weight in the entire right hind limbs, where monoiodoacetic acid was administered to the knee joint. The animal model clearly showed the importance of physical activity in the early stages of OA, as it slows down the process of joint destruction, bone atrophy, and muscle wasting, whereas physical inactivity contributes to progression of generalised changes in the musculoskeletal system.

Artificial-Intelligence-Aided Radiographic Diagnostic of Knee Osteoarthritis Leads to a Higher Association of Clinical Findings with Diagnostic Ratings

BACKGROUND

Radiographic knee osteoarthritis (OA) severity and clinical severity are often dissociated. Artificial intelligence (AI) aid was shown to increase inter-rater reliability in radiographic OA diagnosis. Thus, AI-aided radiographic diagnoses were compared against AI-unaided diagnoses with regard to their correlations with clinical severity.

METHODS

Seventy-one DICOMs (m/f = 27:42, mean age: 27.86 ± 6.5) (X-ray format) were used for AI analysis (KOALA software, IB Lab GmbH). Subjects were recruited from a physiotherapy trial (MLKOA). At baseline, each subject received (i) a knee X-ray and (ii) an assessment of five main scores (Tegner Scale (TAS); Knee Injury and Osteoarthritis Outcome Score (KOOS); International Physical Activity Questionnaire; Star Excursion Balance Test; Six-Minute Walk Test). Clinical assessments were repeated three times (weeks 6, 12 and 24). Three physicians analyzed the presented X-rays both with and without AI via KL grading. Analyses of the (i) inter-rater reliability (IRR) and (ii) Spearman's Correlation Test for the overall KL score for each individual rater with clinical score were performed.

RESULTS

We found that AI-aided diagnostic ratings had a higher association with the overall KL score and the KOOS. The amount of improvement due to AI depended on the individual rater.

CONCLUSION

AI-guided systems can improve the ratings of knee radiographs and show a stronger association with clinical severity. These results were shown to be influenced by individual readers. Thus, AI training amongst physicians might need to be increased. KL might be insufficient as a single tool for knee OA diagnosis.

Advanced MR Imaging for Knee Osteoarthritis: A Review on Local and Brain Effects

Knee osteoarthritis is one of the leading causes of chronic disability worldwide and is a significant social and economic burden on healthcare systems; hence it has become essential to develop methods to identify patients at risk for developing knee osteoarthritis at an early stage. Standard morphological MRI sequences are focused mostly on alterations seen in advanced stages of osteoarthritis. However, they possess low sensitivity for early, subtle, and potentially reversible changes of the degenerative process. In this review, we have summarized the state of the art with regard to innovative quantitative MRI techniques that exploit objective and quantifiable biomarkers to identify subtle alterations that occur in early stages of osteoarthritis in knee cartilage before any morphological alteration occurs and to capture potential effects on the brain. These novel MRI imaging tools are believed to have great potential for improving the current standard of care, but further research is needed to address limitations before these compositional techniques can be robustly applied in research and clinical settings.

Repeatability of the Vibroarthrogram in the Temporomandibular Joints

Current research concerning the repeatability of the joint's sounds examination in the temporomandibular joints (TMJ) is inconclusive; thus, the aim of this study was to investigate the repeatability of the specific features of the vibroarthrogram (VAG) in the TMJ using accelerometers. The joint sounds of both TMJs were measured with VAG accelerometers in two groups, study and control, each consisting of 47 participants (n = 94). Two VAG recording sessions consisted of 10 jaw open/close cycles guided by a metronome. The intraclass correlation coefficient (ICC) was calculated for seven VAG signal features. Additionally, a k-nearest-neighbors (KNN) classifier was defined and compared with a state-of-the-art method (joint vibration analysis (JVA) decision tree). ICC indicated excellent (for the integral below 300 Hz feature), good (total integral, integral above 300 Hz, and median frequency features), moderate (integral below to integral above 300 Hz ratio feature) and poor (peak amplitude feature) reliability. The accuracy scores for the KNN classifier (up to 0.81) were higher than those for the JVA decision tree (up to 0.60). The results of this study could open up a new field of research focused on the features of the vibroarthrogram in the context of the TMJ, further improving the diagnosing process.

Analysis of the Effect of Component Ratio Imbalances on Selected Mechanical Properties of Seasoned, Medium Viscosity Bone Cements

The paper presents the results of experimental strength tests of specimens made of two commercially available bone cements subjected to compression, that is a typical variant of load of this material during use in the human body, after it has been used for implantation of prostheses or supplementation of bone defects. One of the factors analysed in detail was the duration of cement seasoning in Ringer's solution that simulates the aggressive environment of the human body and material degradation caused by it. The study also focused on the parameters of quantitative deviation from the recommended proportions of liquid (MMA monomer, accelerator and stabiliser) and powder (PMMA prepolymer and initiator) components, i.e., unintentional inaccuracy of component proportioning at the stage of cement mass preparation. Statistical analysis has shown the influence of these factors on the decrease in compressive strength of the cements studied, which may be of significant importance in operational practice.

Research on Tiny Target Detection Technology of Fabric Defects Based on Improved YOLO

Fabric quality plays a crucial role in modern textile industry processes. How to detect fabric defects quickly and effectively has become the main research goal of researchers. The You Only Look Once (YOLO) series of networks have maintained a dominant position in the field of target detection. However, detecting small-scale objects, such as tiny targets in fabric defects, is still a very challenging task for the YOLOv4 network. To address this challenge, this paper proposed an improved YOLOv4 target detection algorithm: using a combined data augmentation method to expand the dataset and improve the robustness of the algorithm, obtaining the anchors suitable for fabric defect detection by using the k-means algorithm to cluster the ground truth box of the dataset, adding a new prediction layer in yolo_head in order to have a better effect on tiny target detection, integrating a convolutional block attention module into the backbone feature extraction network, and innovatively replacing the CIOU loss function with the CEIOU loss function to achieve accurate classification and localization of defects. Experimental results show that compared with the original YOLOv4 algorithm, the detection accuracy of the improved YOLOv4 algorithm for tiny targets has been greatly increased, the AP value of tiny target detection has increased by 12%, and the overall mean average precision (mAP) has increased by 3%. The prediction results of the proposed algorithm can provide enterprises with more accurate defect positioning, reduce the defect rate of fabric products, and improve their economic effect.

Diagnostics of Articular Cartilage Damage Based on Generated Acoustic Signals Using ANN—Part II: Patellofemoral Joint

Cartilage loss due to osteoarthritis (OA) in the patellofemoral joint provokes pain, stiffness, and restriction of joint motion, which strongly reduces quality of life. Early diagnosis is essential for prolonging painless joint function. Vibroarthrography (VAG) has been proposed in the literature as a safe, noninvasive, and reproducible tool for cartilage evaluation. Until now, however, there have been no strict protocols for VAG acquisition especially in regard to differences between the patellofemoral and tibiofemoral joints. The purpose of this study was to evaluate the proposed examination and acquisition protocol for the patellofemoral joint, as well as to determine the optimal examination protocol to obtain the best diagnostic results. Thirty-four patients scheduled for knee surgery due to cartilage lesions were enrolled in the study and compared with 33 healthy individuals in the control group. VAG acquisition was performed prior to surgery, and cartilage status was evaluated during the surgery as a reference point. Both closed (CKC) and open (OKC) kinetic chains were assessed during VAG. The selection of the optimal signal measures was performed using a neighborhood component analysis (NCA) algorithm. The classification was performed using multilayer perceptron (MLP) and radial basis function (RBF) neural networks. The classification using artificial neural networks was performed for three variants: I. open kinetic chain, II. closed kinetic chain, and III. open and closed kinetic chain. The highest diagnostic accuracy was obtained for variants I and II for the RBF 9-35-2 and MLP 10-16-2 networks, respectively, achieving a classification accuracy of 98.53, a sensitivity of 0.958, and a specificity of 1. For variant III, a diagnostic accuracy of 97.79 was obtained with a sensitivity and specificity of 0.978 for MLP 8-3-2. This indicates a possible simplification of the examination protocol to single kinetic chain analyses.