Chronic stress overactivates the sympathetic nervous system, which alters the body, mind, and behavior. Purpose Stress can indeed be employed to preserve homeostasis when there is a physical or mental imbalance brought on by damaging stimuli. Currently, there isn't a standard reference point for quantifying stress. The purpose of this meta-analysis is to assess studies that support the use of heart rate variability (HRV) as an indicator of stress. Methods and Materials: Studies concerning HRV that have been published in bibliographic database from 2013 to 2023 were firstly selected. A total of 181 articles were found, 69 in Elsevier, 51 in Google Scholar, 38 PubMed, and 23 in other databases. The criteria selected were human study, HRV reactivity and the HRV as an objective indicator of psychological stress. Only human study was restrained. Finally, ten publications that fit criteria were found. Results: Majority of research selected found that HRV components changed in response to stress brought on by diverse techniques. The most often cited component associated with variance in HRV variables was a drop in the high-frequency band and an increase in the low-frequency band, both of which are markers of diminished parasympathetic activity. HRV may be related to cortical areas that are engaged in evaluating stressful situations, according to neuroimaging research. Conclusion: The findings support the use of HRV for the purpose of evaluating stress and mental health objectively, and neurobiological data suggests that HRV is impacted by stress reactions.

The measure of cardiac variability (HRV) is considered an accurate diagnostic method to identify autonomic dysfunction. The heart rate influences the pulse. Therefore, pulse rate variability (PRV), like HRV, precisely indicates autonomic nervous system tone. The research investigates the correlation between HRV for the ECG signal and PRV in a cardiac patient. Method and Materials: 53 electrocardiogram (ECG) and photoplethysmogram (PPG) signals for 8 minutes from the PhysioNet BIDMC PPG and Respiration Dataset were used. Afterward, the PRV from PPG and the R-R interval calculated independently using Acqknowledge software were used to estimate the ECG and get HRV characteristics. Results: According to the results, there was a strong correlation between the R-R interval for PRV (694.49 ± 112.98ms) and HRV (695.60 ± 112.97ms) (r=0.99). For all linear parameters for both domains, frequency and time of HRV and PRV, there was a significant positive correlation: HFnu (r =0.99), HF Power (r =1), LFnu (r = 0.99), LF Power (r = 1), RMSSD (r = 0.99), SDNN (r = 0.99), NN50 (r = 0.99), and pNN50 (r =0.99). The Bland & Altman plot demonstrated a high level of agreement among approaches for all parameters. Conclusion: According to the finding, which showed a high level of agreement because it provides values similar to PRV and HRV for all parameters, the idea of PRV rather than HRV can be used to assess sympathovagal regulation in a broad community-based investigation alongside HRV under various clinical circumstances.

Three-dimensional (3D) printing offers new opportunities in surgical planning and medical education, yet high costs and technological complexity often limit its widespread use, especially in low-resource settings. This study presents a personalized, cost-effective, and anatomically accurate liver model designed using open-source tools and affordable 3D-printing techniques. Segmentation of hepatic CT images was performed in 3D Slicer using a region-growing method, and the resulting models were optimized and exported as STL files. The external mold was printed with Fused Deposition Modeling (FDM) using PLA+, while internal structures such as vessels and tumors were fabricated via Liquid Crystal Display (LCD) printing using PLA Pro resin. The final assembly was cast in food-grade gelatin to mimic liver tissue texture. The complete model was produced for under USD 50, with an average total production time of under 128 h. An exploratory pedagogical evaluation with five medical trainees yielded high Likert scores for anatomical understanding (4.6), spatial awareness (4.4), planning confidence (4.2), and realism (4.4). This model demonstrated utility in preoperative discussions and training simulations. The proposed workflow enables the fabrication of low-cost, realistic hepatic phantoms suitable for education and surgical rehearsal, promoting the integration of 3D printing into everyday clinical practice.

Background: Heart rate variability (HRV), generated from an electrocardiogram (ECG), can be used to evaluate the autonomic nervous system (ANS). Heart rate changes during different physical activities are due to changing involuntary regulation. Objective: The main aim of the current study is to explore the ANS by analyzing linear HRV parameters, so that clinicians can preliminarily explore ANS function using ECG analysis with their patients. Patients and methods: A total of 15 student volunteers were recorded. Data was collected for 5 minutes for each supine and standing position. The R-peak obtained from an ECG is used to assess the RR-peak, which is also required for HRV analysis. Linear HRV parameters with different time-domain indices and frequency-domain indices are interpreted in 2 body positions. Results: We discovered that the RR interval is longer in the supine position than in the standing position (952.8±181.6 vs. 771.9±164, respectively; P<0.05), and that in comparison to supine position, when standing as opposed to when lying down, the heart rate is higher (81.7±10.2 vs. 65.8±9.1, respectively; P<0.05), where the body is more relaxed. This affects ANS, and stress index values, which are low before increasing in the standing position, starting in the supine position (5.7±2.4 vs. 9.5±2.7, respectively; P<0.05). Conclusion: We conclude that there is a relationship between HRV and the sympathetic system in different positions, where when moving from supine to standing, the values of HRV changes (increases) and, therefore, the stress index changes (increase) and, from this, we note the change (value increase) in ANS.

Complex liver resections related to hepatic tumors represent a major surgical challenge that requires precise preoperative planning supported by reliable three-dimensional (3D) anatomical models. In this context, accurate volumetric segmentation of the liver is a critical prerequisite to ensure the fidelity of printed models and to optimize surgical decision-making. This study compares different segmentation techniques integrated into open-source software to identify the most suitable approach for clinical application in resource-limited settings. Three semi-automatic methods, region growing, thresholding, and contour interpolation, were tested using the 3D Slicer platform and compared with a proprietary automatic method (Hepatic VCAR, GE Healthcare) and a manual segmentation reference, considered the gold standard. Ten anonymized abdominal CT volumes from the Medical Segmentation Decathlon dataset, encompassing various hepatic pathologies, were used to assess and compare the performance of each technique. Evaluation metrics included the Dice similarity coefficient (Dice), Hausdorff distance (HD), root mean square error (RMS), standard deviation (SD), and colorimetric surface discrepancy maps, enabling both quantitative and qualitative analysis of segmentation accuracy. Among the tested methods, the semi-automatic region growing approach demonstrated the highest agreement with manual segmentation (Dice = 0.935 ± 0.013; HD = 4.32 ± 0.48 mm), surpassing both other semi-automatic techniques and the automatic proprietary method. These results suggest that the region growing method implemented in 3D Slicer offers a reliable, accurate, and reproducible workflow for generating 3D liver models, particularly in surgical environments with limited access to advanced commercial solutions. The proposed methodology can potentially improve surgical planning, enhance training through realistic patient-specific models, and facilitate broader adoption of 3D printing in hepatobiliary surgery worldwide.