This study aims to understand the impact of backpack carriage, a regular activity for many, on back muscles and joint mobility during walking so that clinicians can develop strategies or products to ensure individuals’ safety and well-being. Surface electromyography (EMG) and XSENS Awinda motion capture systems were used to analyze the effects of carrying a backpack (12% of body weight) on erector spinae and multifidus muscles, as well as spinal, hip, knee, and ankle joints. Subjects walked at 4 km/h on flat and inclined surfaces. Paired t-tests compared backpack loads to baseline measurements. Carrying a backpack reduced activation levels in erector spinae and multifidus muscles and restricted spinal joint range of motion (axial and lateral bending, $$\varvec{p<0.05}$$ p < 0.05 ). Hip joint rotation increased ( $$\varvec{p<0.05}$$ p < 0.05 ). Moderate to strong correlations were observed between muscle activity and spinal joint ROM, notably with left erector spinae and L5-S1 lateral bending ( $$\varvec{r=0.723}, \varvec{p<0.001}$$ r = 0.723 , p < 0.001 ). Backpack carriage decreases back muscle activation and alters the joint range of motion. Asymmetric correlations show that the subjects adapt muscle activity and gait patterns asymmetrically to manage external loads. Graphical

Objective : When there are multiple tests, the receiver operating characteristic (ROC) curve analysis does not answer the question of how the individual tests can be combined in medicine. Approach : In this study, 2D-ROC analysis is considered to calculate the correct classification rate (CCR) by using two independent test results. To obtain the best combination of paired tests, results were combined as ‘BOTH’, ‘ANY’ or ‘AVERAGE’ for the final 2D-ROC decision. Main results : When the combined model was ‘AVERAGE’, the CCR was better than individual test results. At every correlation level, the 2D-ROC was shown to have a better CCR compared to individual tests, and when the correlations were lower, the CCR of 2D-ROC was even better. For uncorrelated test pairs ( r = 0, p < 0.0001), in healthy and diseased populations with normal distributions, the improvement in CCR compared to individual tests were from 2.6% to 6.5%, and leptokurtic distribution of diseased population ( k = 2, p < 0.0001) was better by 1.3% to 5.3%. As a clinical application, multifrequency bioelectric impedance (BI) spectroscopy characteristic frequency ( f _c ) and body mass index (BMI) measurements from 53 post-menopausal women were used in finding the 2D-ROC decision matrix to determine the hip area bone mineral deficiency. Using the ‘AVERAGE’ combination model, the CCR of 2D-ROC was 1.6% better than BMI and 14.8% better than fc alone. In the second clinical application of prediction of metabolic syndrome (MeS), parameters such as BMI, waist circumference, abnormal fasting blood sugar, triglyceride and high-density lipoprotein cholesterol were measured from 5533 subjects and combined to assess individual and paired success rates. Using the ‘AVERAGE’ combination model, the CCR of pairs were up to 6.1% better compared to using each parameter alone. Significance : Although the use of a simple ‘AVERAGE’ function was promising, the formulation for combining paired test results could be extended to include the deviations from ideal by weighted averaging of individual tests or by adding other parameters like their kurtosis or disease prevalence into the formulation.

This study utilizes cold water consumption as a method of vagus nerve stimulation, investigating how body mass index (BMI) and repeated stimulation affect heart rate variability (HRV) in both time and frequency domains. HRV was measured in 18 subjects (mean age 21.3 ± 1.6 years) over 90 minutes, divided into three equal phases: resting (baseline), first stimulation (FSP), and second stimulation (SSP). Fourier and Short-Time Fourier Transform (STFT) analyses were used to extract the static and time-varying frequency components of HRV. For the normal body mass index (BMI) group, stimulation resulted in statistically significant changes in frequency band power densities compared to their baseline measurements (p

Unilateral handbag carriage is a common practice in daily life, which imposes asymmetric demands on the trunk. This study examined the resulting kinematic and muscular adaptations during walking in 22 healthy male adults who carried a unilateral 5 kg handbag. Principal component analysis (PCA) was used to analyze spine–hip kinematics and paraspinal EMG, and its robustness was confirmed through component stability and sensitivity analyses. Load carriage significantly altered both kinematics (Pillai's trace = 0.978, p < 0.001) and muscular activations (Pillai's trace = 0.745, p < 0.001). Six kinematic and two muscular principal components (PC) explained 95% of the variance. Kinematic adaptations to load were driven by axial rotation at L3–L4 (31.0% contribution), lateral bending at T8–T9 (36.5% contribution), and flexion/extension at L3–L4 (73.9%), particularly in PCs 2, 4, and 5. Muscular changes were dominated by increased activation in the longissimus (d = 1.493, p < 0.001) and iliocostalis (d = 0.663, p = 0.02) on the side contralateral to the carried bag, and reflected in PCs 1 and 2. Complementary univariate analyses confirmed reduced thoracolumbar mobility and elevated contralateral paraspinal activation ( adjusted p < 0.05). Together, these findings demonstrate an integrated compensatory strategy adjustment under asymmetric load. The robustness of the methodology was confirmed via PC jackknife and bootstrap analyses; however, the findings are based on healthy young male participants under a fixed 5 kg load, acknowledging limited generalizability.