More than 70% of all knee injuries in soccer occur in non-contact situations. It is known that increased lower limb dynamic knee valgus is associated with such situations. Little has been found out about differences in knee kinematics of the dominant (kicking) and non-dominant (supporting) leg during a single leg landing. A total of 114 male adolescent soccer players (age 14.6 ± 1.1 years) from elite (N = 66) and amateur soccer clubs (N = 48) performed a single leg drop landing down from a box. For each leg, the two-dimensional dynamic knee valgus angle (DKVA) was calculated. Paired t-tests were used to statistically determine significant differences between dominant and non-dominant leg DKVA, and t-tests were calculated between the two performance groups. Statistically significant differences (p < 0.05) were identified for the DKVA between the dominant and non-dominant leg for both amateur and elite players, showing a greater DKVA for the dominant leg. Group differences for the DKVA between amateur and elite players were not found, neither for the dominant, nor for the non-dominant leg. It can be concluded that the non-dominant leg showed more stable dynamics than the dominant leg during unilateral landing regardless of the player’s performance level. This could be due to adaptions to sport-specific requirements. Therefore, it is recommended that programs to prevent knee injuries among soccer players consider the dynamics of each leg individually.

Muscular imbalances of the trunk muscles are held responsible for changes in body posture. At the same time, whole-body electromyostimulation (WB-EMS) has been established as a new training method that enables simultaneous stimulation of many muscle groups. This study was aiming to analyze if a 10 weeks WB-EMS training changes posture-relevant parameters and/or improves isometric strength of the trunk extensors and flexors, and if there are differences based on stimulation at 20 Hz and 85 Hz. Fifty eight untrained adult test persons were divided into three groups (control, CON; training with 20 Hz stimulation, TR20; training with 85 Hz, TR85). Anthropometric parameters, trunk extension and flexion forces and torques, and posture parameters were determined before (n = 58) and after (n = 53: CON: n = 15, TR20: n = 19, TR85: n = 19) a 10 weeks WB-EMS training program (15 applications, 9 exercises). Differences between the groups were calculated for pre- and post-tests using univariate ANOVA and between the test times using repeated (2 × 3) ANOVA. Comparisons of pairs were calculated post hoc based on Fisher (LSD). No differences between the groups were found for the posture parameters. The post hoc analysis of both trunk flexion and trunk extension forces and torques showed a significant difference between the groups TR85 and CON but no difference between the other group pairs. A 10 weeks whole-body electrostimulation training with a stimulation frequency of 85 Hz in contrast to training with a stimulation frequency of 20 Hz improves the trunk muscle strength of an untrained group but does not significantly change posture parameters.

Postural deficits such as hyperlordosis (hollow back) or hyperkyphosis (hunchback) are relevant health issues. Diagnoses depend on the experience of the examiner and are, therefore, often subjective and prone to errors. Machine learning (ML) methods in combination with explainable artificial intelligence (XAI) tools have proven useful for providing an objective, data-based orientation. However, only a few works have considered posture parameters, leaving the potential for more human-friendly XAI interpretations still untouched. Therefore, the present work proposes an objective, data-driven ML system for medical decision support that enables especially human-friendly interpretations using counterfactual explanations (CFs). The posture data for 1151 subjects were recorded by means of stereophotogrammetry. An expert-based classification of the subjects regarding the presence of hyperlordosis or hyperkyphosis was initially performed. Using a Gaussian progress classifier, the models were trained and interpreted using CFs. The label errors were flagged and re-evaluated using confident learning. Very good classification performances for both hyperlordosis and hyperkyphosis were found, whereby the re-evaluation and correction of the test labels led to a significant improvement (M_PRAUC = 0.97). A statistical evaluation showed that the CFs seemed to be plausible, in general. In the context of personalized medicine, the present study’s approach could be of importance for reducing diagnostic errors and thereby improving the individual adaptation of therapeutic measures. Likewise, it could be a basis for the development of apps for preventive posture assessment.

Reliability of posturography is essential for the identification of intervention effects in any setting (e.g., sport, rehabilitation). The purpose was to establish the intraobserver reliability of a posturographic method in asymptomatic subjects (n = 30). Intraclass correlation coefficients (relative reliability) for every parameter and all test positions (ALL_mean) ranged from 0.78 (95% CI: 0.53–0.90) to 0.95 (95% CI: 0.89–0.97). Absolute reliability, quantified by using the coefficient of variation, ranged between 3.5 and 19.8. Reliability of single test positions is much lower. The posturographic system showed good relative and satisfactory absolute intraobserver reliability for ALL_mean.

Intensity regulation during whole-body electromyostimulation (WB-EMS) training is mostly controlled by subjective scales such as CR-10 Borg scale. To determine objective training intensities derived from a maximum as it is used in conventional strength training using the one-repetition-maximum (1-RM), a comparable maximum in WB-EMS is necessary. Therefore, the aim of this study was to examine, if there is an individual maximum intensity tolerance plateau after multiple consecutive EMS application sessions. A total of 52 subjects (24.1 ± 3.2 years; 76.8 ± 11.1 kg; 1.77 ± 0.09 m) participated in the longitudinal, observational study (38 males, 14 females). Each participant carried out four consecutive maximal EMS applications (T1–T4) separated by 1 week. All muscle groups were stimulated successively until their individual maximum and combined to a whole-body stimulation index to carry out a possible statement for the development of the maximum intensity tolerance of the whole body. There was a significant main effect between the measurement times for all participants (p < 0.001; 𝜂² = 0.39) as well as gender specific for males (p = 0.001; 𝜂² = 0.18) and females (p < 0.001; 𝜂² = 0.57). There were no interaction effects of gender × measurement time (p = 0.394). The maximum intensity tolerance increased significantly from T1 to T2 (p = 0.001) and T2 to T3 (p < 0.001). There was no significant difference between T3 and T4 (p = 1.0). These results indicate that there is an adjustment of the individual maximum intensity tolerance to a WB-EMS training after three consecutive tests. Therefore, there is a need of several habituation units comparable to the identification of the individual 1-RM in conventional strength training. Further research should focus on an objective intensity-specific regulation of the WB-EMS based on the individual maximum intensity tolerance to characterize different training areas and therefore generate specific adaptations to a WB-EMS training compared to conventional strength training methods.

Study aim: To find out, without relying on gait-specific assumptions or prior knowledge, which parameters are most important for the description of asymmetrical gait in patients after total hip arthroplasty (THA). Material and methods: The gait of 22 patients after THA was recorded using an optical motion capture system. The waveform data of the marker positions, velocities, and accelerations, as well as joint and segment angles, were used as initial features. The random forest (RF) and minimum-redundancy maximum-relevance (mRMR) algorithms were chosen for feature selection. The results were compared with those obtained from the use of different dimensionality reduction methods. Results: Hip movement in the sagittal plane, knee kinematics in the frontal and sagittal planes, marker position data of the anterior and posterior superior iliac spine, and acceleration data for markers placed at the proximal end of the fibula are highly important for classification (accuracy: 91.09%). With feature selection, better results were obtained compared to dimensionality reduction. Conclusion: The proposed approaches can be used to identify and individually address abnormal gait patterns during the rehabilitation process via waveform data. The results indicate that position and acceleration data also provide significant information for this task.