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Whole-body electromyostimulation (WB-EMS) is an extension of the EMS application known in physical therapy. In WB-EMS, body composition and skinfold thickness seem to play a decisive role in influencing the Ohmic resistance and therefore the maximum intensity tolerance. That is why the therapeutic success of (WB-)EMS may depend on individual anatomical parameters. The aim of the study was to find out whether gender, skinfold thickness and parameters of body composition have an influence on the maximum intensity tolerance in WB-EMS. [Participants and Methods] Fifty-two participants were included in the study. Body composition (body impedance, body fat, fat mass, fat-free mass) and skinfold thicknesses were measured and set into relation to the maximum intensity tolerance. [Results] No relationship between the different anthropometric parameters and the maximum intensity tolerance was detected for both genders. Considering the individual muscle groups, no similarities were found in the results. [Conclusion] Body composition or skinfold thickness do not seem to have any influence on the maximum intensity tolerance in WB-EMS training. For the application in physiotherapy this means that a dosage of the electrical voltage within the scope of a (WB-) EMS application is only possible via the subjective feedback (BORG Scale).
3D joint kinematics can provide important information about the quality of movements. Optical motion capture systems (OMC) are considered the gold standard in motion analysis. However, in recent years, inertial measurement units (IMU) have become a promising alternative. The aim of this study was to validate IMU-based 3D joint kinematics of the lower extremities during different movements. Twenty-eight healthy subjects participated in this study. They performed bilateral squats (SQ), single-leg squats (SLS) and countermovement jumps (CMJ). The IMU kinematics was calculated using a recently-described sensor-fusion algorithm. A marker based OMC system served as a reference. Only the technical error based on algorithm performance was considered, incorporating OMC data for the calibration, initialization, and a biomechanical model. To evaluate the validity of IMU-based 3D joint kinematics, root mean squared error (RMSE), range of motion error (ROME), Bland-Altman (BA) analysis as well as the coefficient of multiple correlation (CMC) were calculated. The evaluation was twofold. First, the IMU data was compared to OMC data based on marker clusters; and, second based on skin markers attached to anatomical landmarks. The first evaluation revealed means for RMSE and ROME for all joints and tasks below 3°. The more dynamic task, CMJ, revealed error measures approximately 1° higher than the remaining tasks. Mean CMC values ranged from 0.77 to 1 over all joint angles and all tasks. The second evaluation showed an increase in the RMSE of 2.28°– 2.58° on average for all joints and tasks. Hip flexion revealed the highest average RMSE in all tasks (4.87°– 8.27°). The present study revealed a valid IMU-based approach for the measurement of 3D joint kinematics in functional movements of varying demands. The high validity of the results encourages further development and the extension of the present approach into clinical settings.
Patients after total hip arthroplasty (THA) suffer from lingering musculoskeletal restrictions. Three-dimensional (3D) gait analysis in combination with machine-learning approaches is used to detect these impairments. In this work, features from the 3D gait kinematics, spatio temporal parameters (Set 1) and joint angles (Set 2), of an inertial sensor (IMU) system are proposed as an input for a support vector machine (SVM) model, to differentiate impaired and non-impaired gait. The features were divided into two subsets. The IMU-based features were validated against an optical motion capture (OMC) system by means of 20 patients after THA and a healthy control group of 24 subjects. Then the SVM model was trained on both subsets. The validation of the IMU system-based kinematic features revealed root mean squared errors in the joint kinematics from 0.24° to 1.25°. The validity of the spatio-temporal gait parameters (STP) revealed a similarly high accuracy. The SVM models based on IMU data showed an accuracy of 87.2% (Set 1) and 97.0% (Set 2). The current work presents valid IMU-based features, employed in an SVM model for the classification of the gait of patients after THA and a healthy control. The study reveals that the features of Set 2 are more significant concerning the classification problem. The present IMU system proves its potential to provide accurate features for the incorporation in a mobile gait-feedback system for patients after THA.
The core muscles play a central role in stabilizing the head during headers in soccer. The objective of this study was to examine the influence of a fatigued core musculature on the acceleration of the head during jump headers and run headers. Acceleration of the head was measured in a pre-post-design in 68 soccer players (age: 21.5 ± 3.8 years, height: 180.0 ± 13.9 cm, weight: 76.9 ± 8.1 kg). Data were recorded by means of a telemetric 3D acceleration sensor and with a pendulum header. The treatment encompassed two exercises each for the ventral, lateral, and dorsal muscle chains. The acceleration of the head between pre- and post-test was reduced by 0.3 G (p = 0.011) in jump headers and by 0.2 G (p = 0.067) in run headers. An additional analysis of all pretests showed an increased acceleration in run headers when compared to stand headers (p < 0.001) and jump headers (p < 0.001). No differences were found in the sub-group comparisons: semi-professional vs. recreational players, offensive vs. defensive players. Based on the results, we conclude that the acceleration of the head after fatiguing the core muscles does not increase, which stands in contrast to postulated expectations. More tests with accelerated soccer balls are required for a conclusive statement.
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.
Poor posture in childhood and adolescence is held responsible for the occurrence
of associated disorders in adult age. This study aimed to verify whether body
posture in adolescence can be enhanced through the improvement of neuromuscular
performance, attained by means of targeted strength, stretch, and body perception
training, and whether any such improvement might also transition into adulthood. From
a total of 84 volunteers, the posture development of 67 adolescents was checked
annually between the age of 14 and 20 based on index values in three posture
situations. 28 adolescents exercised twice a week for about 2 h up to the age of 18, 24
adolescents exercised continually up to the age of 20. Both groups practiced other
additional sports for about 1.8 h/week. Fifteen persons served as a non-exercising
control group, practicing optional sports of about 1.8 h/week until the age of 18,
after that for 0.9 h/week. Group allocation was not random, but depended on the
participants’ choice. A linear mixed model was used to analyze the development
of posture indexes among the groups and over time and the possible influence of
anthropometric parameters (weight, size), of optional athletic activity and of sedentary
behavior. The post hoc pairwise comparison was performed applying the Scheffé test.
The significance level was set at 0.05. The group that exercised continually (TR20)
exhibited a significant posture parameter improvement in all posture situations from
the 2nd year of exercising on. The group that terminated their training when reaching
adulthood (TR18) retained some improvements, such as conscious straightening of the
body posture. In other posture situations (habitual, closed eyes), their posture results
declined again from age 18. The effect sizes determined were between Eta² = 0.12 and
Eta² = 0.19 and represent moderate to strong effects. The control group did not exhibit
any differences. Anthropometric parameters, additional athletic activities and sedentary
behavior did not influence the posture parameters significantly. An additional athletic
training of 2 h per week including elements for improved body perception seems to
have the potential to improve body posture in symptom free male adolescents and
young adults.
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 (MPRAUC = 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.
Many machine learning models show black box characteristics and, therefore, a lack of transparency, interpretability, and trustworthiness. This strongly limits their practical application in clinical contexts. For overcoming these limitations, Explainable Artificial Intelligence (XAI) has shown promising results. The current study examined the influence of different input representations on a trained model’s accuracy, interpretability, as well as clinical relevancy using XAI methods. The gait of 27 healthy subjects and 20 subjects after total hip arthroplasty (THA) was recorded with an inertial measurement unit (IMU)-based system. Three different input representations were used for classification. Local Interpretable Model-Agnostic Explanations (LIME) was used for model interpretation. The best accuracy was achieved with automatically extracted features (mean accuracy Macc = 100%), followed by features based on simple descriptive statistics (Macc = 97.38%) and waveform data (Macc = 95.88%). Globally seen, sagittal movement of the hip, knee, and pelvis as well as transversal movement of the ankle were especially important for this specific classification task. The current work shows that the type of input representation crucially determines interpretability as well as clinical relevance. A combined approach using different forms of representations seems advantageous. The results might assist physicians and therapists finding and addressing individual pathologic gait patterns
The objectification of acute fatigue (during isometric muscle contraction) and cumulative fatigue (due to multiple intermittent isometric muscle contractions) plays an important role in sport climbing. The data of 42 participants were used in the study. Climbing performance was operationalized using maximal climbing-specific holding time (CSHT) by performing dead hangs. The test started with an initial measurement of handgrip strength (HGS) followed by three intermittent measurements of CSHT and HGS. During the test, finger flexor muscle oxygen saturation (SmO2) was measured using a near-infrared spectroscopy wearable biosensor. Significant reductions in CSHT and HGS could be found (p < 0.001), which indicates that the consecutive maximal isometric holding introduces cumulative fatigue. The reduction in CSHT did not correlate with a reduction in HGS over multiple consecutive maximal dead hangs (p > 0.35). Furthermore, there were no significant differences in initial SmO2 level, SmO2 level at termination, SmO2 recovery, and mean negative slope of the SmO2 saturation reduction between the different measurements (p > 0.24). Significant differences were found between pre-, termination-, and recovery- (10 s after termination) SmO2 levels (p < 0.001). Therefore, monitoring acute fatigue using athletes’ termination SmO2 saturation seems promising. By contrast, the measurement of HGS and muscle oxygen metabolism seems inappropriate for monitoring cumulative fatigue during intermittent isometric climbing-specific muscle contractions.
Heading in Soccer: Does Kinematics of the Head‐Neck‐Torso Alignment Influence Head Acceleration?
(2021)
There is little scientific evidence regarding the cumulative effect of purposeful heading. The head-neck-torso alignment is considered to be of great importance when it comes to minimizing potential risks when heading. Therefore, this study determined the relationship between head-neck-torso alignment (cervical spine, head, thoracic spine) and the acceleration of the head, the relationship between head acceleration and maximum ball speed after head impact and differences between head accelerations throughout different heading approaches (standing, jumping, running). A total of 60 male soccer players (18.9 ± 4.0 years, 177.6 ± 14.9 cm, 73.1 ± 8.6 kg) participated in the study. Head accelerations were measured by a telemetric Noraxon DTS 3D Sensor, whereas angles for the head-neck-torso alignment and ball speed were analyzed with a Qualisys Track Manager program. No relationship at all was found for the standing, jumping and running approaches. Concerning the relationship between head acceleration and maximum ball speed after head impact only for the standing header a significant result was calculated (p = 0.024, R2 = .085). A significant difference in head acceleration (p < .001) was identified between standing, jumping and running headers. To sum up, the relationship between head acceleration and head-neck-torso alignment is more complex than initially assumed and could not be proven in this study. Furthermore first data were generated to check whether the acceleration of the head is a predictor for the resulting maximum ball speed after head impact, but further investigations have to follow. Lastly, we confirmed the results that the head acceleration differs with the approach.