ANALYSIS OF HUMAN MOTION WITH METHODS FROM MACHINE LEARNING

Usually, predefined kinematic parameters are investigated in biomechanical studies of human motion. In recent years, techniques of machine learning have been added to this field of research (Chau, 2001). In this study different dimension reduction methods like Principal Component Analysis (PCA) and Fourier Transformation (FT) are investigated as an alternative to common biomechanical approaches in motion analysis

Reduced activation in isometric muscle action after lengthening contractions is not accompanied by reduced performance fatigability

After active lengthening contractions, a given amount of force can be maintained with less muscle activation compared to pure isometric contractions at the same muscle length and intensity. This increase in neuromuscular efficiency is associated with mechanisms of stretch-induced residual force enhancement. We hypothesized that stretch-related increase in neuromuscular efficiency reduces fatigability of a muscle during submaximal contractions. 13 subjects performed 60 s isometric knee extensions at 60% of maximum voluntary contraction (MVC) with and without prior stretch (60°/s, 20°). Each 60 s trial was preceded and followed by neuromuscular tests consisting of MVCs, voluntary activation (VA) and resting twitches (RT), and there was 4 h rest between sets. We found a significant (p = 0.036) 10% reduction of quadriceps net-EMG after lengthening compared to pure isometric trials. However, increase in neuromuscular efficiency did not influence the development of fatigue. Albeit we found severe reduction of MVC (30%), RT (30%) and VA (5%) after fatiguing trials, there were no differences between conditions with and without lengthening. As the number of subjects showing no activation reduction increased with increasing contraction time, intensity may have been too strenuous in both types of contractions, such that a distinction between different states of fatigue was not possible anymore

ANALYSIS OF HUMAN MOTION WITH METHODS FROM MACHINE LEARNING

biomechanical studies of human motion. In recent years, techniques of machine learning have been added to this field of research (Chau, 2001). In this study different dimension reduction methods like Principal Component Analysis (PCA) and Fourier Transformation (FT) are investigated as an alternative to common biomechanical approaches in motion analysis

Oxygen consumption of gastrocnemius medialis muscle during submaximal voluntary isometric contractions with and without preceding stretch

After an active muscle stretch, maintaining a certain amount of force in the following isometric phase is accompanied by less muscle activation compared to an isometric contraction without preceding active stretch at the corresponding muscle length. This reduced muscle activation might be related to reduced metabolic costs, such as the oxidative metabolism. Hence, the aim of this study was to clarify if mechanisms associated with stretch-induced activation reduction (AR) also influence oxygen consumption of voluntary activated human muscles after active stretch. Plantarflexion torque of 20 subjects was measured during 1) purely isometric and 2) active stretch contractions (26°, 60°/s), at a submaximal torque level of 30% MVC. Oxygen consumption (m VO) of gastrocnemius medialis (GM) was estimated by near-infrared spectroscopy while applying arterial occlusion. Since the overall group did not show AR at GM after active stretch (p > 0.19), a subgroup was defined (n = 10) showing AR of 13.0 ± 10.3% (p = 0.00). However, for both purely isometric and active contractions m VO was the same (p = 0.32). Therefore, AR triggered by active stretch did not affect m VO of active human muscle

Geophysical investigations in the Southern Bohemian Massif

No abstract available

Multidisciplinary and multi-methodological approach for the study of active volcanic areas. Preliminary results for the Vulcano island test site (Southern Sicily, Italy)

We present a multidisciplinary and multi-metodological approach to develop a geostructural and dynamic model applied to an active volcanic area and based on the integrated interpretation of all available geophysical data sets. New algorithms are proposed and applied to synthesise the results coming from the single modelling of different geophysical data sets. Some constrains imposed by the results of other geo-scientific methodologies (geological, geochemical, geodetic, etc.) are considered to obtain a geo-structural model of the volcanic area under investigation. This area, for its peculiar nature, can modify itself from time to time and therefore is necessary to take in account the temporal and spatial variations of monitored parameters. So, the model parameters changes will give an indication on the persisting volcanic dynamics in the subsurface. These results, will be mosaiced using a Geographical Information System. The Vulcano Island was selected as test site, because high quality sets of geophysical data are available within the framework of our previous research projects