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With the progress in modern medicine, it was possible to significantly reduce the risks of birth for mother and child. One aspect that has received less attention so far is the risk of injury to the accoucheurs (obstetricians and midwives) during the birth process. Indeed, studies indicate that 92% of midwives suffer from musculoskeletal disorders, with the lower back being the main cause of complaints (72%). The aim of this study was to investigate two commonly used postural techniques used by accoucheurs during childbirth and to analyze the resulting load on the lower back using the AnyBodyTM musculoskeletal simulation software.
We present two methods that combine image reconstruction and edge detection in computed tomography (CT) scans. Our first method is as an extension of the prominent filtered backprojection algorithm. In our second method we employ ℓ1-regularization for stable calculation of the gradient. As opposed to the first method, we show that this approach is able to compensate for undersampled CT data.
In this work, a simple cost effective method to create tunable self-assembled three-dimensional nanostructure array-like nanoantennas on a tip of an optical quartz glass fiber is described. The structures are prepared using lithography-less dry etching. Gold nanoparticles are used as an etching mask using a thin metal-film thermal dewetting technique. The structures are applied as sensor for label-free analysis of organic substances in ppb range, such as drug residues in groundwater. The measurements are carried out by means of a Surface-enhanced Raman scattering (SERS) effect, an exchangeable sensor head, and a portable Raman device. This method allows in situ applications. Parathiocresol is used as a model substance to characterize the SERS cells. For metallization, gold and silver are compared. Reproducible SERS enhancement factors up to 10 7 are evaluated.
Background:
Brain lesions in language-related cortical areas remain a challenge in the clinical routine. In recent years the resting-state fMRI (rs-fMRI) was shown to be a feasible method for preoperative language assessment. The aim of this study was to examine whether language-related resting-state components, which have been obtained using a data-driven independent-component-based identification algorithm, can be supportive in determining language dominance in the left or right hemisphere.
Methods:
Twenty patients suffering from brain lesions close to supposed language relevant cortical areas were included. Rs-fMRI and task-based (tb-fMRI) were performed for the purpose of preoperative language assessment. Tb-fMRI included a verb generation task with an appropriate control condition (a syllable switching task) to decompose language critical and language supportive processes. Subsequently, the best fitting ICA component for the resting-state language network (RSLN) referential to general linear models (GLMs) of the tb-fMRI (including models with and without linguistic control conditions) was identified using an algorithm based on the Dice-index.
Results:
The RSLNs associated with GLMs using a linguistic control condition led to significantly higher laterality indices than GLM baseline contrasts. LIs derived from GLM contrasts with and without control conditions alone did not differ significantly.
Conclusion:
In general, the results suggest that determining language dominance in the human brain is feasible both with tb-fMRI and rs-fMRI, and in particular, the combination of both approaches yields a higher specificity in preoperative language assessment. Moreover, we can conclude that the choice of the language mapping paradigm is crucial for the mentioned benefits.
Evaluation of muscle recruitment and muscle models in musculoskeletal simulation of dynamic motion
(2021)
Musculoskeletal simulation plays an increasingly important role in sports biomechanics. In the last years, the field of application widened from orthopaedics and ergonomics to sports [1]. A muscle recruitment algorithm with a quadratic objective function is usually used to calculate muscle activity in dynamic movements. The agreement of calculated and measured thigh muscle activity has already been investigated [2]. They found a strong agreement for sprinting and running, while the correlation decreased for side-cutting manoeuvres. Nevertheless, the influence of different muscle recruitment criteria on muscle activity in dynamic musculoskeletal simulations is currently unknown. Hence, this study aimed to analyse the effect of different muscle recruitment criteria and muscle models on the correlation of numerical and measured muscle activity in highly dynamic movements.