Knowing how many people are likely to benefit from a newly developed running shoe is of high relevance for footwear developers, phrasing legal claims and ultimately purchasing consumers. In order to assess and evaluate a likely scenario, the between-days reproducibility of percentages benefitting from lighter conventional flat running shoes (CON) or lighter advanced shoes with high stack height and longitudinally placed stiffening element (ADV) was investigated in a pool of 32 recreational runners. After comparing ADV and CON against running in heavier familiar shoes (OWN), percentages of the participant pool benefitting at different magnitudes of metabolic saving were derived. When comparing percentages of participants benefitting from CON and ADV between visits, retest correlation coefficients were respectively 0.95 and 0.99. Across magnitudes, the typical errors of percentages benefitting were 9.18% (CON) and 3.46% (ADV). Stated group averages of i.e. 4% metabolic savings when running in ADV, may potentially lead to the false assumption that the stated benefit applies to every runner. In contrast, based on our introduced approach, one can reliably state that a metabolic saving of i.e. 4% can be expected for at least 25% of recreational runners. Therefore, the expected percentage population benefitting at given magnitudes might be a more transparent expression for developers, marketing teams and consumers considering the relatively large measurement error of footwear induced metabolic savings on individual level.
The aim of this study was to provide a rationale for future validations of a priori calibrated respiratory inductance plethysmography (RIP) when used under exercise conditions. Therefore, the validity of a posteriori-adjusted gain factors and accuracy in resultant breath-by-breath RIP data recorded under resting and running conditions were examined.Healthy subjects, 98 men and 88 women (mean ± SD: height = 175.6 ± 8.9 cm, weight = 68.9 ± 11.1 kg, age = 27.1 ± 8.3 yr), underwent a standardized test protocol, including a period of standing still, an incremental running test on treadmill, and multiple periods of recovery. Least square regression was used to calculate gain factors, respectively, for complete individual data sets as well as several data subsets. In comparison with flowmeter data, the validity of RIP in breathing rate (fR) and inspiratory tidal volume (VTIN) were examined using coefficients of determination (R). Accuracy was estimated from equivalence statistics.Calculated gains between different data subsets showed no equivalence. After gain adjustment for the complete individual data set, fR and VTIN between methods were highly correlated (R = 0.96 ± 0.04 and 0.91 ± 0.05, respectively) in all subjects. Under conditions of standing still, treadmill running, and recovery, 86%, 98%, and 94% (fR) and 78%, 97%, and 88% (VTIN), respectively, of all breaths were accurately measured within ± 20% limits of equivalence.In case of the best possible gain adjustment, RIP confidentially estimates tidal volume accurately within ± 20% under exercise conditions. Our results can be used as a rationale for future validations of a priori calibration procedures.
Objective: Finishing a marathon requires to prepare for a 42.2 km run. Current literature describes which training characteristics are related to marathon performance. However, which training is most effective in terms of a performance improvement remains unclear. Methods: We conducted a retrospective analysis of training responses during a 16 weeks training period prior to an absolved marathon. The analysis was performed on unsupervised fitness app data (Runtastic) from 6,771 marathon finishers. Differences in training volume and intensity between three response and three marathon performance groups were analyzed. Training response was quantified by the improvement of the velocity of 10 km runs Δ v 10 between the first and last 4 weeks of the training period. Response and marathon performance groups were classified by the 33.3rd and 66.6th percentile of Δ v 10 and the marathon performance time, respectively. Results: Subjects allocated in the faster marathon performance group showed systematically higher training volume and higher shares of training at low intensities. Only subjects in the moderate and high response group increased their training velocity continuously along the 16 weeks of training. Conclusion: We demonstrate that a combination of maximized training volumes at low intensities, a continuous increase in average running speed up to the aimed marathon velocity and high intensity runs ≤ 5 % of the overall training volume was accompanied by an improved 10 km performance which likely benefited the marathon performance as well. The study at hand proves that unsupervised workouts recorded with fitness apps can be a valuable data source for future studies in sport science.
Drug therapy is one of the most common therapeutic interventions in the medical care of in-patients. It is a complex risk-associated procedure, which is why risk prevention is of top priority in medication safety. Medical care in hospitals is organised via various forms of distribution, e.g. the traditional distribution on the ward or as computerised unit dose drug dispensing system. In order to improve medication safety, the computerised unit dose drug dispensing system was introduced in the Ruppiner Kliniken in 2009. The implementation of the system to the clinic was scientifically evaluated within the scope of a diploma thesis which focused on the examination and analysis of medication safety and its evolvement. Amongst others, medication errors were detected and classified (via DokuPIK). The thesis showed that the implementation of the computerised unit dose system had a positive impact on the reduction of consequences of common and clinically relevant medication errors, thereby enhancing medication safety for the patient.
This study investigated the relationship between thermal perceptions during human wear trials and thermal foot manikin measurements of heat and vapour resistance for five running shoes varying in material and construction. Measurements of thermal/evaporative resistance were performed using a 12-zone sweating thermal-foot manikin. Eleven males performed running trials on five occasions, wearing shoes of same design, differing in materials and construction, to achieve a range of heat/vapour resistances and air permeabilities. Trials in 20°C/60% RH consisted of three phases: 15 min rest, 40 min running, 15 min recovery. In-shoe temperature/humidity were measured at two sites on the left foot. Thermal sensation/wetness perception/thermal comfort were provided for the left foot and four foot regions. Variations in shoe material and construction resulted in differences in thermal and evaporative resistance. These differences were reflected in in-shoe temperature and in-shoe absolute humidity assessed during wear trials. At the end of the rest period, thermal sensation was strongly related to thermal insulation ( r 2 = 0.69, p<0.001). During exercise however, thermal sensation, wetness perception and thermal discomfort were related to both thermal insulation and evaporative resistance. Thermal foot manikins provide a sensitive, effective evaluation of footwear thermal properties, which are also reflective of changes to in-shoe parameters during actual use. This discriminate power may be enhanced using higher, more realistic air-speeds during testing, as well as simulating foot movement. While thermal foot manikins are highly sensitive to design features/attributes of footwear (e.g. ventilation openings, air-permeabilities and coatings), subjective evaluations of footwear do not seem to have the same sensitivity and discriminative power.
The present research describes the development and validation of a cardiovascular model (CVR Model) for use in conjunction with advanced thermophysiological models, where usually only a total cardiac output is estimated. The CVR Model detailed herein estimates cardio-dynamic parameters (changes in cardiac output, stroke volume, and heart rate), regional blood flow, and muscle oxygen extraction, in response to rest and physical workloads, across a range of ages and aerobic fitness levels, as well as during exposure to heat, dehydration, and altitude. The model development strategy was to first establish basic resting and exercise predictions for cardio-dynamic parameters in an "ideal" environment (cool, sea level, and hydrated person). This basic model was then advanced for increasing levels of altitude, heat strain, and dehydration, using meta-analysis and reaggregation of published data. Using the estimated altitude- and heat-induced changes in maximum oxygen extraction and maximum cardiac output, the decline in maximum oxygen consumption at high altitude and in the heat was also modeled. A validation of predicted cardiovascular strain using heart rate was conducted using a dataset of 101 heterogeneous individuals (1,371 data points) during rest and exercise in the heat and at altitude, demonstrating that the CVR Model performs well (R2 = 0.82-0.84) in predicting cardiovascular strain, particularly at a group mean level (R2 = 0.97). The development of the CVR Model is aimed at providing the Fiala thermal Physiology & Comfort (FPC) Model and other complex thermophysiological models with improved estimations of cardiac strain and exercise tolerance, across a range of individuals during acute exposure to environmental stressors.NEW & NOTEWORTHY The present research promotes the adaption of thermophysiological modeling to the estimation of cardiovascular strain in individuals exercising under acute environmental stress. Integration with advanced models of human thermoregulation opens doors for detailed numerical analysis of athletes' performance and physiology during exercise, occupational safety, and individual work tolerability. The research provides a simple-to-validate metric of cardiovascular function (heart rate), as well as a method to evaluate key principles influencing exercise- and thermoregulation in humans.
This experiment studied textile (surface texture, thickness) and non-textile (local skin temperature changes, stickiness sensation and fabric-to-skin pressure) parameters affecting skin wetness perception under dynamic interactions. Changes in fabric texture sensation between WET and DRY states and their effect on pleasantness were also studied. The surface texture of eight fabric samples, selected for their different structures, was determined from surface roughness measurements using the Kawabata Evaluation System. Sixteen participants assessed fabric wetness perception, at high pressure and low pressure conditions, stickiness, texture and pleasantness sensation on the ventral forearm. Differences in wetness perception (p < 0.05) were not determined by texture properties and/or texture sensation. Stickiness sensation and local skin temperature drop were determined as predictors of wetness perception (r 2 = 0.89), and although thickness did not correlate with wetness perception directly, when combined with stickiness sensation it provided a similar predictive power (r 2 = 0.86). Greater (p < 0.05) wetness perception responses at high pressure were observed compared with low pressure. Texture sensation affected pleasantness in DRY (r 2 = 0.89) and WET (r 2 = 0.93). In WET, pleasantness was significantly reduced (p < 0.05) compared to DRY, likely due to the concomitant increase in texture sensation (p < 0.05). In summary, under dynamic conditions, changes in stickiness sensation and wetness perception could not be attributed to fabric texture properties (i.e. surface roughness) measured by the Kawabata Evaluation System. In dynamic conditions thickness or skin temperature drop can predict fabric wetness perception only when including stickiness sensation data.
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