@techreport{FischerHrsg2017, author = {Fischer (Hrsg.), Doris}, title = {Tourism in W{\"u}rzburg: Suggestions on how to enhance the travel experience for Chinese tourists}, edition = {1. Auflage}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-143898}, pages = {64}, year = {2017}, abstract = {This report provides suggestions on how to enhance the travel experience for Chinese tourists in the German city of W{\"u}rzburg. Based on a user experience survey and a market research, this work includes a quantitative and competitive analysis. It further provides concrete and hands-on measurements for the city council to improve the experience of Chinese visitors coming to W{\"u}rzburg.}, subject = {China}, language = {en} } @article{DuekingHolmbergKunzetal.2020, author = {D{\"u}king, Peter and Holmberg, Hans‑Christer and Kunz, Philipp and Leppich, Robert and Sperlich, Billy}, title = {Intra-individual physiological response of recreational runners to different training mesocycles: a randomized cross-over study}, series = {European Journal of Applied Physiology}, volume = {120}, journal = {European Journal of Applied Physiology}, issn = {1439-6319}, doi = {10.1007/s00421-020-04477-4}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-235022}, pages = {2705-2713}, year = {2020}, abstract = {Purpose Pronounced differences in individual physiological adaptation may occur following various training mesocycles in runners. Here we aimed to assess the individual changes in performance and physiological adaptation of recreational runners performing mesocycles with different intensity, duration and frequency. Methods Employing a randomized cross-over design, the intra-individual physiological responses [i.e., peak (\(\dot{VO}_{2peak}\)) and submaximal (\(\dot{VO}_{2submax}\)) oxygen uptake, velocity at lactate thresholds (V\(_2\), V\(_4\))] and performance (time-to-exhaustion (TTE)) of 13 recreational runners who performed three 3-week sessions of high-intensity interval training (HIIT), high-volume low-intensity training (HVLIT) or more but shorter sessions of HVLIT (high-frequency training; HFT) were assessed. Results \(\dot{VO}_{2submax}\), V\(_2\), V\(_4\) and TTE were not altered by HIIT, HVLIT or HFT (p > 0.05). \(\dot{VO}_{2peak}\) improved to the same extent following HVLIT (p = 0.045) and HFT (p = 0.02). The number of moderately negative responders was higher following HIIT (15.4\%); and HFT (15.4\%) than HVLIT (7.6\%). The number of very positive responders was higher following HVLIT (38.5\%) than HFT (23\%) or HIIT (7.7\%). 46\% of the runners responded positively to two mesocycles, while 23\% did not respond to any. Conclusion On a group level, none of the interventions altered \(\dot{VO}_{2submax}\), V\(_2\), V\(_4\) or TTE, while HVLIT and HFT improved \(\dot{VO}_{2peak}\). The mean adaptation index indicated similar numbers of positive, negative and non-responders to HIIT, HVLIT and HFT, but more very positive responders to HVLIT than HFT or HIIT. 46\% responded positively to two mesocycles, while 23\% did not respond to any. These findings indicate that the magnitude of responses to HIIT, HVLIT and HFT is highly individual and no pattern was apparent.}, language = {en} } @article{SarebanWinkertSperlichetal.2018, author = {Sareban, Mahdi and Winkert, Kay and Sperlich, Billy and Berger, Marc M. and Niebauer, Josef and Steinacker, J{\"u}rgen M. and Treff, Gunnar}, title = {Speckle tracking-derived bi-atrial strain before and after eleven weeks of training in elite rowers}, series = {Scientific Reports}, volume = {8}, journal = {Scientific Reports}, doi = {10.1038/s41598-018-32542-8}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-227362}, pages = {14300, 1-9}, year = {2018}, abstract = {The left (LA) and right (RA) atria undergo adaptive remodeling in response to hemodynamic stress not only induced by endurance exercise but also as part of several cardiovascular diseases thereby confounding differential diagnosis. Echocardiographic assessment of the atria with novel speckle tracking (STE)-derived variables broadens the diagnostic spectrum compared to conventional analyses and has the potential to differentiate physiologic from pathologic changes. The purpose of this study was to assess and categorize baseline values of bi-atrial structure and function in elite rowers according to recommended cutoffs, and to assess the cardiac changes occurring with endurance training. Therefore, fifteen elite rowers underwent 2D-echocardiographic analysis of established variables of cardiac structure and function as well as STE-derived variables of bi-atrial function. Measurements were performed at baseline and after eleven weeks of extensive training. 40\% of athletes displayed mildly enlarged LA and 47\% mildly enlarged RA at baseline, whereas no athlete fell below the lower reference values of LA and RA reservoir strain. Average power during a 2000 m ergometer rowing test (P2000 m) improved from 426 +/- 39 W to 442 +/- 34 W (p = 0.010) but there were no changes of echocardiographic variables following training. In elite rowers, longitudinal bi-atrial strain assessment indicates normal resting function of structurally enlarged atria and thereby may assist to differentiate between exercise-induced versus disease-associated structural cardiac changes in which function is commonly impaired.}, language = {en} } @article{DuekingGiessingFrenkeletal.2020, author = {D{\"u}king, Peter and Giessing, Laura and Frenkel, Marie Ottilie and Koehler, Karsten and Holmberg, Hans-Christer and Sperlich, Billy}, title = {Wrist-Worn Wearables for Monitoring Heart Rate and Energy Expenditure While Sitting or Performing Light-to-Vigorous Physical Activity: Validation Study}, series = {JMIR mhealth and uhealth}, volume = {8}, journal = {JMIR mhealth and uhealth}, number = {5}, doi = {10.2196/16716}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-229413}, year = {2020}, abstract = {Background: Physical activity reduces the incidences of noncommunicable diseases, obesity, and mortality, but an inactive lifestyle is becoming increasingly common. Innovative approaches to monitor and promote physical activity are warranted. While individual monitoring of physical activity aids in the design of effective interventions to enhance physical activity, a basic prerequisite is that the monitoring devices exhibit high validity. Objective: Our goal was to assess the validity of monitoring heart rate (HR) and energy expenditure (EE) while sitting or performing light-to-vigorous physical activity with 4 popular wrist-worn wearables (Apple Watch Series 4, Polar Vantage V, Garmin Fenix 5, and Fitbit Versa). Methods: While wearing the 4 different wearables, 25 individuals performed 5 minutes each of sitting, walking, and running at different velocities (ie, 1.1 m/s, 1.9 m/s, 2.7 m/s, 3.6 m/s, and 4.1 m/s), as well as intermittent sprints. HR and EE were compared to common criterion measures: Polar-H7 chest belt for HR and indirect calorimetry for EE. Results: While monitoring HR at different exercise intensities, the standardized typical errors of the estimates were 0.09-0.62, 0.13-0.88, 0.62-1.24, and 0.47-1.94 for the Apple Watch Series 4, Polar Vantage V, Garmin Fenix 5, and Fitbit Versa, respectively. Depending on exercise intensity, the corresponding coefficients of variation were 0.9\%-4.3\%, 2.2\%-6.7\%, 2.9\%-9.2\%, and 4.1\%-19.1\%, respectively, for the 4 wearables. While monitoring EE at different exercise intensities, the standardized typical errors of the estimates were 0.34-1.84, 0.32-1.33, 0.46-4.86, and 0.41-1.65 for the Apple Watch Series 4, Polar Vantage V, Garmin Fenix 5, and Fitbit Versa, respectively. Depending on exercise intensity, the corresponding coefficients of variation were 13.5\%-27.1\%, 16.3\%-28.0\%, 15.9\%-34.5\%, and 8.0\%-32.3\%, respectively. Conclusions: The Apple Watch Series 4 provides the highest validity (ie, smallest error rates) when measuring HR while sitting or performing light-to-vigorous physical activity, followed by the Polar Vantage V, Garmin Fenix 5, and Fitbit Versa, in that order. The Apple Watch Series 4 and Polar Vantage V are suitable for valid HR measurements at the intensities tested, but HR data provided by the Garmin Fenix 5 and Fitbit Versa should be interpreted with caution due to higher error rates at certain intensities. None of the 4 wrist-worn wearables should be employed to monitor EE at the intensities and durations tested."}, language = {en} } @article{DuekingTaflerWallmannSperlichetal.2020, author = {D{\"u}king, Peter and Tafler, Marie and Wallmann-Sperlich, Birgit and Sperlich, Billy and Kleih, Sonja}, title = {Behavior Change Techniques in Wrist-Worn Wearables to Promote Physical Activity: Content Analysis}, series = {JMIR Mhealth and Uhealth}, volume = {8}, journal = {JMIR Mhealth and Uhealth}, number = {11}, doi = {10.2196/20820}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-230556}, year = {2020}, abstract = {Background: Decreasing levels of physical activity (PA) increase the incidences of noncommunicable diseases, obesity, and mortality. To counteract these developments, interventions aiming to increase PA are urgently needed. Mobile health (mHealth) solutions such as wearable sensors (wearables) may assist with an improvement in PA. Objective: The aim of this study is to examine which behavior change techniques (BCTs) are incorporated in currently available commercial high-end wearables that target users' PA behavior. Methods: The BCTs incorporated in 5 different high-end wearables (Apple Watch Series 3, Garmin V{\´i}voactive 3, Fitbit Versa, Xiaomi Amazfit Stratos 2, and Polar M600) were assessed by 2 researchers using the BCT Taxonomy version 1 (BCTTv1). Effectiveness of the incorporated BCTs in promoting PA behavior was assessed by a content analysis of the existing literature. Results: The most common BCTs were goal setting (behavior), action planning, review behavior goal(s), discrepancy between current behavior and goal, feedback on behavior, self-monitoring of behavior, and biofeedback. Fitbit Versa, Garmin V{\´i}voactive 3, Apple Watch Series 3, Polar M600, and Xiaomi Amazfit Stratos 2 incorporated 17, 16, 12, 11, and 11 BCTs, respectively, which are proven to effectively promote PA. Conclusions: Wearables employ different numbers and combinations of BCTs, which might impact their effectiveness in improving PA. To promote PA by employing wearables, we encourage researchers to develop a taxonomy specifically designed to assess BCTs incorporated in wearables. We also encourage manufacturers to customize BCTs based on the targeted populations.}, language = {en} } @article{SchaffarczykKoehnOggianoetal.2022, author = {Schaffarczyk, Alois and Koehn, Silas and Oggiano, Luca and Schaffarczyk, Kai}, title = {Aerodynamic benefits by optimizing cycling posture}, series = {Applied Sciences}, volume = {12}, journal = {Applied Sciences}, number = {17}, issn = {2076-3417}, doi = {10.3390/app12178475}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-285942}, year = {2022}, abstract = {An approach to aerodynamically optimizing cycling posture and reducing drag in an Ironman (IM) event was elaborated. Therefore, four commonly used positions in cycling were investigated and simulated for a flow velocity of 10 m/s and yaw angles of 0-20° using OpenFoam-based Nabla Flow CFD simulation software software. A cyclist was scanned using an IPhone 12, and a special-purpose meshing software BLENDER was used. Significant differences were observed by changing and optimizing the cyclist's posture. Aerodynamic drag coefficient (CdA) varies by more than a factor of 2, ranging from 0.214 to 0.450. Within a position, the CdA tends to increase slightly at yaw angles of 5-10° and decrease at higher yaw angles compared to a straight head wind, except for the time trial (TT) position. The results were applied to the IM Hawaii bike course (180 km), estimating a constant power output of 300 W. Including the wind distributions, two different bike split models for performance prediction were applied. Significant time saving of roughly 1 h was found. Finally, a machine learning approach to deduce 3D triangulation for specific body shapes from 2D pictures was tested.}, language = {en} } @article{SchneiderWiewelhoveRaederetal.2019, author = {Schneider, Christoph and Wiewelhove, Thimo and Raeder, Christian and Flatt, Andrew A. and Hoos, Olaf and Hottenrott, Laura and Schumbera, Oliver and Kellmann, Michael and Meyer, Tim and Pfeiffer, Mark and Ferrauti, Alexander}, title = {Heart Rate Variability Monitoring During Strength and High-Intensity Interval Training Overload Microcycles}, series = {Frontiers in Physiology}, volume = {10}, journal = {Frontiers in Physiology}, doi = {10.3389/fphys.2019.00582}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-231515}, year = {2019}, abstract = {Objective: In two independent study arms, we determine the effects of strength training (ST) and high-intensity interval training (HIIT) overload on cardiac autonomic modulation by measuring heart rate (HR) and vagal heart rate variability (HRV). Methods: In the study, 37 well-trained athletes (ST: 7 female, 12 male; HIIT: 9 female, 9 male) were subjected to orthostatic tests (HR and HRV recordings) each day during a 4-day baseline period, a 6-day overload microcycle, and a 4-day recovery period. Discipline-specific performance was assessed before and 1 and 4 days after training. Results: Following ST overload, supine HR, and vagal HRV (Ln RMSSD) were clearly increased and decreased (small effects), respectively, and the standing recordings remained unchanged. In contrast, HIIT overload resulted in decreased HR and increased Ln RMSSD in the standing position (small effects), whereas supine recordings remained unaltered. During the recovery period, these responses were reversed (ST: small effects, HIIT: trivial to small effects). The correlations between changes in HR, vagal HRV measures, and performance were weak or inconsistent. At the group and individual levels, moderate to strong negative correlations were found between HR and Ln RMSSD when analyzing changes between testing days (ST: supine and standing position, HIIT: standing position) and individual time series, respectively. Use of rolling 2-4-day averages enabled more precise estimation of mean changes with smaller confidence intervals compared to single-day values of HR or Ln RMSSD. However, the use of averaged values displayed unclear effects for evaluating associations between HR, vagal HRV measures, and performance changes, and have the potential to be detrimental for classification of individual short-term responses. Conclusion: Measures of HR and Ln RMSSD during an orthostatic test could reveal different autonomic responses following ST or HIIT which may not be discovered by supine or standing measures alone. However, these autonomic changes were not consistently related to short-term changes in performance and the use of rolling averages may alter these relationships differently on group and individual level.}, language = {en} } @article{TreffWinkertSarebanetal.2019, author = {Treff, Gunnar and Winkert, Kay and Sareban, Mahdi and Steinacker, J{\"u}rgen M. and Sperlich, Billy}, title = {The Polarization-Index: A Simple Calculation to Distinguish Polarized From Non-polarized Training Intensity Distributions}, series = {Frontiers in Physiology}, volume = {10}, journal = {Frontiers in Physiology}, doi = {10.3389/fphys.2019.00707}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-229040}, year = {2019}, abstract = {The training intensity distribution (TID) of endurance athletes has retrieved substantial scientific interest since it reflects a vital component of training prescription: (i) the intensity of exercise and its distribution over time are essential components for adaptation to endurance training and (ii) the training volume (at least for most endurance disciplines) is already near or at maximum, so optimization of training procedures including TID have become paramount for success. This paper aims to elaborate the polarization-index (PI) which is calculated as log10(Zone 1/Zone 2∗Zone 3∗100), where Zones 1-3 refer to aggregated volume (time or distance) spent with low, mid, or high intensity training. PI allows to distinguish between non-polarized and polarized TID using a cut-off > 2.00 a.U. and to quantify the level of a polarized TID. Within this hypothesis paper, examples from the literature illustrating the usefulness of PI-calculation are discussed as well as its limitations. Further it is elucidated how the PI may contribute to a more precise definition of TID descriptors.}, language = {en} }