9 research outputs found

    The effect of visual focus on spatio-temporal and kinematic parameters of treadmill running

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    The characteristics of a treadmill and the environment where it is based could influence the user’s gaze and have an effect on their running kinematics and lower limb impacts. The aim of this study was to identify the effect of visual focus on spatio-temporal parameters and lower limb kinematics during treadmill running. Twenty six experienced runners ran at 3.33 m s−1 on a treadmill under two visual conditions, either looking ahead at a wall or looking down at the treadmill visual display. Spatio-temporal parameters, impact accelerations of the head and tibia, and knee and ankle kinematics were measured for the final 15 s of a 90 s bout of running under each condition. At the end of the test, participants reported their preference for the visual conditions assessed. Participants’ stride angle, flight time, knee flexion during the flight phase, and ankle eversion during contact time were increased when runners directed visual focus toward the wall compared to the treadmill display (p 0.05). However, the effect size of all biomechanical alterations was small. The Treadmill condition was the preferred condition by the participants (p < 0.001; ESw = 1.0). The results of the current study indicate that runners had a greater mass centre vertical displacement when they ran looking ahead, probably with the aim of compensating for reduced visual feedback, which resulted in larger head accelerations. Greater knee flexion during the flight phase and ankle eversion during the contact time were suggested as compensatory mechanisms for lower limb impacts

    Thermographic imaging in sports and exercise medicine: A Delphi study and consensus statement on the measurement of human skin temperature

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    This is an accepted manuscript of an article published by Elsevier in Journal of Thermal Biology on 18/07/2017, available online: https://doi.org/10.1016/j.jtherbio.2017.07.006 The accepted version of the publication may differ from the final published version.© 2017 Elsevier Ltd The importance of using infrared thermography (IRT) to assess skin temperature (tsk) is increasing in clinical settings. Recently, its use has been increasing in sports and exercise medicine; however, no consensus guideline exists to address the methods for collecting data in such situations. The aim of this study was to develop a checklist for the collection of tsk using IRT in sports and exercise medicine. We carried out a Delphi study to set a checklist based on consensus agreement from leading experts in the field. Panelists (n  =  24) representing the areas of sport science (n = 8; 33%), physiology (n = 7; 29%), physiotherapy (n = 3; 13%) and medicine (n = 6; 25%), from 13 different countries completed the Delphi process. An initial list of 16 points was proposed which was rated and commented on by panelists in three rounds of anonymous surveys following a standard Delphi procedure. The panel reached consensus on 15 items which encompassed the participants’ demographic information, camera/room or environment setup and recording/analysis of tsk using IRT. The results of the Delphi produced the checklist entitled “Thermographic Imaging in Sports and Exercise Medicine (TISEM)” which is a proposal to standardize the collection and analysis of tsk data using IRT. It is intended that the TISEM can also be applied to evaluate bias in thermographic studies and to guide practitioners in the use of this technique.Published versio

    Effect of Saddle height on skin temperature measured in different days of cycling.

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    Infrared thermography can be useful to explore the effects of exercise on neuromuscular function. During cycling, it could be used to investigate the effects of saddle height on thermoregulation. The aim of this study was to examine whether different cycling postures, elicited by different knee flexion angles, could influence skin temperature. Furthermore, we also determined whether the reproducibility of thermal measurements in response to cycling differed in the body regions affected or not affected by saddle height. Sixteen cyclists participated in three tests of 45 min of cycling at their individual 50 % peak power output. Each test was performed in a different knee flexion position on the bicycle (20°, 30°, 40° knee flexion when the pedal crank was at 180°). Different knee angles were obtained by changing saddle height. Skin temperatures were determined by infrared thermography before, immediately after and 10 min after the cycling test, in 16 different regions of interest (ROI) in the trunk and lower limbs. Changes in saddle height did not result in changes in skin temperature in the ROI. However, lower knee flexion elicited higher temperature in popliteus after cycling than higher flexion (p = 0.008 and ES = 0.8), and higher knee flexion elicited lower temperature variation in the tibialis anterior than intermediate knee flexion (p = 0.004 and ES = 0.8). Absolute temperatures obtained good and very good intraday reproducibility in the different measurements (ICCs between 0.44 and 0.85), but temperature variations showed lower reproducibility (ICCs between 0.11 and 0.74). Different postures assumed by the cyclist due to different saddle height did not influence temperature measurements. Skin temperature can be measured on different days with good repeatability, but temperature variations can be more sensitive to the effects of an intervention

    Multi-sector thermo-physiological head simulator for headgear research

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    [EN] A novel thermo-physiological human head simulator for headgear testing was developed by coupling a thermal head manikin with a thermo-physiological model. As the heat flux at head-site is directly measured by the head manikin, this method provides a realistic quantification of the heat transfer phenomena occurring in the headgear, such as moisture absorption-desorption cycles, condensation, moisture migration across clothing layers. Before coupling, the opportunities of the head manikin for representing the human physiology were evaluated separately. The evaluation revealed reduced precision in forehead and face temperature predictions under extreme heterogeneous temperature distributions and no initial limitation for simulating temperature changes observed in the human hysiology.This work has been supported by the State Secretariat for Education, Research and Innovation (SBFI C11.0137) under the grant COST Action TU1101 project (http://www.bicycle-helmets.eu/) The authors gratefully acknowledge Dr. Matthew Morrissey and Rolf Stampfli from Empa (St. Gallen, Switzerland) for their valuable contribution to programming of the coupling interface and Barbara Koelblen from Empa (St. Gallen, Switzerland) and Warsaw University of Technology (Warsaw, Poland) for providing the validation data and consultation.MartĂ­nez GuillamĂłn, N.; Psikuta, A.; CorberĂĄn, JM.; Rossi, RM.; Annaheim, S. (2017). Multi-sector thermo-physiological head simulator for headgear research. International Journal of Biometeorology. 61(2):273-285. https://doi.org/10.1007/s00484-016-1209-9273285612ASTM F2370-10, 2010 (2010) Standard test method for measuring the evaporative resistance of clothing using a sweating manikin. ASTM International, West ConshohockenBuono MJ, Ulrich RL (1998) Comparison of mean skin temperature using “covered” versus “uncovered” contact thermistors. Physiol Meas 19:297–300Burton AC (1944) An analysis of the physiological effects of clothing in hot environments. National Research Council, CanadaCasa DJ, Becker SM, Ganio MS, Brown CM, Yeargin SW, Roti MW, Siegler J, Blowers JA, Glaviano NR, Huggins RA, Armstrong LE, Maresh CM (2007) Validity of devices that assess body temperature during outdoor exercise in the heat. J Athl Train 42:333–342Curran AR, Peck SD, Hepokoski MA, Burke RA (2014) Physiological model control of a sweating thermal manikin. In: Ambience’14&10i3m, Tampere, Finland, 7-9 Sept 2014, pp. 7–9Easton C, Fudge BW, Pitsiladis YP (2007) Rectal, telemetry pill and tympanic membrane thermometry during exercise heat stress. J Therm Biol 32:78–86. doi: 10.1016/j.jtherbio.2006.10.004Fan J, Cheng X-J (2005a) Heat and moisture transfer with sorption and phase change through clothing assemblies: part I: experimental investigation. Text Res J 75:900–105. doi: 10.1177/004051750507500301Fan J, Cheng X-J (2005b) Heat and moisture transfer with sorption and phase change through clothing assemblies: part II: theoretical modeling, simulation, and comparison with experimental results. Text Res J 75:187–196. doi: 10.1177/004051750507500301Farrington RB, Rugh JP, Bharathan D, Burke R (2004) Use of a thermal manikin to evaluate human thermoregulatory responses in transient, non-uniform, thermal environments. In: Society of Automotive Engineers Technical Paper. pp. 2004–01–2345. SAE International. doi: 10.4271/2004-01-2345Farrington RB, Rugh JP, Bharathan D, Paul H, Bue G, Trevino L (2005). Using a sweating manikin, controlled by a human physiological model, to evaluate liquid cooling garments, in: Society of Automotive Engineers Technical Paper. doi: 10.4271/2005-01-2971Fiala D, Havenith G (2015) Modelling human heat transfer and temperature regulation, in: Springer-Verlag Berlin Heidelberg (Ed.), Studies in Mechanobiology, Tissue Engineering and Biomaterials. pp. 1–38. doi: 10.1007/8415Fiala D, Lomas KJ, Stohrer M (1999) A computer model of human thermoregulation for a wide range of environmental conditions: the passive system. J Appl Physiol 87:1957–1972Fiala D, Lomas KJ, Stohrer M (2001) Computer prediction of human thermoregulatory and temperature responses to a wide range of environmental conditions. Int J Biometeorol 45:143–159. doi: 10.1007/s004840100099Fiala D, Havenith G, Bröde P, Kampmann B, Jendritzky G (2012) UTCI-Fiala multi-node model of human heat transfer and temperature regulation. Int J Biometeorol 56:429–441. doi: 10.1007/s00484-011-0424-7Haslam RA, Parsons KC (1994) Using computer-based models for predicting human thermal responses to hot and cold environments. Ergonomics 37:399–416. doi: 10.1080/00140139408963659Havenith G, Richards MG, Wang X, Bröde P, Candas V, Den Hartog E, HolmĂ©r I, Kuklane K, Meinander H, Nocker W (2008) Apparent latent heat of evaporation from clothing: attenuation and heat pipe effects. J Appl Physiol 104:142–149. doi: 10.1152/japplphysiol.00612.2007Havenith G, Bröde P, den Hartog E, Kuklane K, Holmer I, Rossi RM, Richards M, Farnworth B, Wang X (2013) Evaporative cooling: effective latent heat of evaporation in relation to evaporation distance from the skin. J Appl Physiol 114:778–785. doi: 10.1152/japplphysiol.01271.2012ISO15831 (2004) Clothing—physiological effects—measurement of thermal insulation by means of a thermal manikin. International Organisation for Standardisation, Geneva (Switzerland)ISO9920 (2007) Ergonomics of the thermal environment—estimation of thermal insulation and water vapour resistance of a clothing ensemble. International Organisation for Standardisation, Geneva (Switzerland)Jones BW (2002) Capabilities and limitations of thermal models for use in thermal comfort standards. Energy Build 34:653–659. doi: 10.1016/S0378-7788(02)00016-6Kobayashi Y, Tanabe S (2013) Development of JOS-2 human thermoregulation model with detailed vascular system. Build Environ 66:1–10. doi: 10.1016/j.buildenv.2013.04.013Li Y, Li F, Liu Y, Luo Z (2004) An integrated model for simulating interactive thermal processes in human-clothing system. J Therm Biol 29:567–575. doi: 10.1016/j.jtherbio.2004.08.071Lotens WA (1993) Heat transfer from human wearing clothing. Techincal University Delft, DelftLotens WA, Havenith G (1994) Effects of moisture absorption in clothing on the human heat balance. Ergonomics 38:1092–1113Lotens WA, van de Linde FJG, Havenith G (1995) Effect of condensation in clothing on heat transfer. Ergonomics 38:1114–1131MĂ€kinen T, Gavhed D, HolmĂ©r I, RintamĂ€ki H (2000) Thermal responses to cold wind of thermoneutral and cooled subjects. Eur J Appl Physiol 81:397–402. doi: 10.1007/s004210050060MartĂ­nez N, Psikuta A, Rossi RM, CorberĂĄn JM, Annaheim S, (2016) Global and local heat transfer analysis for bicycle helmets using thermal head manikins. Int J Ind Ergon. 53:157–166. doi: 10.1016/j.ergon.2015.11.012MartĂ­nez N, Psikuta A, Annaheim S, CorberĂĄn JM, Rossi RM (2015) Validation of a physiological model for controlling a thermal head simulator. 16th International Conference on Environmental Ergonomics, PortsmouthMunir A, Takada S, Matsushita T (2009) Re-evaluation of Stolwijk’s 25-node human thermal model under thermal-transient conditions: prediction of skin temperature in low-activity conditions. Build Environ 44:1777–1787. doi: 10.1016/j.buildenv.2008.11.016Niedermann R, Wyss E, Annaheim S, Psikuta A, Davey S, Rossi RM (2014) Prediction of human core body temperature using non-invasive measurement methods. Int J Biometeorol 58:7–15. doi: 10.1007/s00484-013-0687-2Priego Quesada JI, MartĂ­nez GuillamĂłn N, CibriĂĄn Ortiz De Anda RM, Psikuta A, Annaheim S, Rossi RM, CorberĂĄn Salvador JM, PĂ©rez Soriano P, Salvador Palmer R (2015) Effect of perspiration on skin temperature measurements by infrared thermography and contact thermometry during aerobic cycling. Infrared Phys Technol 72:68–76. doi: 10.1016/j.infrared.2015.07.008Psikuta A (2009) Development of an “artificial human” for clothing research. De Monfort University, LeicesterPsikuta A, Richards M, Fiala D (2008) Single-sector thermophysiological human simulator. Physiol Meas 29:181–192Psikuta A, Fiala D, Laschewski G, Jendritzky G, Richards M, Blazejczyk K, Mekjavič I, RintamĂ€ki H, de Dear R, Havenith G (2012) Validation of the Fiala multi-node thermophysiological model for UTCI application. Int J Biometeorol 56:443–460Psikuta A, Niedermann R, Rossi RM (2013a) Effect of ambient temperature and attachment method on surface temperature measurements. Int J Biometeorol. doi: 10.1007/s00484-013-0669-4Psikuta A, Wang L-C, Rossi RM (2013b) Prediction of the physiological response of humans wearing protective clothing using a thermophysiological human simulator. J Occup Environ Hyg 10:222–232. doi: 10.1080/15459624.2013.766562Psikuta A, Kuklane K, Bogdan A, Havenith G, Annaheim S, Rossi RM (2016) Opportunities and constraints of presently used thermal manikins for thermophysiological simulation of the human body. Int J Biometeorol 60:435–446. doi: 10.1007/s00484-015-1041-7Redortier B, Voelcker T (2010) Implementation of thermo-physiological control on a multi-zone manikin. In: 8th International Meeting for Thermal Manikin and Modeling (8I3M), Victoria, Canada, 22-26 August 2010Redortier B, Voelcker T (2011) A 38-zone thermal manikin with physiological control: validation for simulating thermal response of the body for sports exercise in cold and hot environment, in: 14th International Conference on Environmental Ergonomics. Napflio, GreeceRugh JP, Farrington RB, Bharathan D, Vlahinos A, Burke R, Huizenga C, Zhang H (2004) Predicting human thermal comfort in a transient nonuniform thermal environment. Eur J Appl Physiol 92:721–727Smith CE (1991) A transient three-dimensional model of the thermal system. MSc thesis, Kansas State University, KansasStolwijk JA (1971) A mathematical model of physiological temperature regulation in man. NASA Contractor Report No. CR-1855, National Aeronautics and Space Administration, Washington, DCTanabe S, Kobayashi K, Nakano J, Ozeki Y (2002) Evaluation of thermal comfort using combined multi-node thermoregulation (65MN) and radiation models and computational fluid dynamics (CFD). Energy Build 34:637–646Teunissen LPJ, de Haan A, de Koning JJ, Daanen HAM (2012) Telemetry pill versus rectal and esophageal temperature during extreme rates of exercise-induced core temperature change. Physiol Meas 33:915–924. doi: 10.1088/0967-3334/33/6/915Wagner JA, Horvath SM (1985) Influences of age and gender on human thermoregulatory responses to cold exposures. J Appl Physiol 58:180–186Werner J, Webb P (1993) A six-cylinder model of human thermoregulation for general use on personal computers. Ann Physiol Anthropol 12:123–134. doi: 10.2114/ahs1983.12.123Wissler EH (1985) Mathematical simulation of human thermal behaviour using whole body models. In: Shitzer A, E.R.C. 1198 (eds) Heat transfer in medicine and biology—analysis and applications, vol 13. Plenum, New York, pp 325–373Wissler EH, Havenith G (2009) A simple theoretical model of heat and moisture transport in multi-layer garments in cool ambient air. Eur J Appl Physiol 105:797–808. doi: 10.1007/s00421-008-0966-5Wu H, Fan J (2008) Study of heat and moisture transfer within multi-layer clothing assemblies consisting of different types of battings. Int J Therm Sci 47:641–647. doi: 10.1016/j.ijthermalsci.2007.04.008Xu X, Werner J (1997) A dynamic model of the human/clothing/environment-system. Appl Hum Sc 16:61–75Zhang H (2003) Human thermal sensation and comfort in transient and non-uniform thermal environments. University of California, Berkele
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