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Effect Of Far-infrared Fabric Riding Pants On Sports Fatigue And Fatigue Recovery

Posted on:2021-01-24Degree:MasterType:Thesis
Country:ChinaCandidate:X LiFull Text:PDF
GTID:2381330602982583Subject:Engineering
Abstract/Summary:PDF Full Text Request
With the demand for fitness shaping and the rise of gym sports,more and more people begin to be enthusiastic about cycling,and begin to pursue professional training.However,in the process of professional sports,only when there is fatigue can the effective training effect be achieved.The degree of muscle fatigue and the recovery state of fatigue after exercise affect the performance of the athlete's sports ability.However,the study found that the existing fatigue relief methods are not timely,and the equipment is complex.Therefore,the light and effective anti-fatigue program appears to be concerned.This project adopts far-infrared fabric to make cycling pants to explore its influence on sports fatigue and fatigue recovery,providing certain reference basis for the development of functional sportswear marketThis subject studies the performance of Emana far-infrared fibers.Based on the morphological characteristics of Emana fibers,Emana fibers and ordinary nylon were used as the raw material of the covering yarn as the base yarn.The 3-level structure and the 5-level interlacing ratio were designed to weave 15 seamless knitted cycling pants.15 groups of cycling pants were tested for cycling function.From the three dimensions of physiology,psychology,and body surface,heart rate,blood pressure,subjective fatigue evaluation,surface electromyography signals,body temperature,girth difference,and blood flow perfusion were measured Multi-factor analysis of variance,2D-kernel density distribution,and other methods were used to measure the impact of far-infrared fabrics,interweaving ratio,and structure of cycling pants on fatigue relief during cycling and muscle fatigue recovery after exercise.The exercise stage and recovery period of fatigue effect period and the muscle group were analyzed to explore the complete process of sports fatigue.Then using the gray near-optimal comprehensive evaluation to consider different evaluation indexes for the effect of sports fatigue relief and fatigue recovery after exercise,evaluate the 15 sets of cycling pants schemes,and find the best cycling pants scheme that resists sports fatigue and the best fatigue recovery cycling pants program.The main research conclusions were divided into the following two parts:First,the far-infrared fabric cycling pants can improve the body's motor function in cycling,and have the effect of restoring physical fitness in the process of cycling.Usually,when the exercise reaches 14?22min,with the far-infrared fabrics,the blood vessels on the body surface dilate,the blood circulation accelerates,the heat dissipation promotes and the body load relieves to some extent.The body feels the physical recovery subjectively,and the recovery effect increases with the content of far-infrared fabrics.The cycling pants with far-infrared fabric content of 100%and 75%had a significant effect of improving the sports performance and increasing the sports duration.According to the comprehensive evaluation,the cycling pants with 100%of far-infrared fabric content and plain weave structure have a better effect on relieving sports fatigueSecond,the far-infrared fabric cycling pants can help accelerate the blood flow microcirculation and relieve the muscle swelling after pedaling.The effect is positively related to the far-infrared content and the wearing time during recovery.Far-infrared fabric cycling pants have a significant effect on the rapid recovery of heart rate and body temperature after pedaling,and the far-infrared content is positively correlated with the recovery rate.Comprehensive evaluation shows that cycling pants with 1+2 false rib structure—100%far-infrared fabric content and plain weave structure—100%far-infrared fabric content have a better effect on fatigue recovery.
Keywords/Search Tags:Emana far-infrared fibers, Sports fatigue, fatigue recovery, Multi-factor variance analysis, 2D-kernel density distribution, Gray near-optimal comprehensive evaluation
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