小于通气阈强度运动对脑电地形图影响的研究     

律海涛 《湖北体育科技》2003,22(3):303-305,311

对体育系男学生(20名)在安静状态、小于通气阈强度负荷运动后即刻1min的脑电变化进行测试得出结论：小于通气阈强度运动在一定程度上对大脑皮质产生影响，增进了大脑细胞新陈代谢强度，可改善大脑皮质神经元代谢能力，可改善和提高脑皮层神经细胞工作能力。  相似文献   

三种强度运动对脑电地形图影响的比较研究     

何叙 《天津体育学院学报》2003,18(4):5-7

采用实验研究方法，对体育系男学生(20名)在安静状态、小于通气阈强度、通气阈强度、大于通气阈强度负荷后即刻1min的脑电变化进行测试。结论：通气阈强度运动在一定程度上对大脑皮质产生影响，增进了大脑细胞新陈代谢强度，可改善大脑皮质神经元代谢能力，使其产生复杂的生理效应和训练效应，对脑皮层神经细胞工作能力的改善和提高很显著；大于通气阈强度运动后易使中枢神经细胞产生疲劳。  相似文献   

Rating of perceived exertion in maximal incremental tests during head-out water-based aerobic exercises     

Cristine Lima Alberton  Stephanie Santana Pinto  Tatiane Gorski  Amanda Haberland Antunes  Paula Finatto  Eduardo Lusa Cadore 《Journal of sports sciences》2016,34(18):1691-1698

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负载型催化剂研究中的自发单层分散原理     

林穗云  邓存 《嘉应学院学报》2006,24(6):42-46

许多负载型催化剂的活性组分可在载体表面自发分散。当活性组分含量低于其分散阈值时,它在载体表面呈单层但非密置单层分散,逾此阈值时出现晶相。自发分散效应可以称为自发单层分散原理。对自发单层分散原理的实质等问题作了初步探讨。  相似文献   

对拳击运动员实战练习前后肺通气功能的研究     

杨海平  高振国  张芝贤 《中国体育科技》2000,36(8):41-42

本文通过对 10名拳击运动员安静、实战后、次日晨的肺通气功能指标的测试 ,发现 VC大强度训练后有下降趋势 ,FEV1 .0 3次测值无差异 ,MVV实战后变化显著。提示 :拳击教练员可用 MVV评价训练负荷强度。  相似文献   

我国优秀女子短跑道速滑运动员最大有氧能力及通气阈的追踪研究     

张士祥  张亚丽 《北京体育大学学报》1993,(3)

最大摄氧量和通气阀作为衡量运动员耐力水平的指标已被广泛地应用于运动实践。对1987～1990年我国短跑道女子速滑运动员各个训练时期的最大摄氧量和通气阈进行了追踪研究。发现1987年的陆地训练能明显提高了运动员的有氧代谢能力。而且我国选手的最大摄氧量也高于国内外一些速度滑冰选手;通气阈在各个训练时期有训练均有明显的提高,所以,通气阈是评定短跑道速度滑冰运动员耐力水平的一个重要指标,通气阈的训练是提高耐力能力的重要训练手段,它优于最大摄氧最的训练。  相似文献   

通气阈强度运动对脑电地形图影响的研究     

何叙 《北京体育大学学报》2003,26(6):773-775

对体育系男学生(20名)在安静状态、通气阈强度负荷后即刻1min、及恢复2min后第3min的脑电变化进行测试得出结论:通气阈强度运动在一定程度上对大脑皮质产生影响,增进了大脑细胞新陈代谢强度,可改善大脑皮质神经元代谢能力,使其产生复杂的生理效应和训练效,对脑皮层神经细胞工作能力的改善和提高是很显著。  相似文献   

Q-代数中具有界限的模糊子代数     

彭家寅 《内江师范学院学报》2011,26(8):1-5

引入了Q-代数中具有界限的模糊子代数的概念,获得了它的一些相关性质,给出了具有界限的模糊子代数与（∈,∈Vq）-模糊子代数的关系．在Q-代数中,引入了t一蕴含的模糊子代数的概念,讨论了具有界限的模糊子代数与分别基于Gaines—Rescher蕴涵算子、Godel蕴涵算子和Godel蕴涵算子的换质算子的0．5-蕴含的模糊子代数之关系．  相似文献   

Blood lactate recovery and respiratory responses during diagonal skiing of variable intensity     

《European Journal of Sport Science》2013,13(5):317-326

Abstract

The aims of the study were to investigate blood lactate recovery and respiratory variables during diagonal skiing of variable intensity in skiers at different performance levels. Twelve male cross-country skiers classified as elite (n=6; [Vdot]O_2max=73±3 ml · kg^?1 · min^?1) or moderately trained (n=6; [Vdot]O_2max=61±5 ml · kg^?1 · min^?1) performed a 48-min variable intensity protocol on a treadmill using the diagonal stride technique on roller skis, alternating between 3 min at 90% and 6 min at 70% of [Vdot]O_2max. None of the moderately trained skiers were able to complete the variable intensity protocol and there was a difference in time to exhaustion between the two groups (elite: 45.0±7.3 min; moderately trained: 31.4±10.4 min) (P<0.05). The elite skiers had lower blood lactate concentrations and higher blood base excess concentrations at all 70% workloads than the moderately trained skiers (all P<0.05). In contrast, [Vdot] _E/[Vdot]O₂ and [Vdot] _E/[Vdot]CO₂ at the 70% [Vdot]O_2max workloads decreased independently of group (P<0.05). Partial correlations showed that [Vdot]O_2max was related to blood lactate at the first and second intervals at 70% of [Vdot]O_2max (r=?0.81 and r=?0.82; both P<0.01) but not to [Vdot] _E/[Vdot]O₂, [Vdot] _E/[Vdot]CO₂ or the respiratory exchange ratio. Our results demonstrate that during diagonal skiing of variable intensity, (1) elite skiers have superior blood lactate recovery compared with moderately trained skiers, who did not show any lactate recovery at 70% of [Vdot]O_2max, suggesting it is an important characteristic for performance; and (2) the decreases in respiratory exchange ratio, [Vdot] _E/[Vdot]O₂, and [Vdot] _E/[Vdot]CO₂ do not differ between elite and moderately trained skiers.  相似文献   

Expert-level classification of ventilatory thresholds from cardiopulmonary exercising test data with recurrent neural networks     

《European Journal of Sport Science》2013,13(9):1221-1229

Abstract

First and second ventilatory thresholds (VT₁ and VT₂) represent the boundaries of the moderate-heavy and heavy-severe exercise intensity. Currently, VTs are primarily detected visually from cardiopulmonary exercise test (CPET) data, beginning with an initial data screening followed by data processing and statistical analysis. Automated VT detection is a challenging task owing to the high signal to noise ratio typical of CPET data. Recurrent neural networks describe a machine learning form of Artificial Intelligence that can be used to uncover complex non-linear relationships between input and output variables. Here we proposed detection of VTs using a single neural network classifier, trained with a database of 228 laboratory CPET data. We tested the neural network performance against the judgement of 7 couples of board-certified exercise-physiologists on 25 CPET tests. The neural network achieved expert-level performances across the tasks (mean absolute error was 9.5% (r?=?0.79) and 4.2% (r?=?0.94) for VT₁ and VT₂, respectively). Estimation errors are compatible with the typical error of the current gold standard visual methodology. The neural network demonstrated VT detecting and exercise intensity level classifying at a high competence level. Neural networks could potentially be embedded in CPET hardware/software to extend the reach of exercise physiologists beyond their laboratories.  相似文献