Variabilidade da frequência cardíaca, carga de treino e caracterização psicofisiológica no ténis: estudo de caso
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2023
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A monitorização dos atletas é um dos aspetos críticos na otimização e individualização
do processo de treino e recuperação. A monitorização da frequência cardíaca (FC),
variabilidade da frequência cardíaca (VFC), perceção do esforço (RPE) e questionário de
stress e recuperação para atletas (RestQ-Sport) através de dados não invasivos, fornece
contributos importantes para este processo. A dissertação tem como objetivo investigar atletas
de elite de Ténis em contexto de treino e de competição através de 3 estudos.
No estudo 1, o objetivo foi monitorizar o período de preparação de dois atletas de elite
de Ténis durante 4 (atleta A, masculino, 28 anos) e 3 (atleta B, feminino, 21 anos) microciclos
de treino (M), através de variáveis fisiológicas (FC e VFC), psicológicas (RestQ-Sport e RPE)
e caracterização do treino, carga de treino (CT) e volume de treino (VT). A análise da VFC,
através das médias semanais, foi feita utilizando a variação mínima útil (SWC) e o erro padrão
de forma a estabelecer uma zona de variação trivial. Os principais resultados foram: Para o
atleta A as maiores variações foram encontradas de M2 para M3, no logaritmo natural da raiz
quadrada da média da soma dos quadrados das diferenças entre intervalos R-R adjacentes
(Ln rMSSD), - 4,05% do SWC; na frequência cardíaca em repouso (FCrep), +0,68%; no índice
do sistema nervoso parassimpático (PNSIndex), -14,4% e índice do sistema nervoso
simpático (SNSIndex), -12,8%. Para o atleta B, foi de M1 para M2 que se verificaram as
maiores variações, Ln rMSSD, +14,4%; FCrep, -14,8%; PNSIndex, 373,8% e SNSIndex,
300%. Foram investigadas as associações entre a carga de treino (CT) e volume de treino
(VT) e RPE, FCrep, Ln rMSSD e o intervalo de tempo entre batimentos consecutivos (R-R).
Para o atleta A, a RPE correlacionou-se com o VT (r = 0,692, p < 0,01), FCrep r = 0,546; p <
0,01 e R-R r = -0,999, p < 0,01; a FCrep com VT, r = 0,546; p < 0,01 e com R-R, r = -0,999, p
< 0,01. Para a atleta B a RPE correlacionou-se com o VT, r = 0,811, p < 0,01; para Ln rMSSD
e R-R, r = 0,829, p < 0,01; para FCrep e Ln rMSSD, r = -0,848, p < 0,01; Para Fcrep e R-R, r
= -0,994, p < 0,01. Para as respostas ao RestQ-Sport, foram encontradas diferenças no atleta
A, no índice de recuperação de M0 para M3 e de M0 para M4 (p < 0,01 e p < 0,03), e para a
atleta B, de M0 para M1 (p < 0,01). Para o índice de stress, no atleta A de M0 para M3 e de
M0 para M4 (p < 0,02) e para a atleta B de M0 para M1, M2 e M3 (p < 0,01).
No estudo 2, o objetivo foi interpretar as diferenças em Ln rMSSD e FCrep nos
resultados de cada atleta e averiguar se existem diferenças na recolha de dados através da
utilização de dias isolados ou médias semanais. Foi calculado o rácio entre Ln rMSSD e R-R
para averiguar as diferenças entre os dois atletas. O atleta A apresentou um padrão
condizente com uma situação de saturação parassimpática (ligeira diminuição de Ln rMSSD,
diminuição da FCrep e diminuição de Ln rMSSD:R-R). A atleta B um padrão considerado clássico (diminuição de Ln rMSSD e aumento da FCrep e vice-versa). A utilização de dias
isolados (segunda-feira, quinta-feira e sábado) para recolha de dados de VFC pode originar
resultados absolutos e tendências díspares comparativamente à utilização de médias
semanais.
No estudo 3, o objetivo foi monitorizar um atleta de elite de Ténis durante o
Campeonato Nacional Absoluto de Ténis, através da caracterização dos encontros (variáveis
fisiológicas, psicológicas e observacionais) e avaliações matinais em repouso. Foram
encontradas diferenças entre os 4 encontros nas variáveis das características dos jogos e FC,
e entre os jogos de serviço e jogos de resposta nas variáveis características do jogo e FC
exceto para o jogo 3. Foram encontradas correlações estatisticamente significativas entre as
variáveis duração dos pontos e o tempo de recuperação entre pontos para os encontros 2, (r
= 0,349, p < 0,01), encontro 3, (r = 0,230, p < 0,03) e encontro 4 r (106) = 0,241, p < 0,01.
Encontramos uma correlação para a associação entre a duração dos encontros e o tempo de
jogo efetivo (r = -0,930, p < 0,05); entre a duração dos encontros e a RPE (r = 0,916, p < 0,05),
e para a associação entre a RPE e o tempo de jogo efetivo (r = -0,977, p < 0,05). Encontrámos
diferenças na FC antes do início do encontro 4 (jogo da final) e os outros encontros anteriores.
Nos períodos de recuperação sentado do encontro 4 verificou-se uma diminuição do
SNSIndex nos dois últimos períodos ao contrário da FC que continuou a aumentar
ligeiramente.
Palavras-chave: Ténis, variabilidade da frequência cardíaca, perceção do esforço, carga de
treino, recuperação
Athlete monitoring is one of the critical aspects in the optimization and individualization of the training and recovery process. The monitoring of heart rate (HR), heart rate variability (HRV), perceived exertion (RPE) and stress and recovery questionnaire for athletes (RestQ Sport) through non-invasive data, provides important contributions to this process. This dissertation aims to investigate elite tennis athletes in context of training and competition through 3 studies. In study 1, the objective was to monitor the preparation period of two tennis elite athletes during 4 (athlete A, male, 28 years old) and 3 (athlete B, female, 21 years old) training micro cycles (M), through physiological (HR and HRV), psychological (RestQ-Sport and RPE) and training characterization, training load (CT) and training volume (VT) variables. HRV analysis through weekly averages was done using the smallest worthwhile change (SWC) and the standard error to establish a trivial variation zone. The main results were: For athlete A, the greatest variations were found from M2 to M3, in the natural logarithm of the square root of the mean sum of squares of the differences between adjacent R-R intervals (Ln rMSSD), - 4.05% SWC; in resting heart rate (HRrest), +0.68%; in parasympathetic nervous system index (PNSIndex), -14.4% and sympathetic nervous system index (SNSIndex), -12.8%. For athlete B, it was from M1 to M2 that the largest variations were seen, Ln rMSSD, +14.4%; HRrest, - 14.8%; PNSIndex, 373.8% and SNSIndex, 300%. The associations between training load (CT) and training volume (VT) and RPE, HRrest, Ln rMSSD and the time interval between consecutive beats (R-R) were investigated. For athlete A, RPE correlated with VT (r = 0.692, p < 0.01), HRrest r = 0.546; p < 0.01 and R-R r = -0.999, p < 0.01; HRrest with VT, r = 0.546; p < 0.01 and with R-R, r = -0.999, p < 0.01. For athlete B the RPE correlated with VT, r = 0.811, p < 0.01; for Ln rMSSD and R-R, r = 0.829, p < 0.01; for HRrest and Ln rMSSD, r = -0.848, p < 0.01; For Fcrep and R-R, r = -0.994, p < 0.01. For the responses to the RestQ-Sport, differences were found in athlete A, in the recovery index from M0 to M3 and from M0 to M4 (p < 0.01 and p < 0.03), and for athlete B, from M0 to M1 (p < 0.01). For the stress index, in athlete A from M0 to M3 and from M0 to M4 (p < 0.02) and for athlete B from M0 to M1, M2 and M3 (p < 0.01). In study 2, the goal was to interpret the differences in Ln rMSSD and HRrest in each athlete's results and to ascertain if there were differences in data collection by using single days or weekly averages. The ratio between Ln rMSSD and R-R was calculated to ascertain the differences between the two athletes. Athlete A presented a pattern consistent with a parasympathetic saturation situation (slight decrease in Ln rMSSD, decrease in HRrest and decrease in Ln rMSSD:R-R). Athlete B a pattern considered classic (decreased Ln rMSSD and increased HRrest and vice versa). The use of single days (Monday, Thursday, and Saturday) for HRV data collection may lead to different absolute results and trends compared to the use of weekly averages. In study 3, the objective was to monitor an elite tennis athlete during the Absolute National Tennis Championships through characterization of matches (physiological, psychological, and observational variables) and assessments at morning rest. Differences were found between the 4 matches in the variables of game characteristics and HR, and between service and return games in the variables game characteristics and HR except for game 3. Statistically significant correlations were found between the variable’s duration of points and recovery time between points for match 2, (r = 0.349, p < 0.01), match 3, (r = 0.230, p < 0.03) and match 4 r (106) = 0.241, p < 0.01. We found a correlation for the association between match duration and effective playing time (r = -0.930, p < 0.05); between match duration and RPE (r = 0.916, p < 0.05), and for the association between RPE and effective playing time (r = -0.977, p < 0.05). We found differences in HR before the start of match 4 (the final match) and the other previous matches. In the sitting recovery periods of match 4 there was a decrease in SNSIndex in the last two periods unlike HR which continued to increase slightly. Key words: Tennis, heart rate variability, perceived exertion, training load, recovery
Athlete monitoring is one of the critical aspects in the optimization and individualization of the training and recovery process. The monitoring of heart rate (HR), heart rate variability (HRV), perceived exertion (RPE) and stress and recovery questionnaire for athletes (RestQ Sport) through non-invasive data, provides important contributions to this process. This dissertation aims to investigate elite tennis athletes in context of training and competition through 3 studies. In study 1, the objective was to monitor the preparation period of two tennis elite athletes during 4 (athlete A, male, 28 years old) and 3 (athlete B, female, 21 years old) training micro cycles (M), through physiological (HR and HRV), psychological (RestQ-Sport and RPE) and training characterization, training load (CT) and training volume (VT) variables. HRV analysis through weekly averages was done using the smallest worthwhile change (SWC) and the standard error to establish a trivial variation zone. The main results were: For athlete A, the greatest variations were found from M2 to M3, in the natural logarithm of the square root of the mean sum of squares of the differences between adjacent R-R intervals (Ln rMSSD), - 4.05% SWC; in resting heart rate (HRrest), +0.68%; in parasympathetic nervous system index (PNSIndex), -14.4% and sympathetic nervous system index (SNSIndex), -12.8%. For athlete B, it was from M1 to M2 that the largest variations were seen, Ln rMSSD, +14.4%; HRrest, - 14.8%; PNSIndex, 373.8% and SNSIndex, 300%. The associations between training load (CT) and training volume (VT) and RPE, HRrest, Ln rMSSD and the time interval between consecutive beats (R-R) were investigated. For athlete A, RPE correlated with VT (r = 0.692, p < 0.01), HRrest r = 0.546; p < 0.01 and R-R r = -0.999, p < 0.01; HRrest with VT, r = 0.546; p < 0.01 and with R-R, r = -0.999, p < 0.01. For athlete B the RPE correlated with VT, r = 0.811, p < 0.01; for Ln rMSSD and R-R, r = 0.829, p < 0.01; for HRrest and Ln rMSSD, r = -0.848, p < 0.01; For Fcrep and R-R, r = -0.994, p < 0.01. For the responses to the RestQ-Sport, differences were found in athlete A, in the recovery index from M0 to M3 and from M0 to M4 (p < 0.01 and p < 0.03), and for athlete B, from M0 to M1 (p < 0.01). For the stress index, in athlete A from M0 to M3 and from M0 to M4 (p < 0.02) and for athlete B from M0 to M1, M2 and M3 (p < 0.01). In study 2, the goal was to interpret the differences in Ln rMSSD and HRrest in each athlete's results and to ascertain if there were differences in data collection by using single days or weekly averages. The ratio between Ln rMSSD and R-R was calculated to ascertain the differences between the two athletes. Athlete A presented a pattern consistent with a parasympathetic saturation situation (slight decrease in Ln rMSSD, decrease in HRrest and decrease in Ln rMSSD:R-R). Athlete B a pattern considered classic (decreased Ln rMSSD and increased HRrest and vice versa). The use of single days (Monday, Thursday, and Saturday) for HRV data collection may lead to different absolute results and trends compared to the use of weekly averages. In study 3, the objective was to monitor an elite tennis athlete during the Absolute National Tennis Championships through characterization of matches (physiological, psychological, and observational variables) and assessments at morning rest. Differences were found between the 4 matches in the variables of game characteristics and HR, and between service and return games in the variables game characteristics and HR except for game 3. Statistically significant correlations were found between the variable’s duration of points and recovery time between points for match 2, (r = 0.349, p < 0.01), match 3, (r = 0.230, p < 0.03) and match 4 r (106) = 0.241, p < 0.01. We found a correlation for the association between match duration and effective playing time (r = -0.930, p < 0.05); between match duration and RPE (r = 0.916, p < 0.05), and for the association between RPE and effective playing time (r = -0.977, p < 0.05). We found differences in HR before the start of match 4 (the final match) and the other previous matches. In the sitting recovery periods of match 4 there was a decrease in SNSIndex in the last two periods unlike HR which continued to increase slightly. Key words: Tennis, heart rate variability, perceived exertion, training load, recovery
Descrição
Orientação: Raquel Maria Santos Barreto Sajara Madeira
Palavras-chave
DOUTORAMENTO EM EDUCAÇÃO FÍSICA E DESPORTO, DESPORTO, SPORT, EDUCAÇÃO FÍSICA, PHYSICAL EDUCATION, FREQUÊNCIA CARDÍACA, HEART RATE, TÉNIS, TENNIS, RECUPERAÇÃO FÍSICA, PHYSICAL RECOVERY