This study attempted to determine the accuracy of measuring heart rate by radial artery palpation in elderly individuals. Elderly (ELD; n = 26) and young (Y; n = 21) individuals completed 3 intensity levels of exercise on a treadmill, each carried out on a separate day. Participants determined their heart rate by palpating the radial artery (PR) after exercise. In ELD, there were significant differences between PR and electrocardiogram (ECG; p = .007). Heart-rate errors at each intensity of exercise were 7.2 ± 12.5, 6.6 ± 15.7, and 10.1 ± 16.5 beats/min. There were no differences in PR and ECG in Y. Fingertip sensitivity was significantly lower in ELD than in Y. A significant, negative correlation existed (r = -.56, n = 26) between heart-rate error and fingertip sensitivity in ELD. These data suggest that self-conducted PR by elderly individuals fails to accurately estimate heart rate. This appears to result from lessened vibrotactile sensitivity in the fingers.
Search Results
Age-Related Decreases in Finger Sensitivity Can Produce Error in Palpated Heart-Rate Determination
Nobuo Takeshima, William F. Brechue, Setsuko Ueya, and Kiyoji Tanaka
Heart-Rate Variability in Elite Synchronized Swimmers
Mònica Solana-Tramunt, Jose Morales, Bernat Buscà, Marina Carbonell, and Lara Rodríguez-Zamora
50% of the routine time, 3 oxygen is mobilized from finite stores in the lungs, blood, and other tissues and the cardiovascular diving response restricts blood flow to selected regions and reduces heart rate (HR) and cardiac output. 3 Elite SS athletes perform 2 training sessions (TS) per day, and
Estimating Resting Core Temperature Using Heart Rate
David P. Looney, Mark J. Buller, Andrei V. Gribok, Jayme L. Leger, Adam W. Potter, William V. Rumpler, William J. Tharion, Alexander P. Welles, Karl E. Friedl, and Reed W. Hoyt
to use, fairly scalable). A number of methods have been developed over the years to predict CT from less invasive measures (e.g., heart rate, skin temperature, respiration rate) ( Buller et al., 2013 ; Niedermann et al., 2014 ; Richmond, Davey, Griggs, & Havenith, 2015 ) as well as methods to
Heart Rate Responses and Fluid Balance of Competitive Cross-Country Hang Gliding Pilots
Darren P. Morton
Purpose:
To evaluate the physiological challenges of competitive cross-country hang gliding.
Methods:
Seventeen experienced male pilots (age = 41 ± 9 y; mean ± SD) were fitted with a monitor that recorded heart rate and altitude at 0.5 Hz throughout a competitive fight. Fluid losses were evaluated by comparing pilot pre- and postfight mass.
Results:
The pilots’ displacement was 88.4 ± 43.7 km in 145.5 ± 49.4 min. Mean fight altitude was 1902 ± 427 m (range = 1363-2601 m) with a maximum altitude of 2925 ± 682 m (1870-3831 m). The mean in-fight heart rate of the pilots was 112 ± 11 bpm (64 ± 6% predicted HRmax). For all except one subject, heart rate was highest while launching (165 ± 12 bpm, 93 ± 7% predicted HRmax), followed by landing (154 ± 13 bpm, 87 ± 7% predicted HRmax). No statistically significant relationship was observed between heart rate during the launch and reported measures of state anxiety. Heart rate was inversely related (P < .01) to altitude for all pilots except one. Fluid loss during the fight was 1.32 ± 0.70 L, which approximated 0.55 L/h, while mean in-fight fluid consumption was 0.39 ± 0.44 L. Six pilots consumed no fluid during the fight.
Conclusions:
Even among experienced pilots, high heart rates are more a function of state anxiety than physical work demand. Fluid losses during fight are surprisingly moderate but pilots may still benefit from attending to fluid balance.
Salivary Cortisol, Heart Rate, and Blood Lactate Responses During Elite Downhill Mountain Bike Racing
Billy Sperlich, Silvia Achtzehn, Mirijam Buhr, Christoph Zinner, Stefan Zelle, and Hans-Christer Holmberg
Purpose:
This study aimed to quantify the intensity profile of elite downhill mountain bike races during competitions.
Methods:
Seventeen male downhill racers (22 ± 5 y; 185.1 ± 5.3 cm; 68.0 ± 3.9 kg; VO2peak: 59.4 ± 4.1 mL·min·kg−1) participated in the International German Downhill Championships in 2010. The racers’ peak oxygen uptake and heart rate (HR) at 2 and 4 mmol·L−1 blood lactate (HR2 and HR4), were assessed during an incremental laboratory step test (100 W, increase 40 W every 5 min). During the races, the HR was recorded and pre- and postrace blood lactate concentrations as well as salivary cortisol levels were obtained.
Results:
During the race, the absolute time spent in the “easy” intensity zone was 23.3 ± 6.8 s, 24.2 ± 12.8 s (HR2–HR4) in the “moderate” zone, and 151.6 ± 18.3 s (>HR4) in the “hard” zone. Eighty percent of the entire race was accomplished at intensities >90% HRpeak. Blood lactate concentrations postrace were higher than those obtained after the qualification heat (8.0 ± 2.5 mmol·L−1 vs 6.7 ± 1.8 mmol·L−1, P < .01). Salivary levels of cortisol before the competition and the qualification heat were twice as high as at resting state (P < .01).
Conclusions:
This study shows that mountain bike downhill races are conducted at high heart rates and levels of blood lactate as well as increased concentration of salivary cortisol as marker for psycho-physiological stress.
Assessing Overreaching With Heart-Rate Recovery: What Is the Minimal Exercise Intensity Required?
Yann Le Meur, Martin Buchheit, Anaël Aubry, Aaron J Coutts, and Christophe Hausswirth
Purpose:
Faster heart-rate recovery (HRR) after high to maximal exercise (≥90% of maximal heart rate) has been reported in athletes suspected of functional overreaching (f-OR). This study investigated whether this response would also occur at lower exercise intensity.
Methods:
Responses of HRR and rating of perceived exertion (RPE) were compared during an incremental intermittent running protocol to exhaustion in 20 experienced male triathletes (8 control subjects and 13 overload subjects led to f-OR) before and immediately after an overload training period and after a 1-wk taper.
Results:
Both groups demonstrated an increase in HRR values immediately after the training period, but this change was very likely to almost certainly larger in the f-OR group at all running intensities (large to very large differences, eg, +16 ± 7 vs +3 ± 5 beats/min, in the f-OR and control groups at 11 km/h, respectively). The highest between-groups differences in changes in HRR were reported at 11 km/h (13 ± 4 beats/min) and 12 km/h (10 ± 6 beats/min). A concomitant increase in RPE at all intensities was reported only in the f-OR group (large to extremely large differences, +2.1 ± 1.5 to +0.7 ± 1.5 arbitrary units).
Conclusion:
These findings confirm that faster HRR does not systematically predict better physical performance. However, when interpreted in the context of the athletes’ fatigue state and training phase, HRR after submaximal exercise may be more discriminant than HRR measures taken after maximal exercise for monitoring f-OR. These findings may be applied in practice by regularly assessing HRR after submaximal exercise (ie, warm-up) for monitoring endurance athletes’ responses to training.
Energy Expenditure in Playground Games in Primary School Children Measured by Accelerometer and Heart Rate Monitors
Jorge Cañete García-Prieto, Vicente Martinez-Vizcaino, Antonio García-Hermoso, Mairena Sánchez-López, Natalia Arias-Palencia, Juan Fernando Ortega Fonseca, and Ricardo Mora-Rodriguez
The aim of this study was to examine the energy expenditure (EE) measured using indirect calorimetry (IC) during playground games and to assess the validity of heart rate (HR) and accelerometry counts as indirect indicators of EE in children´s physical activity games. 32 primary school children (9.9 ± 0.6 years old, 19.8 ± 4.9 kg · m-2 BMI and 37.6 ± 7.2 ml · kg-1 · min-1 VO2max). Indirect calorimetry (IC), accelerometry and HR data were simultaneously collected for each child during a 90 min session of 30 playground games. Thirty-eight sessions were recorded in 32 different children. Each game was recorded at least in three occasions in other three children. The intersubject coefficient of variation within a game was 27% for IC, 37% for accelerometry and 13% for HR. The overall mean EE in the games was 4.2 ± 1.4 kcals · min-1 per game, totaling to 375 ± 122 kcals/per 90 min/session. The correlation coefficient between indirect calorimetry and accelerometer counts was 0.48 (p = .026) for endurance games and 0.21 (p = .574) for strength games. The correlation coefficient between indirect calorimetry and HR was 0.71 (p = .032) for endurance games and 0.48 (p = .026) for strength games. Our data indicate that both accelerometer and HR monitors are useful devices for estimating EE during endurance games, but only HR monitors estimates are accurate for endurance games.
Heart-Rate Acceleration Is Linearly Related to Anaerobic Exercise Performance
Noah M.A. d’Unienville, Maximillian J. Nelson, Clint R. Bellenger, Henry T. Blake, and Jonathan D. Buckley
In order to prescribe appropriate training loads to improve exercise performance, one must know how an athlete is responding to a change in load. The maximal rate of heart-rate increase (rHRI) is a marker of heart-rate (HR) acceleration that has been shown to change in response to acute 1 and
Training Prescription Guided by Heart-Rate Variability in Cycling
Alejandro Javaloyes, Jose Manuel Sarabia, Robert Patrick Lamberts, and Manuel Moya-Ramon
training adaptation is cardiac autonomic regulation (CAR). 8 This is supported by Lamberts et al, 9 who showed that cyclists who adapted well to high intensity training (HIT) had a faster heart rate recovery (HRR) response than cyclists who did not responds well to the HIT. In general, a decreased
Reliability and Sensitivity of Nocturnal Heart Rate and Heart-Rate Variability in Monitoring Individual Responses to Training Load
Olli-Pekka Nuuttila, Santtu Seipäjärvi, Heikki Kyröläinen, and Ari Nummela
Heart rate (HR) and HR variability (HRV) either during exercise or at rest are commonly monitored in sport to estimate the current recovery and training status. 1 In terms of recovery, since HRV is a surrogate of cardiac parasympathetic nervous system activity, 2 it is a potential marker due to
