New Wearable Heart Rate Monitor for Contact Sports and Its Potential to Change Training Load Management

2019 ◽  
Author(s):  
Yuichi Higuchi ◽  
Naoki Saijo ◽  
Takako Ishihara ◽  
Tomohiro Usui ◽  
Takahiro Murakami ◽  
...  
Keyword(s):  
Heart Rate ◽  
Training Load ◽  
Load Management ◽  
Heart Rate Monitor ◽  
Contact Sports

scholarly journals Heart Rate Monitor Instead of Ablation? Atrioventricular Nodal Re-Entrant Tachycardia in a Leisure-Time Triathlete: 6-Year Follow-Up

Diagnostics ◽  
2020 ◽  
Vol 10 (6) ◽  
pp. 391 ◽  
Author(s):  
Robert Gajda
Keyword(s):  
Heart Rate ◽  
Diagnostic Tool ◽  
Leisure Time ◽  
Submaximal Exercise ◽  
Training Load ◽  
Heart Rate Monitor ◽  
Heart Rate Monitors ◽  
Amateur Athlete ◽  
Electrocardiogram Ecg

This study describes a triathlete with effort-provoked atrioventricular nodal re-entrant tachycardia (AVNRT), diagnosed six years ago, who ineffectively controlled his training load via heart-rate monitors (HRM) to avoid tachyarrhythmia. Of the 1800 workouts recorded for 6 years on HRMs, we found 45 tachyarrhythmias, which forced the athlete to stop exercising. In three of them, AVNRT was simultaneously confirmed by a Holter electrocardiogram (ECG). Tachyarrhythmias occurred in different phases (after the 2nd–131st minutes, median: 29th minute) and frequencies (3–8, average: 6.5 times/year), characterized by different heart rates (HR) (150–227 beats per minute (bpm), median: 187 bpm) and duration (10–186, median: 40 s). Tachyarrhythmia appeared both unexpectedly in the initial stages of training as well as quite predictably during prolonged submaximal exercise—but without rigid rules. Tachyarrhythmias during cycling were more intensive (200 vs. 162 bpm, p = 0.0004) and occurred later (41 vs. 10 min, p = 0.0007) than those during running (only one noticed but not recorded during swimming). We noticed a tendency (p = 0.1748) towards the decreasing duration time of tachycardias (2014–2015: 60 s; 2016–2017: 50 s; 2018–later: 37 s). The amateur athlete tolerated the tachycardic episodes quite well and the ECG test and echocardiography were normal. In the studied case, the HRM was a useful diagnostic tool for detecting symptomatic arrhythmia; however, no change in the amount, phase of training, speed, or duration of exercise-stimulated tachyarrhythmia was observed.

Validation of a widely used heart rate monitor to track steps in older adults

2019 ◽  
Vol 59 (10) ◽  
Author(s):  
Stefanie Rüdiger ◽  
Tim Stuckenschneider ◽  
Vera Abeln ◽  
Christopher D. Askew ◽  
Petra Wollseiffen ◽  
...  
Keyword(s):  
Older Adults ◽  
Heart Rate ◽  
Heart Rate Monitor

Comparison between photoplethysmographic heart rate monitor from Polar Vantage M and Polar V800 with H10 chest strap while running on a treadmill: Validation of the Polar Precision PrimeTM photoplestimographic system

2020 ◽  
pp. 175433712097665
Author(s):  
Emilio J Ruiz-Malagón ◽  
Santiago A Ruiz-Alias ◽  
Felipe García-Pinillos ◽  
Gabriel Delgado-García ◽  
Victor M Soto-Hermoso
Keyword(s):  
Heart Rate ◽  
Random Error ◽  
Maximum Speed ◽  
Systematic Bias ◽  
Long Distance ◽  
Time Intervals ◽  
Heart Rate Monitor ◽  
Calibration Time

Chest bands have been the most used device to monitor heart rate during running. However, some runners feel uncomfortable with the use of bands due to the friction and pressure exerted on the chest. Thus, the aim of this study was to determine if the photoplethysmography (PPG) system Polar Precision Prime used in the Polar Vantage M watch could replace chest bands (Polar V800-H10) to monitor heart rate with the same precision. A group of 37 people, middle-distance and long-distance professional runners, participated in this study. The submaximal speed was determined using 50% of the participants’ maximum speed in the height of their season. The Polar Vantage M reported high correlation ( r > 0.84) and high ICC (ICC > 0.86) when comparing its heart rate monitor with the Polar V800 synchronised with H10 chest strap during recording intervals of more than 2 min. The systematic bias and random error were very small (<1 bpm), especially for the 600 s recording interval (0.26 ± 5.10 bpm). Nevertheless, the error increased for 10 s (−5.13 ± 9.20 bpm), 20 s (−8.65 ± 12.60 bpm) and 30 s (−10.71 ± 14.99 bpm) time intervals. In conclusion, the PPG Polar Precision Prime included in the Polar Vantage M demonstrates that it could be a valid alternative to chest bands for monitoring heart rate while running, taking into account some usage considerations, good strap adjustment and an initial calibration time during the first 2–3 min.

scholarly journals Quantifying Accelerations and Decelerations in Elite Women Soccer Players during Regular In-Season Training as an Index of Training Load

Sports ◽  
2021 ◽  
Vol 9 (8) ◽  
pp. 109
Author(s):  
Tom Douchet ◽  
Allex Humbertclaude ◽  
Carole Cometti ◽  
Christos Paizis ◽  
Nicolas Babault
Keyword(s):  
Heart Rate ◽  
Perceived Exertion ◽  
Training Load ◽  
Soccer Players ◽  
Unit Recording ◽  
Fitness Level ◽  
Total Distance ◽  
Load Monitoring ◽  
Soccer Training ◽  
Stress Fatigue

Accelerations (ACC) and decelerations (DEC) are important and frequent actions in soccer. We aimed to investigate whether ACC and DEC were good indicators of the variation of training loads in elite women soccer players. Changes in the training load were monitored during two different selected weeks (considered a “low week” and a “heavy week”) during the in-season. Twelve elite soccer women playing in the French first division wore a 10-Hz Global Positioning System unit recording total distance, distance within speed ranges, sprint number, ACC, DEC, and a heart rate monitor during six soccer training sessions and rated their perceived exertion (RPE). They answered the Hooper questionnaire (sleep, stress, fatigue, DOMS) to get an insight of their subjective fitness level at the start (Hooper S) and at the end of each week (Hooper E). A countermovement jump (CMJ) was also performed once a week. During the heavy week, the training load was significantly greater than the low week when considering number of ACC >2 m·s−2 (28.2 ± 11.9 vs. 56.1 ± 10.1, p < 0.001) and number of DEC < −2 m·s−2 (31.5 ± 13.4 vs. 60.9 ± 14.4, p < 0.001). The mean heart rate percentage (HR%) (p < 0.05), RPE (p < 0.001), and Hooper E (p < 0.001) were significantly greater during the heavy week. ACC and DEC showed significant correlations with most outcomes: HR%, total distance, distance per min, sprint number, Hooper index of Hooper E, DOMS E, Fatigue E, RPE, and session RPE. We concluded that, for elite women soccer players, quantifying ACC and DEC alongside other indicators seemed to be essential for a more complete training load monitoring. Indeed, it could lead to a better understanding of the reasons why athletes get fatigued and give insight into neuromuscular, rather than only energetic, fatigue.

Internal Training Load Affects Day-After-Pretraining Perceived Fatigue in Female Volleyball Players

2021 ◽  
pp. 1-7
Author(s):  
Alexandru Nicolae Ungureanu ◽  
Corrado Lupo ◽  
Gennaro Boccia ◽  
Paolo Riccardo Brustio
Keyword(s):  
Heart Rate ◽  
Muscle Soreness ◽  
Perceived Exertion ◽  
Well Being ◽  
Delayed Onset Muscle Soreness ◽  
Training Load ◽  
Rating Of Perceived Exertion ◽  
Mixed Effect ◽  
Delayed Onset ◽  
Volleyball Players

Purpose: The primary aim of this study was to evaluate whether the internal (session rating of perceived exertion [sRPE] and Edwards heart-rate-based method) and external training load (jumps) affect the presession well-being perception on the day after (ie, +22 h), according to age and tactical position, in elite (ie, Serie A2) female volleyball training. Methods: Ten female elite volleyball players (age = 23 [4] y, height = 1.82 [0.04] m, body mass = 73.2 [4.9] kg) had their heart rate monitored during 13 team (115 individual) training sessions (duration: 101 [8] min). Mixed-effect models were applied to evaluate whether sRPE, Edwards method, and jumps were correlated (P ≤ .05) to Hooper index factors (ie, perceived sleep quality/disorders, stress level, fatigue, and delayed-onset muscle soreness) in relation to age and tactical position (ie, hitters, central blockers, opposites, and setters). Results: The results showed a direct relationship between sRPE (P < .001) and presession well-being perception 22 hours apart, whereas the relationship was the inverse for Edwards method internal training load. Age, as well as the performed jumps, did not affect the well-being perception of the day after. Finally, central blockers experienced a higher delayed-onset muscle soreness than hitters (P = .003). Conclusions: Findings indicated that female volleyball players’ internal training load influences the pretraining well-being status on the day after (+ 22 h). Therefore, coaches can benefit from this information to accurately implement periodization in a short-term perspective and to properly adopt recovery strategies in relation to the players’ well-being status.

Heart rate responses of two breeds of four-gaited horses to a standardised field gaited test

2012 ◽  
Vol 8 (1) ◽  
pp. 41-46 ◽  
Author(s):  
H.C. Manso Filho ◽  
H.E.C.C.C. Manso ◽  
K.H. McKeever ◽  
S.R.R. Duarte ◽  
J.M.G. Abreu
Keyword(s):  
Heart Rate ◽  
Energy Expenditure ◽  
Negative Correlation ◽  
Repeated Measures ◽  
Recovery Period ◽  
T Test ◽  
Heart Rate Monitor ◽  
Positive Correlation ◽  
Gaited Horses ◽  
Athletic Horse

In order to understand how gaited horses use their energy during exercise, a standardised field gaited test (SFGT) was developed to assess energy expenditure of four beat gaited horses independently of size, sex or breed. This work aimed at developing such an SFGT, using as main measurement parameter the heart rate (HR) of horses during the SFGT performance. Thirty-one four beat gaited horses were evaluated and divided into two groups: FIT (conditioned) and UNFIT (not conditioned). Horses were submitted to the SFGT and their heart rates were measured with a heart rate monitor as follows: right after being mounted, at the beginning of pre-test (HRSADDLE); at 5, 10, 15, 20, 25 and 30 minutes of four beat gait dislocation; and at 15 minutes after the recovery period (T+15). Maximum HR (HRMAX); HR percentage over 150 beats per minute (HR%≯150), HR percentage over 170 beats per minute (HR%≯170), and average HR during the four beat gait stage (HRM@M) of SFGT were calculated. Results were analysed by ANOVA for repeated measures. Where significant differences were observed, ‘T’ test was performed and significance was set at 5%. The FIT group presented HRMAX, HR+15, HRM@M, HR%≯150 and HR%≯170 rates lower (P<0.05) than the UNFIT group. It was noted that there was a negative correlation between fitness and HRMAX (R=−0.67; P<0.001) and a positive correlation between HRMAX and HR+15 (R=0.60; P<0.001) when comparing the FIT to the UNFIT horses. In conclusion, during the SFGT, the FIT group was more efficient in energy expenditure than the UNFIT group, based on the results observed for the significantly lower HRs during the SFGT. It is relevant to note that the SFGT developed and used in this research, which was easily reproduced and accurate, was able to detect and confirm important adaptations related to fitness in the athletic horse.

Competition-Based Heart Rate, Training Load, and Time Played Above 85% Peak Heart Rate in NCAA Division I Women's Basketball

2018 ◽  
Vol Publish Ahead of Print ◽  
Author(s):  
Gabriel J. Sanders ◽  
Brian Boos ◽  
Jessica Rhodes ◽  
Roger O. Kollock ◽  
Corey A. Peacock
Keyword(s):  
Heart Rate ◽  
Ncaa Division I ◽  
Training Load ◽  
Division I ◽  
Peak Heart Rate ◽  
Women's Basketball

scholarly journals Heart Rate monitor based on IP networking

2018 ◽  
Vol 210 ◽  
pp. 01006
Author(s):  
Miguel G. Molina ◽  
Priscila E. Garzón ◽  
Carolina J. Molina ◽  
Juan X. Nicola
Keyword(s):  
Heart Rate ◽  
Real Time ◽  
Electronic Devices ◽  
Vital Signs ◽  
Well Being ◽  
Heart Rate Monitor ◽  
Ip Address ◽  
Health Concept ◽  
New Applications ◽  
Threat Situation

With the uprising of Internet of Things (IoT) networks, new applications have taken advantage of this new concept. Having all devices and all people connected 24/7 have several advantages in a variated amount of disciplines. One of them is medicine and the e-health concept. The possibility of having a real time lecture of the vital signs of people can prevent a live threat situation. This paper describes the realization of a device capable of measuring the heart rate of a person and checking for abnormalities that may negatively affect the patient’s well-being. This project will make use of electronic devices known as microcontrollers, specifically from the Arduino family, enabling us to capture data, and, with the help of a network card and a RJ-45 cable, transfer it to a PC and visualize the heart rate in real time over its assigned IP address.

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