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تحليل تغير معدل ضربات القلب (HRV) في عالم الرياضة: الوسيلة والتطبيق العملي والرؤية المستقبلية

يمثل تغير معدل ضربات القلب (HRV) الاختلافات المتواجدة بين ضربات القلب المتتابعة (الفاصل الزمني بين كل ضربة وأخرى) مع مرور الوقت. وتختفي تلك الاختلافات بين ضربات القلب المتتابعة نتيجة لخلل وظيفي مستقل قد يرتبط بأمراض عصبية أو قلبية وعائية أو نفسية. تتسم الحالة النفسية المرتبطة بتغير معدلات ضربات القلب بالتعقيد وتأثرها بالهرمونات الجائلة ومستقبلات الضغط والمستقبلات الكيميائية والوارد العضلي. هذا ويقوم الجهاز العصبي المستقل (ANS) من خلال قنوات الجهاز العصبي السمبثاوي والجهاز العصبي الباراسمبثاوي بتنظيم وظيفة الأعضاء الداخلية والجهاز القلبي الوعائي. يؤدي نشاط الجهاز السمبثاوي إلى زيادة انقباض عضلة القلب (مع ارتفاع معدل ضربات القلب) بينما يكون لتنبيه الجهاز الباراسيمبثاوي (المبهمي) تأثير عكسي (انخفاض معدل ضربات القلب) _ENREF_4. يؤدي أي مصدر للإجهاد (سواء كان نفسي أو بدني أو مرضي) إلى التسبب في اضطراب الجهاز العصبي المستقل، ويليه تباعاً اضطراب تغير معدل ضربات القلب. وقد يؤدي اختلال التوازن طويل الأجل بين الجهاز العصبي السيمبثاوي والجهاز العصبي الباراسيمبثاوي إلى إعاقة الأداء السليم لبعض وظائف الجسم وكذلك الحال بالنسبة لأداء الرياضيين. وبناء عليه، بدأ منذ العقدين المنصرمين الاهتمام بتحليل تغير معدل ضربات القلب والعمل به كوسيلة غير جائرة لتقييم تفاعلات الجسم إزاء أحمال التدريب وأساليب التعافي ومتلازمة إفراط التدريب (OTS). أثناء التدريب، ينخفض تغير معدل ضربات القلب (فواصل زمنية أقصر بين كل ضربة والأخرى) ويرتفع معدل ضربات القلب نتيجة لنشاط الجهاز العصبي السيمبثاوي المتزايد ونشاط الجهاز العصبي الباراسيمبثاوي الموهن. ولا يقتصر الأمر فحسب على وجود فواصل زمنية أقصر بين الضربة والأخرى، بل إنها تصبح في الوقت ذاته غير متساوية (انخفاض تغير الضربة – الضربة). تتسبب أحمال التدريب الأعلى في الإصابة بمستوى أعلى من اضطراب الجهاز العصبي المستقل وخلل التوازن sympathovagal. ويعد عودة خلل توازن sympathovagal إلى مستوى الاستتباب بمثابة العنصر الحاسم في عملية التعافي والتي يجب أن يهيمن عليها النشاط الباراسيمبثاوي، وذلك على الرغم من إمكانية تلخيصها بأن حالة التعافي المثلى عادة ما تتصف بهيمنة الجهاز الباراسيمبثاوي (المبهمي) على الجهاز العصبي المستقل بغض النظر عن توقيت ذلك من اليوم. تؤدي جلسات التدريب مرتفعة الكثافة طويلة الأمد إلى انخفاض العنصر الباراسيمبثاوي لتغير معدل ضربات القلب تدريجياً، والذي سيزيد خلال فترة الراحة. هذا بينما يسلك العنصر السيمبثاوي مسلكاً عكسياً. بصفة العموم، تعمل إعادة تنشيط  النشاط الباراسيمبثاوي لتغير معدل ضربات القلب في أسرع وقت ممكن ليعود إلى المستوى السابق للتمرين على تحسين عملية تعافي الرياضيين إلى حد كبير. هذا بيد أن العجز عن إعادة معلمات تغير معدل ضربات القلب إلى المستوى السابق للتدريب أو المستوى الأمثل في التوقيت المناسب يعتبر اضطراب مزمن في نشاط الجهاز العصبي المستقل مما قد يؤدي بدوره إلى فرط التدريب. تعد متلازمة فرط التدريب نتاجاً لخلل التوازن طويل الأجل بين عامل الضغط (الداخلي و/أو الخارجي) وفترات التعافي. هذا وتشير الكثير من الأدلة إلى أن خلل التوازن المستقل بين قناتي الجهاز العصبي المستقل (السيمبثاوي والباراسيمبثاوي) يحدث نتيجة لمتلازمة فرط التدريب. وعلى وجه العموم، تم تسجيل نوعين من متلازمة فرط التدريب: النوع السيمبثاوي والباراسيمبثاوي من فرط التدريب مع وجود خصائص فسيولوجية لكل منهما. هذا وتتسم المراحل المبكرة من إعاقة الأداء بالهيمنة السيمباثوية للجهاز العصبي المستقل أثناء الراحة والمحددة عادة كحالة وصول زائد. في حال استمرار حالة الوصول الزائد لفترات زمنية ممتدة، سوف يصاب الرياضي بمتلازمة فرط التدريب وهيمنة الجهاز العصبي الباراسيمبثاوي المستقل. وفي نهاية الأمر، يجب أن نؤكد على أن من بين أوجه قصور تقنية تحليل تغير معدل ضربات القلب هو الطبيعة غير المستقرة وغير المباشرة لإشارات تغير معدل ضربات القلب. ومع ذلك، مازالت تقنيات التحليل المتقدمة تخضع للتطوير المتواصل لتحسين تحليل طبيعة إشارات تغير معدل ضربات القلب العشوائية.

Heart rate variability analysis in sport

Utility, practical implementation and future perspectives

 

– Written by Bojan Makivic and Pascal Bauer, Austria

 

Heart rate variability (HRV) represents variations between consecutive heart beats (beat to beat or R-R interval) over time (Figure 1). This beat to beat variation in heart rhythm is considered normal and even desirable. Disappearance of variations between consecutive heart beats is a result of autonomic dysfunction which can be associated with neurological, cardiovascular and psychiatric disease states1. There is a large body of evidence reporting that higher variability of heart rhythm is associated with reduced mortality 2,3, improved quality of life4 and better physical fitness5. The most common use of HRV analysis is in risk prediction and prevention of heart failure6,7.

 

Interestingly, in ancient China, HRV was known to physician Shu-he Wang (265 to 317 AD) who described heart rhythm as an indicator of disease: “if the pattern of the heart beat becomes as regular as the tapping of a woodpecker or the dripping of rain from the roof, the patient will be dead in 4 days”8.

 

The physiological background of HRV is complex and affected by circulating hormones, baroreceptors, chemoreceptors and muscle afferents. An important factor which influences HRV is respiratory sinus arrhythmia – the natural variation in heart rate (HR) that occurs during breathing5. During inspiration, HR increases whereas expiration is characterised by a decrease in HR. The autonomic nervous system (ANS) through sympathetic (SNS) and parasympathetic (PNS) pathways regulates the function of internal organs and the cardiovascular system1,5. Sympathetic activity increases cardiac contractility and HR, whereas parasympathetic (vagal) stimulation reduces HR5,9. Any source of stress (psychological, physical or illness) will provoke disturbance in the ANS and consequently in HRV. The long-term presence of imbalance between sympathetic and parasympathetic tone can impair the performance of athletes.

 

The analysis of HRV in sport has become established and recognised in the past 2 decades as a non-invasive method for evaluation of the body’s reaction to training loads, recovery methods and overtraining syndrome (OTS). In the last 5 years, innovations in wireless technology have significantly increased the number of devices on the market which are using HRV indices to control and manage the training processes of athletes.

 

INDICES (PARAMETERS) OF HRV

The most common methods for analysis of HRV are time domain, frequency domain (power spectral) and Poincaré plot (scatter gram) analysis. The simplest method to analyse HRV is time domain analysis, which represents basic mathematical and statistical measures such as root mean square of the differences and standard deviation of adjacent NN (normal to normal) intervals (Table 1). NN intervals generally represent adjacent beat to beat intervals that differ more than 50ms. They originate from sinus node depolarization 10. Power spectral analysis represents distribution of variation in HR as a function of frequency 11 (Table 1). The common frequencies of HRV encompass very low (VLF), low (LF) and high frequency (HF) components (Figure 2). Poincaré analysis plots each R-R interval against previous one in a graphical representation of ANS activity (Figure 2). All aforementioned analysis methods consist of parameters which provide information about sympathetic and parasympathetic modulation i.e. the balance between them (Table 1).

 

HRV DURING AND AFTER EXERCISE (INDICATORS OF STRESS/TRAINING LOAD)

During exercise HRV is reduced (shorter R-R intervals) and HR is increased as a result of augmented SNS and attenuated PNS activity. Not only are the intervals between R-R peaks shorter, they become more uniform (reduced R-R variability). The relationship between sympathetic and parasympathetic activity during exercise depends directly on training intensity. During physical activity, sympathetic nerves can increase cardiac output to 2 to 3 times the resting value 12. One of the often researched topics in terms of HRV during exercise is analysis of anaerobic (lactate or ventilatory) threshold during incremental test to exhaustion13-15. It looks promising that in the future a non-invasive method, such as HRV analysis, could eventually replace lactate analysis and therefore decrease the cost and time of anaerobic threshold testing.

 

Caution should be taken when interpreting HRV analysis during exercise. The HF component (PNS activity) of spectral analysis is highly influenced by respiration dynamics. Due to this fact, at high exercise intensities (>90% VO2 max) increased breathing frequency will cause an increase in vagal contribution (higher PNS activity) caused purely by the mechanical properties of the heart and not neural contribution of the ANS16,17. This means that actual SNS activity at higher exercise intensities will be masked by PNS activity as a result of a higher frequency of respiration. Therefore, during an incremental test to exhaustion, the subject has to be instructed to maintain a stable respiration rate as much as possible.

 

Training load

Distribution of training loads is a fundamental component of periodisation. The elements which comprise training load are training volume and intensity. Interplay between these two elements will define the total training load. Higher training loads will cause a greater degree of ANS disturbance and sympathovagal imbalance12,18. Post-exercise HRV analysis appears to be a valuable indicator to evaluate variations in performance level and can indirectly reflect training loads18-20. There is evidence that HRV parameters are highly correlated with intensity and volume of exercise and are inversely related to the level of training load21.

 

HRV AND RECOVERY

On the assumption that physical activity causes stress (a stimulus), the body will respond with a stress reaction on different physiological levels. In addition to a stress reaction, adaptation processes occur during the recovery period. If the magnitude of the stress stimulus (e.g. training load) is high enough (overload principle) to evoke a reaction of the body, then the response will be proportional to the stress level and, as a result, greater training effects will be accomplished (adaptation).

 

In order to reach higher performance levels, it is essential to understand that well-designed and integrated rest periods are of great importance. Recovery after training is considered an integral part of training methodology. There is no improvement in performance if there is a lack of optimal recovery. Problems occur when the demands are so frequent that the body is not able to adapt12. This means that the body will continuously be under sympathetic domination during rest as well as during activity. Every training session can be considered as stress to the body, which in turn causes disturbance of homeostasis and ANS modulation. These changes in ANS activity are manifested by increased sympathetic or/and decreased parasympathetic activity of the ANS and are reflected by HRV parameters12.

 

One crucial aspect of recovery is sleep, during which parasympathetic activity should dominate, however, an optimal recovery state is generally characterised by parasympathetic (vagal) predominance of ANS regardless of time of the day12. There are a variety of parameters which can be used to measure post-exercise recovery (VO2 max, creatine kinase, C-reactive protein, plasma cortisol, blood leukocyte, myeloperoxidase protein level and glutathione status), but these methods are mostly invasive, time consuming and expensive for everyday use22-25. Accordingly, the importance of a non-invasive, easy and affordable method to evaluate recovery is obvious. Thus, HRV technology is being increasingly used to evaluate the status and level of recovery.

 

Long-term high-intensity training sessions gradually decrease the para-sympathetic component of HRV (root mean square of the differences, HF, onestandard deviation parameters), which increases during the rest period26. The sympathetic component demonstrates the opposite tendency (LF and two standard deviation parameters). The reactivation of parasympathetic activity of HRV to pre-exercise levels as quickly as possible significantly improves the recovery process of athletes. Inability to return HRV parameters to pre-exercise or optimal levels in a reasonable time is considered a chronic disturbance in ANS activity, which can lead to overtraining. Today, HRV-based devices and software assist in recovery analysis of athletes, providing easily interpretable data to trainers and athletes. The most common procedure used to evaluate recovery level involves overnight measurement(nocturnal) of HRV, although systems which can assess a quick recovery index (5 minute measurement) are available as well.

 

HRV AND OVERTRAINING

Sometimes the line between optimal performance level and overtraining is very thin. Overtraining syndrome is the result of long-term imbalance between stress (internal and/or external) and recovery periods. There is a large body of evidence implying that significant cardiac autonomic imbalance between the two ANS pathways (sympathetic and parasympathetic) occurs due to overtraining syndrome5,27. In the literature there are conflicting results about ANS modulation in overtrained athletes, with some studies reporting a predominance of sympathetic27,28 and some of parasympathetic autonomic tone29,30 during an overtrained period. These disputed results might be explained by the description of different types of overtraining. Two types of OTS have been reported: sympathetic and parasympathetic overtraining, with each having specific physiological characteristics (Table 2)29,31. Early stages of performance impairment are characterised by sympathetic domination of ANS at rest which is often referred to as an ‘overreaching state’ or ‘short-term overtraining’32, meaning that the disturbance of homeostasis was not high and/or long enough to provoke a chronic overtraining state and therefore the time needed for full recovery of all physiological systems typically encompasses a few days to several weeks33. Increased sympathetic tone is generally observed in sports where higher intensity of exercise dominates34.

 

If the overreaching state (sympathetic autonomic tone domination) continues over a longer period of time, OTS and domination of parasympathetic autonomic tone will develop33. Parasympathetic OTS dominates in sports which are characterised by high training volume34. HRV parameters such as root mean square of the differences and HF reflect parasympathetic activity of ANS whereas standard deviation and LF can be partially used as markers of sympathetic autonomic tone. LF/HF ratio, which represents sympathetic to parasympathetic balance, is markedly increased during the overreaching state, implying that sympathetic autonomic tone is augmented. The reverse effect occurs during the late phase of overreaching where LF/HF ratio decreases (sympathetic activity (LF) decreases and parasympathetic activity (HF) increases). Scattergram (Poincaré plot) analysis provides a clear visual representation of the autonomic imbalance during OTS. OTS will cause the concentration of points in the graph take a more narrow pattern (Figure 3). Today HRV systems are a common part of professional sport organisations due to fact that they reflect the sensitivity of the ANS which can occur during overreaching and overtraining states.

 

LIMITATIONS, IMPROVEMENTS AND FUTURE PERSPECTIVES OF HRV ANALYSIS IN SPORT

HRV analysis has become a widely accepted method for non-invasive evaluation of ANS modulation during and after exercise. Nevertheless, the majority of physiological signals are non-stationary and non-linear in nature. The same is true for ANS-regulated HR. Thus, in order to overcome the aforementioned disadvantages, the signal of recording must contain a minimum of 5 minutes of HRV fluctuation in order to get reliable results from power spectral analysis and scattergram. Moreover, new non-linear HRV analysis techniques are continuously being developed and improved. Recent mathematical algorithm advancements have great potential to enhance the accuracy of HRV analysis.

 

In the last 5 years the number of devices and software programmes/apps using HRV technology has increased exponentially. The current trend in software engineering is to make all wireless sensors for capturing and transmitting of HRV data compatible with smartphones. Hardware and software engineers are continuously improving the accuracy of sensors which record and receive HRV signals (heart rate belts, wireless technologies and protocols), as well as HRV analysis techniques (software, mathematical models). This provides the trainer and athletes quick and easy analysis of HRV data during and after a training workout (training load, recovery and overtraining). In addition, a multidisciplinary approach is required to better understand fluctuations in HR. The true potential of HRV analysis in sport can be only achieved with teams consisting of sport scientists, cardiologists and sport physiologists working together in order to better understand ANS modulation during and after exercise.

 

SUMMARY

Today, HRV can be easily assessed in athletes with the help of portable HRV systems. Those systems include wrist watch monitors, HR belts and smartphones with software to measure R-R intervals. With improved analysis techniques, for optimal and reliable results, a minimum duration of recording of 5 to 10 minutes is recommended. However, if the purpose of measurement is to assess distribution of stress and recovery in the course of the day, longer measurements are required (overnight recovery measurement, daily stress management). In addition, one of the biggest advantages of HRV analysis is that the day-to-day variability of bodily responses to continuous training processes can be assessed with minimum time and effort. No expensive equipment and skilled lab specialists are required.

 

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Bojan Makivic M.Sc.

Sports Therapist Rehabilitation Clinic

ENNS Enns, Austria

 

Pascal Bauer Mag.

Research Associate

Centre for Sports Science and University Sports

University of Vienna

Vienna, Austria

 

Contact: bojan.makivic@rehaenns.at

 

Image by Filipe Oliveira

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