Arto J. Hautala

Physiological Background of the Loss of Fractal Heart Rate Dynamics

Background—Altered fractal heart rate (HR) dynamics occur during various disease states, but the physiological background of abnormal fractal HR behavior is not well known. We tested the hypothesis that the fractal organization of human HR dynamics is determined by the balance between sympathetic and vagal outflow. Methods and Results—A short-term fractal scaling exponent (&agr;1) of HR dynamics, analyzed by the detrended fluctuation analysis (DFA) method, and the high-frequency (HF) and low-frequency (LF) spectral components of R-R intervals (0.15 to 0.4 Hz; n=13), along with muscle sympathetic nervous activity (MSNA) from the peroneus nerve (n=11), were assessed at rest and during cold face and cold hand immersion in healthy subjects. During cold face immersion, HF power increased (from 6.9±1.3 to 7.6±1.2 ln ms2, P<0.01), as did MSNA (from 32±17 to 44±14 bursts/100 heartbeats, P<0.001), and LF/HF ratio decreased (P<0.01). Cold hand immersion resulted in a similar increase in MSNA (from 34±17 to 52±19 bursts/100 heartbeats, P<0.001) but a decrease in HF spectral power (from 7.0±1.3 to 6.5±1.1 ln ms2, P<0.05) and an increase in the LF/HF ratio (P<0.05). The fractal scaling index &agr;1 decreased in all subjects (from 0.85±0.27 to 0.67±0.30, P<0.0001) during cold face immersion but increased during cold hand immersion (from 0.77±0.22 to 0.97±0.20, P<0.01). Conclusions—The fractal organization of human HR dynamics is determined by a delicate interplay between sympathetic and vagal outflow, with the breakdown of fractal HR behavior toward more random dynamics occurring during coactivation of sympathetic and vagal outflow.

Individual responses to aerobic exercise: The role of the autonomic nervous system

It is well established that regular aerobic exercise training reduces all-cause mortality and improves a number of health outcomes. However, a marked heterogeneity in the training-induced changes, e.g. in terms of aerobic fitness, has been observed in healthy human subjects, even with highly standardized training programs. Mean improvements in aerobic fitness, expressed as maximal oxygen consumption, have been about 10-15% of the baseline values, but the training-induced changes have ranged from almost none to a 40% increase. The exact nature of the mechanisms responsible for this heterogeneity in response to regular aerobic exercise is not well known. In this review, we consider evidence of the association between the autonomic nervous system (ANS), aerobic fitness and aerobic training-induced changes in fitness. Results of recent studies support the hypothesis that assessment of ANS functioning includes important information concerning acute and chronic physiological processes before, during and after aerobic exercise training stimulus. Moreover, we show that daily assessment of ANS activity could serve as an indicator of appropriate physiological condition for aerobic training.

Human isometric force production and electromyogram activity of knee extensor muscles in water and on dry land

Abstract This study was designed to determine trial-to-trial and day-to-day reproducibility of isometric force and electromyogram activity (EMG) of the knee extensor muscles in water and on dry land as well as to make comparisons between the two training conditions in muscle activity and force production. A group of 20 healthy subjects (12 women and 8 men) were tested three times over 2 weeks. A measurement session consisted of recordings of maximal and submaximal isometric knee extension force with simultaneous recording of surface EMG from the vastus medialis, vastus lateralis and biceps femoris muscles. To ensure identical measurement conditions the same patient elevator chair was used in both the dry and the wet environment. Intraclass correlation coefficients (ICC) and coefficients of variation (CV) showed high trial-to-trial (ICC=0.95–0.99, CV=3.5%–11%) and day-to-day reproducibility (ICC=0.85–0.98, CV=11%–19%) for underwater and dry land measurements of force and EMG in each muscle during maximal contractions. The day-to-day reproducibility for submaximal contractions was similar. The interesting finding was that underwater EMG amplitude decreased significantly in each muscle during maximal (P < 0.01–P < 0.001) and submaximal contractions (P < 0.05–P < 0.001). However, the isometric force measurements showed similar values in both wet and dry conditions. The water had no disturbing effect on the electrodes as shown by slightly lowered interelectrode resistance values, the absence of artefacts and low noise levels of the EMG signals. It was concluded that underwater force and EMG measurements are highly reproducible. The significant decrease of underwater EMG could have electromechanical and / or neurophysiological explanations.

Short-term correlation properties of R-R interval dynamics at different exercise intensity levels.

Methods based on non‐linear heart rate (HR) dynamics have been suggested to probe features in HR behaviour that are not easily detected by the traditional HR variability indices. This study tested the hypothesis that analysis of correlation properties of R–R intervals provides useful information on HR fluctuation during exercise. High‐ (HF) and low‐frequency (LF) spectral components and a short‐term scaling exponent (α1) of HR variability, were analysed for nine healthy subjects at rest, during incremental and steady‐state exercise, during atropine infusion and during incremental exercise after atropine administration. During the incremental exercise test α1 increased from rest to an intensity level of ∼40% of (from 1·07 ± 0·24 to 1·50 ± 0·25, P<0·001) and thereafter decreased linearly until the end of exercise (from 1·50 ± 0·25 to 0·38 ± 0·10, P<0·001). Atropine infusion increased the scaling exponent α1 value from 0·91 ± 0·23 to 1·37 ± 0·31 (P<0·001). During exercise after atropine infusion, a linear reduction was observed in the scaling exponent α1 from 1·37 ± 0·23 to 0·25 ± 0·08 (P<0·001). Analogous changes in α1 were seen during long‐term steady‐state exercise compared to incremental exercise. Conventional HR variability indices did not show any significant changes during exercise at high exercise intensity levels. α1 correlated with the LF/HF ratio at rest (r = 0·90, P<0·001), but the correlation was weaker after atropine (r = 0·71, P<0·05) and during exercise (e.g. r = 0·33, P = NS at the level of 40% of ). In conclusion, incremental exercise test until exhaustion results in bidirectional changes in correlation properties of R–R interval dynamics. These changes can be explained by the intensity of vagal and sympathetic input to the sinus node during the different intensity levels of exercise. Changes in α1 values can be detected also in high intensity levels, when the conventional measures of HR variability can not be applied.

Recovery Pattern of Baroreflex Sensitivity after Exercise

PURPOSE To test the association between exercise mode and the recovery pattern of baroreflex sensitivity (BRS) after exercise. METHODS The study population included healthy male subjects (N = 12, age: 31 +/- 3 yr). Four different interventions were performed in a randomized order: 1) aerobic exercise session on a bicycle ergometer, 2) light resistance exercise session, 3) heavy resistance exercise session, and 4) control intervention with no exercise. All interventions lasted 40 min. R-R intervals and continuous blood pressure were measured before (10 min) and 30-180 min after the interventions. BRSLF was calculated by the transfer function method from the low-frequency band (LF, 0.04-0.15 Hz) of the R-R intervals and systolic blood pressure spectra. RESULTS BRSLF had blunted until 30 min after aerobic and light resistance exercise (11.1 +/- 4.3 and 10.0 +/- 3.6 vs 17.5 +/- 7.0 ms.mm Hg(-1), P = 0.002 for both, compared with the control intervention, respectively). However, BRSLF was significantly blunted until 60 min after heavy resistance exercise (9.3 +/- 2.3 vs 15.1 +/- 4.7 ms.mm Hg(-1), P = 0.005, compared with the control intervention). The high-frequency power of R-R intervals (0.15-0.4 Hz) was significantly reduced, and the LF power of systolic blood pressure oscillation was significantly augmented 30 min after heavy resistance exercise (P < 0.01 for both), whereas both indices were restored to the control level by 30 min after aerobic and light resistance exercise. CONCLUSION BRS after acute exercise is associated with exercise intensity, showing relatively rapid recovery after aerobic and light resistance exercise and delayed recovery after heavy resistance exercise. The delayed BRS pattern after heavy resistance exercise is regulated by delicate interplay between the withdrawal of vagal outflow and the probably increased sympathetic vasomotor tone documented by measurements of heart rate and blood pressure variability.

Novel spectral indexes of heart rate variability as predictors of sudden and non-sudden cardiac death after an acute myocardial infarction

Background. Various indexes of 24‐hour heart rate variability (HRV) have been able to predict all‐cause mortality after an acute myocardial infarction (AMI), but their value in predicting specific modes of cardiac death has been limited. Aim. The aim of this study was to assess the role of two novel spectral indexes of HRV as predictors of either sudden (SCD) or non‐sudden cardiac death after an AMI. Method. We used two novel methods of spectral analysis of HRV: 1) the high‐frequency (HF) spectral component, Vindex, calculated as an average HF power from the most linear portion of HF power versus the R‐R interval regression curve, and 2) the prevalent low‐frequency oscillation of heart rate (PLF). Vindex, conventional HRV measures, and PLF were analyzed from 24‐hour Holter recordings of 590 patients with a recent AMI. Results. During the mean follow‐up of 39±14 months, SCD occurred in 3% (n = 17) and non‐sudden cardiac death in 5% (n = 28) of the patients. In univariate analysis, Vindex was the most potent predictor of SCD (RR: 6.0, 95% CI: 1.7–20.7, P<0.01), also remaining the most powerful predictor of SCD after adjustment for clinical variables and ejection fraction (RR: 4.2, 95% CI: 1.2–15.2, P<0.05). PLF was a potent predictor of non‐sudden cardiac death (RR: 13.9, 95% CI: 5.9–32.5, P<0.001), but it did not predict SCD. Conclusions. Novel spectral HRV analysis methods, Vindex and PLF, provide significant information of the risk of the specific mode of death after an AMI.

Determination of hydrodynamic drag forces and drag coefficients on human leg/foot model during knee exercise

OBJECTIVE The purpose of this laboratory experiment was to measure hydrodynamic drag forces in barefoot/hydro-boot conditions and accordingly, to determine the coefficients of drag on human leg/foot model during simulated knee extension-flexion exercise. DESIGN The prosthesis of the human lower leg was set in a water tank and connected into an isokinetic force dynamometer to measure resistive forces during knee motion. BACKGROUND Quantifying resistance for aquatic exercises has been a challenge in hydrotherapy. The use of models of foot/leg provides a practical method to calculate coefficients of drag and to estimate resistance for rehabilitation purposes in musculoskeletal and amputee patients. METHODS The dynamometer produced constant angular velocities of 250 degrees /s, 270 degrees /s and 300 degrees /s to the prosthesis. The baseline for measurements was performed in barefoot condition. A hydro-boot was used to study effects of increased frontal area (30%) of the leg on drag forces and coefficients. RESULTS The maximal drag force values were 61 N (300 degrees /s) in barefoot and 270 N (270 degrees /s) in hydro-boot condition. Related drag coefficient values during the range of motion were from 0.3 to 0.1 and from 1 to 0.8, respectively. CONCLUSIONS Drag force and related drag coefficient were highest during the early part of extension (150-140 degrees flexion) as the model was opposing the lift forces with the influence of water resistance. The effect of velocity was remarkable on drag forces but minimal on drag coefficient values. RelevanceThe drag forces and coefficients of this experiment can be clinically utilised to calculate hydrodynamic forces to develop progressive knee exercise programs as well as to design of prosthesis for amputee patients.

Physical activity and heart rate variability measured simultaneously during waking hours

Heart rate (HR) variability (HRV) during ambulatory recordings may be affected by individual differences in daily physical activity (PA). However, the influence of various levels of PA on different measures of HRV is not exactly known. We examined the association between simultaneously measured HRV and objective PA data obtained with an accelerometer during waking hours among 45 healthy adults. Bouts of PA were identified from minute-by-minute accelerometer data as metabolic equivalent (METs) values and calculated as mean METs for 30 min. HRV was analyzed concurrently. Within-individual correlation analyses and sign tests were performed to study the relationships between various HRV indexes and PA. The mean PA time was 15:44 +/- 1:01 h, and the mean MET was 1.91 +/- 0.14. HR and sample entropy, but not the other measures of HRV, had a significant relationship with PA, as shown by both correlation analyses (r = 0.64, P = 0.021, and r = -0.55, P = 0.022, respectively) and sign tests (P < 0.0001 for both). Beat-to-beat R-R interval fluctuation expressed as SD1 also demonstrated a significant relation to PA according to the sign test (P = 0.037) and a trend of association according to the correlation analysis (r = -0.40, P = 0.129). The complexity measure of HRV, in addition to average HR and the short-term index of HRV (SD1), is significantly influenced by the level of PA during ambulatory conditions. Long-term HRV indexes remained relatively stable at various activity levels, making them the most robust indexes for the assessment of cardiac autonomic function during free-running ambulatory conditions.

Sprint interval running increases insulin sensitivity in young healthy subjects.

High intensity cycling training increases oxidative capacity in skeletal muscles and improves insulin sensitivity. The present study compared the effect of eight weeks of sprint interval running (SIT) and continuous running at moderate intensity (CT) on insulin sensitivity and cholesterol profile in young healthy subjects (age 25.2 ± 0.7; VO2max 49.3 ± 1.2 ml·kg−1·min−1). SIT and CT increased maximal oxygen uptake by 5.3 ± 1.8 and 3.8 ± 1.6%, respectively (p < 0.05 for both). Oral glucose tolerance test (OGTT) was performed before and 60 h after the last training session. SIT, but not CT, reduced glucose area under curve and improved HOMA β-cell index (p < 0.05). Insulin area under curve did not decrease significantly in any group. SIT, but not CT, reduced LDL and total cholesterol. In conclusion, sprint interval running improves insulin sensitivity and cholesterol profile in healthy subjects, and sprint interval running may be more effective to improve insulin sensitivity than continuous running at moderate intensity.

Sympatho‐vagal interaction in the recovery phase of exercise

Reciprocal autonomic regulation occurs during incremental exercise. We hypothesized that sympatho‐vagal interplay may become altered after exercise because of the differences in recovery patterns of autonomic arms. The cardiac vagal activity was assessed by measurement of beat‐to‐beat R–R interval oscillations using a Poincaré plot method (SD1), and muscle sympathetic nervous activity (MSNA) was measured from peroneus nerve by a microneurography technique during and after exercise in 16 healthy subjects. Autonomic regulation was compared between the rest and after exercise (3·5 ± 1·0 min after exercise) at equal heart rates (HR). SD1 was at the equal level at the recovery phase (40 ± 21 ms) compared to the resting condition (38 ± 16 ms, P = ns) at comparable HR (57 ± 10 for both). MSNA was higher at the recovery phase (40 ± 19 burst per 100 heartbeats) than at rest (25 ± 13 burst per 100 heartbeats, P<0·0001). The difference of MSNA activity between rest and late recovery phase had a strong positive correlation with the difference in SD1 (r = 0·78, P<0·001) at equal HRs. Subjects who have a higher sympathetic activity in the recovery phase of exercise have a more augmented cardiac vagal activity resulting in an accentuated sympatho‐vagal outflow. The altered autonomic interaction observed here may partly explain the clustering of various cardiovascular events to the recovery phase of exercise.