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A special issue of International Journal of Environmental Research and Public Health (ISSN 1660-4601). This special issue belongs to the section "Exercise and Health-Related Quality of Life".

Deadline for manuscript submissions: 31 August 2024 | Viewed by 8025

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Special Issue Editor

Prof. Dr. Giovanna Zimatore

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Guest Editor

Department of Theoretical and Applied Sciences, eCampus University, Via Isimbardi, 10, 22060 Novedrate, Italy
Interests: metabolic threshold; sport, physical activity and health; heart rate variability; nonlinear dynamic; wearable devices; overtraining; fatigue; chronic stress

Special Issue Information

Dear Colleagues,

The metabolic thresholds detection is fundamental in order to assess the individual physical activities related to weight loss in obese subjects or to a performance improvement of athletes.

Specific incremental physical exercises are requested to detected metabolic thresholds by ventilatory Cardiopulmonary exercise test (CPET) or metabolic variables (Blood Lactate).

Energy consumption and physiological response to different physical exercises are largely studied.

The large diffusion of wearable devices that suit better the cardiovascular monitoring during physical activities have increased the role of heart rate monitoring on this context. Although, the physiological response of the cardiovascular system referable to improvement in cardiovascular fitness is complex mechanism and not yet completely explained. The non linear methods applied on heart rate time series have encouraged researchers to apply these methodology where the medical and paramedical staff to have direct access to parameters pertaining to an automated and personalized approach in athletic performance.

This Special Issue is aimed at providing selected contributions to address this topic with a particular emphasis on how to transfer experimental interventions and findings to practical on field applications.

The keywords listed below provide an outline of some of the possible areas of interest.

Prof. Dr. Giovanna Zimatore
Guest Editor

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Keywords

metabolic threshold
sport, physical activity and health
heart rate variability
nonlinear dynamic
wearable devices
overtraining
fatigue
chronic stress

Published Papers (4 papers)

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Research

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10 pages, 608 KiB

Open AccessArticle

Patients with Adolescent Idiopathic Scoliosis Have Higher Metabolic Cost during High-Intensity Interval Training

by Rufina Wing-Lum Lau, Rachel Lai-Chu Kwan, Jack Chun-Yiu Cheng, Stanley Sai-Chuen Hui and Tsz-Ping Lam

Int. J. Environ. Res. Public Health 2023, 20(3), 2155; https://doi.org/10.3390/ijerph20032155 - 25 Jan 2023

Cited by 2 | Viewed by 1974

Abstract

Background: Patients with adolescent idiopathic scoliosis (AIS) are found to have a lower level of physical activity, and may have reduced exercise capacity due to spinal deformity. Previous study showed the benefits of high-intensity interval training (HIIT), named E-Fit, which is specifically designed for patients with AIS to improve musculoskeletal health and psychological well-being. To optimize the beneficial effects of training, the current study aimed to investigate the appropriate exercise intensity and metabolic demand in patients with AIS when performing E-Fit. Methods: In all, 22 female subjects, 10 diagnosed with AIS and 12 gender-matched healthy controls, aged between 10 and 16 years, were recruited. Subjects were instructed to perform two trials of a seven min E-Fit. Breath-by-breath gas exchange parameters including oxygen consumption (VO₂), heart rate (HR) and the rate of perceived exertion (PRE) were measured during exercise. Demographic data and clinical features of AIS and body composition were obtained. Metabolic demand between AIS and control groups was compared using MANOVA with covariates adjustment. Results: Patients with AIS had an earlier onset of menarche (p = 0.01), higher visceral adipose tissue (p = 0.04) and percentage body fat (p = 0.03) as compared to controls. Patients with AIS showed a significantly higher adjusted means of VO₂ average in both the first (p = 0.014) and second trials (p = 0.011) of E-Fit. The adjusted mean of the highest measured VO₂ was higher than healthy controls and reached statistical significance in the second trial (p = 0.004). Both the AIS and control group exercised at a similar percentage of VO₂ peak (64.26% vs. 64.60%). Conclusion: Patients with AIS showed higher oxygen consumption during E-Fit than heathy controls, which might indicate a higher metabolic cost. Patients with AIS could carry out exercise at a moderate exercise intensity similar to that of healthy controls, but special considerations in designing an exercise program, such as frequent rest intervals, would be useful to avoid fatigue among patients with AIS. Full article

(This article belongs to the Special Issue Research on Physical Activity and Exercise Physiology)

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11 pages, 1526 KiB

Open AccessArticle

Automatic Detection of Aerobic Threshold through Recurrence Quantification Analysis of Heart Rate Time Series

by Giovanna Zimatore, Cassandra Serantoni, Maria Chiara Gallotta, Laura Guidetti, Giuseppe Maulucci and Marco De Spirito

Int. J. Environ. Res. Public Health 2023, 20(3), 1998; https://doi.org/10.3390/ijerph20031998 - 21 Jan 2023

Cited by 2 | Viewed by 1590

Abstract

During exercise with increasing intensity, the human body transforms energy with mechanisms dependent upon actual requirements. Three phases of the body’s energy utilization are recognized, characterized by different metabolic processes, and separated by two threshold points, called aerobic (AerT) and anaerobic threshold (AnT). These thresholds occur at determined values of exercise intensity(workload) and can change among individuals. They are considered indicators of exercise capacities and are useful in the personalization of physical activity plans. They are usually detected by ventilatory or metabolic variables and require expensive equipment and invasive measurements. Recently, particular attention has focused on AerT, which is a parameter especially useful in the overweight and obese population to determine the best amount of exercise intensity for weight loss and increasing physical fitness. The aim of study is to propose a new procedure to automatically identify AerT using the analysis of recurrences (RQA) relying only on Heart rate time series, acquired from a cohort of young athletes during a sub-maximal incremental exercise test (Cardiopulmonary Exercise Test, CPET) on a cycle ergometer. We found that the minima of determinism, an RQA feature calculated from the Recurrence Quantification by Epochs (RQE) approach, identify the time points where generic metabolic transitions occur. Among these transitions, a criterion based on the maximum convexity of the determinism minima allows to detect the first metabolic threshold. The ordinary least products regression analysis shows that values of the oxygen consumption VO₂, heart rate (HR), and Workload correspondent to the AerT estimated by RQA are strongly correlated with the one estimated by CPET (r > 0.64). Mean percentage differences are <2% for both HR and VO₂ and <11% for Workload. The Technical Error for HR at AerT is <8%; intraclass correlation coefficients values are moderate (≥0.66) for all variables at AerT. This system thus represents a useful method to detect AerT relying only on heart rate time series, and once validated for different activities, in future, can be easily implemented in applications acquiring data from portable heart rate monitors. Full article

(This article belongs to the Special Issue Research on Physical Activity and Exercise Physiology)

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12 pages, 1475 KiB

Open AccessArticle

The Autonomic Imbalance of Myocardial Ischemia during Exercise Stress Testing: Insight from Short-Term Heart Rate Variability Analysis

by Ping-Yen Lin, Cheng-Ting Tsai, Chang Francis Hsu, Ying-Hsiang Lee, Han-Ping Huang, Chun-Che Huang, Lawrence Yu-Min Liu, Long Hsu, Ten-Fang Yang and Po-Lin Lin

Int. J. Environ. Res. Public Health 2022, 19(22), 15096; https://doi.org/10.3390/ijerph192215096 - 16 Nov 2022

Viewed by 1533

Abstract

Exercise stress testing (EST) has limited power in diagnosing obstructive coronary artery disease (CAD). The heart rate variability (HRV) analysis might increase the sensitivity of CAD detection. This study aimed to evaluate the correlation between short-term HRV and myocardial ischemia during EST, including the acceleration, maximum, and recovery stages of heart rate (HR). The HRV during EST from 19 healthy (RHC) subjects and 35 patients with CAD (25 patients with insignificant CAD (iCAD), and 10 patients with significant CAD (sCAD)) were compared. As a result, all HRV indices decreased at the maximum stage and no significant differences between iCAD and sCAD were found. The low-frequency power of heart rate signal (LF) of the RHC group recovered relatively quickly from the third to the sixth minutes after maximum HR, compared with that of the sCAD group. The relative changes of most HRV indices between maximum HR and recovery stage were lower in the sCAD group than in the RHC group, especially in LF, the standard deviation of all normal to normal intervals (SDNN), and the standard deviation in the long axis direction of the Poincaré plot analysis (SD2) indices (p < 0.05). The recovery slope of LF was significantly smaller in the sCAD group than in the RHC group (p = 0.02). The result suggests that monitoring short-term HRV during EST provides helpful insight into the cardiovascular autonomic imbalance in patients with significant CAD. The relative change of autonomic tone, especially the delayed sympathetic recovery, could be an additional marker for diagnosing myocardial ischemia. Full article

(This article belongs to the Special Issue Research on Physical Activity and Exercise Physiology)

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Review

Jump to: Research

24 pages, 3684 KiB

Open AccessReview

Detecting Metabolic Thresholds from Nonlinear Analysis of Heart Rate Time Series: A Review

by Giovanna Zimatore, Maria Chiara Gallotta, Matteo Campanella, Piotr H. Skarzynski, Giuseppe Maulucci, Cassandra Serantoni, Marco De Spirito, Davide Curzi, Laura Guidetti, Carlo Baldari and Stavros Hatzopoulos

Int. J. Environ. Res. Public Health 2022, 19(19), 12719; https://doi.org/10.3390/ijerph191912719 - 5 Oct 2022

Cited by 5 | Viewed by 2329

Abstract

Heart rate time series are widely used to characterize physiological states and athletic performance. Among the main indicators of metabolic and physiological states, the detection of metabolic thresholds is an important tool in establishing training protocols in both sport and clinical fields. This paper reviews the most common methods, applied to heart rate (HR) time series, aiming to detect metabolic thresholds. These methodologies have been largely used to assess energy metabolism and to identify the appropriate intensity of physical exercise which can reduce body weight and improve physical fitness. Specifically, we focused on the main nonlinear signal evaluation methods using HR to identify metabolic thresholds with the purpose of identifying a method which can represent a useful tool for the real-time settings of wearable devices in sport activities. While the advantages and disadvantages of each method, and the possible applications, are presented, this review confirms that the nonlinear analysis of HR time series represents a solid, robust and noninvasive approach to assess metabolic thresholds. Full article

(This article belongs to the Special Issue Research on Physical Activity and Exercise Physiology)

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