Initial Investigation of Athletes’ Electrocardiograms Acquired by Wearable Sensors during the Pre-exercise Phase

Abstract

Aim: The aim of this study is to support large-scale prevention programs fighting sport-related sudden cardiac death by providing a set of electrocardiographic features representing a starting point in the development of normal reference values for the pre-exercise phase. Background: In people with underlying, often unknown, cardiovascular abnormalities, increased cardiovascular load during exercise can trigger sport-related sudden cardiac death. Prevention remains the only weapon to contrast sport-related sudden cardiac death. So far, no reference values have been proposed for electrocardiograms of athletes acquired with wearable sensors in the pre-exercise phase, consisting of the few minutes immediately before the beginning of the training session. Objective: To perform an initial investigation of athletes’ electrocardiograms acquired by wearable sensors during the pre-exercise phase. Methods: The analyzed electrocardiograms, acquired through BioHarness 3.0 by Zephyr, belong to 51 athletes (Sport Database and Cycling Database of the Cardiovascular Bioengineering Lab of the Università Politecnica delle Marche, Italy). Preliminary values consist of interquartile ranges of six electrocardiographic features which are heart rate, heart-rate variability, QRS duration, ST level, QT interval, and corrected QT interval. Results: For athletes 35 years old or younger, preliminary values were [72;91]bpm, [26;47]ms, [85;104]ms, [-0.08;0.08]mm, [326;364]ms and [378;422]ms, respectively. For athletes older than 35 years old, preliminary values were [71;94]bpm, [16;65]ms, [85;100]ms, [-0.11;0.07]mm, [330;368]ms and [394;414]ms, respectively. Conclusion: Availability of preliminary reference values could help identify those athletes who, due to electrocardiographic features out of normal ranges, are more likely to develop cardiac complications that may lead to sport-related sudden cardiac death.

Progress Planning Method of Strength Quality Training of Volleyball Players Based on Data Mining

“…In recent years, research on human muscle strength has primarily focused on the development of human muscle strength test methods and instruments. However, data analysis and data processing of test results have remained in general analysis and statistical processing, correlation comparison, and inspection [18]. Volleyball training focuses on improving players' explosive strength, flexibility, and exceptional endurance.…”

Sport?Sicuro! A Graphical User Interface for Continuous Cardiovascular Monitoring while Playing Sport Based on Heart Rate and Heart-Rate Variability

“…Finally, an algorithm for automatic detection of training phases is applied to segment HR series in resting and exercise phases [3]. HR and HRV parameters are extracted and assessed from the HR series according to [1,[6][7][8]. Table 1 shows prevention indexes along with their definition and range of normality; Table 2 shows the performance indexes along with their definition.…”

“…Colours help the identification of training phases and acceleration (green band) and deceleration (light blue band) on the HR series plot [3]. Automatic analysis is based on feature definition provided in literature [1,[6][7][8], and thus cannot be changed by the user. Parameter settings can be changed according to user's preference or to acquisition settings of wearable HR recorders.…”

“…The analysis of HR and HRV while training requires several information among which demographic data, anthropometric data and the training context [1,3]. Further highly trained athletes suffer exercise-related physiological adaptation which could lead to different normative values for interpretation of HR and HRV parameters compared to general population [7]. Due to the complexity of physiological phenomena affecting HR and HRV during physical exercise with different level of psychophysical stress, it is difficult for athletes and trainers to interpret measures provided by commercial wearable technologies.…”

Smartwatch ECG Tracing and Ischemic Heart Disease: ACS Watch Study

“…Therefore, an everyday tool such as the watch has become “smart” (127.5 M units sold in 2021) [1], and its key application is the heart rate measurement through ECG tracing. Some devices are already approved for atrial fibrillation detection [2] and have been tested for athletes pre-exercise electrocardiographic evaluation [3]. However, their role in ischemic heart disease (IHD), leading cause of cardiovascular death, has not been appropriately tested.…”