scholarly journals A Trigonometric Projection Method for Overcoming High Intensity Heart Rate Caused Waveform Deformation in Electrocardiogram Biometrics

2021 ◽  
Author(s):  
Tsu-Wang Shen ◽  
Shan-Chun Chang
Keyword(s):  
Heart Rate ◽  
High Intensity ◽  
Correlation Coefficients ◽  
Calibration Method ◽  
Mean Square ◽  
Biometric Technology ◽  
Overall Performance ◽  
Electrocardiogram Signal ◽  
Mean Square Difference ◽  
Electrocardiogram Ecg

Abstract Purpose Although electrocardiogram (ECG) has been proven as a biometric for human identification, applying biometric technology remains challenging with diverse heart rate circumstances in which high intensity heart rate caused waveform deformation may not be known in advance when ECG templates are registered. Methods A calibration method that calculates the ratio of the length of an unidentified electrocardiogram signal to the length of an electrocardiogram template is proposed in this paper. Next, the R peak is used as an axis anchor point of a trigonometric projection (TP) to attain the displacement value. Finally, the unidentified ECG signal is calibrated according to the generated trigonometric value, which corresponds to the trigonometric projection degree of the ratio and the attained displacement measurement. Results The results reveal that the proposed method provides superior overall performance compared with that of the conventional downsampling method, based on the percentage root mean square difference (PRD), correlation coefficients, and mean square error (MSE). Conclusion The curve fitting equation directly maps from the heart rate levels to the TP degree without prior registration information. The proposed ECG calibration method offers a more robust system against heart rate interference when conducting ECG identification.

Bernoulli's Chaotic Map-Based 2D ECG Image Steganography

2019 ◽  
pp. 208-241 ◽  
Author(s):  
Anukul Pandey ◽  
Barjinder Singh Saini ◽  
Butta Singh ◽  
Neetu Sood
Keyword(s):  
Signal Processing ◽  
Chaotic Map ◽  
Image Steganography ◽  
Cover Image ◽  
Ecg Signal ◽  
Mean Square ◽  
Secret Key ◽  
Mean Square Difference ◽  
Electrocardiogram Ecg ◽  
Ecg Steganography

Signal processing technology comprehends fundamental theory and implementations for processing data. The processed data is stored in different formats. The mechanism of electrocardiogram (ECG) steganography hides the secret information in the spatial or transformed domain. Patient information is embedded into the ECG signal without sacrificing the significant ECG signal quality. The chapter contributes to ECG steganography by investigating the Bernoulli's chaotic map for 2D ECG image steganography. The methodology adopted is 1) convert ECG signal into the 2D cover image, 2) the cover image is loaded to steganography encoder, and 3) secret key is shared with the steganography decoder. The proposed ECG steganography technique stores 1.5KB data inside ECG signal of 60 seconds at 360 samples/s, with percentage root mean square difference of less than 1%. This advanced 2D ECG steganography finds applications in real-world use which includes telemedicine or telecardiology.

scholarly journals The Impact of Functional Overreaching on Post-exercise Parasympathetic Reactivation in Runners

2021 ◽  
Vol 11 ◽  
Author(s):  
Clint R. Bellenger ◽  
Rebecca L. Thomson ◽  
Kade Davison ◽  
Eileen Y. Robertson ◽  
Jonathan D. Buckley
Keyword(s):  
Heart Rate ◽  
Root Mean Square ◽  
Time Trial ◽  
Exercise Heart Rate ◽  
Mean Square ◽  
Post Exercise ◽  
Parasympathetic Reactivation ◽  
Mean Square Difference ◽  
The Impact ◽  
Heavy Training

While post-exercise heart rate (HR) variability (HRV) has been shown to increase in response to training leading to improvements in performance, the effect of training leading to decrements in performance (i.e., overreaching) on this parameter has been largely ignored. This study evaluated the effect of heavy training leading to performance decrements on sub-maximal post-exercise HRV. Running performance [5 km treadmill time-trial (5TTT)], post-exercise HRV [root-mean-square difference of successive normal R-R intervals (RMSSD)] and measures of subjective training tolerance (Daily Analysis of Life Demands for Athletes “worse than normal” scores) were assessed in 11 male runners following 1 week of light training (LT), 2 weeks of heavy training (HT) and a 10 day taper (T). Post-exercise RMSSD was assessed following 5 min of running exercise at an individualised speed eliciting 85% of peak HR. Time to complete 5TTT likely increased following HT (ES = 0.14 ± 0.03; p < 0.001), and then almost certainly decreased following T (ES = −0.30 ± 0.07; p < 0.001). Subjective training tolerance worsened after HT (ES = −2.54 ± 0.62; p = 0.001) and improved after T (ES = 2.16 ± 0.64; p = 0.004). In comparison to LT, post-exercise RMSSD likely increased at HT (ES = 0.65 ± 0.55; p = 0.06), and likely decreased at T (ES = −0.69 ± 0.45; p = 0.02). A moderate within-subject correlation was found between 5TTT and post-exercise RMSSD (r = 0.47 ± 0.36; p = 0.03). Increased post-exercise RMSSD following HT demonstrated heightened post-exercise parasympathetic modulation in functionally overreached athletes. Heightened post-exercise RMSSD in this context appears paradoxical given this parameter also increases in response to improvements in performance. Thus, additional measures such as subjective training tolerance are required to interpret changes in post-exercise RMSSD.

Eleven Years’ Monitoring of the World’s Most Successful Male Biathlete of the Last Decade

2020 ◽  
pp. 1-6
Author(s):  
Laurent Schmitt ◽  
Stéphane Bouthiaux ◽  
Grégoire P. Millet
Keyword(s):  
Heart Rate ◽  
High Frequency ◽  
Spectral Power ◽  
Mean Square ◽  
Training Volume ◽  
World Cup ◽  
High Intensity Training ◽  
Low Intensity ◽  
Mean Square Difference ◽  
Intensity Training

Purpose: To report the changes in the training characteristics, performance, and heart-rate variability (HRV) of the world’s most successful male biathlete of the last decade. Method: During the analyzed 11-year (2009–2019) period, the participant won 7 big crystal globes, corresponding to the winner of the International Biathlon Union World Cup. The training characteristics are reported as yearly volume (in hours) of low-intensity training (LIT), moderate- and high-intensity training, and speed and strength training. Performance was quantified by the number of World Cup top-3 positions per season. HRV was expressed as low- and high-frequency spectral power (in milliseconds squared), root-mean-square difference of successive R–R interval (in milliseconds), and heart rate (in beats per minute). Results: The training volume increased from 530 to ∼700 hours per year in 2009–2019, with a large polarization in training intensity distribution (ie, LIT 86.3% [2.9%]; moderate-intensity training 3.4% [1.5%]; high-intensity training 4.0% [0.7%]; strength 6.3% [1.6%]). The number of top-3 positions increased from 2 to 24–26 in 2009–2018 but decreased to 6 in 2019. The mean supine values in the root-mean-square difference of successive R–R interval and high-frequency spectral power divided by heart rate increased until 2015, which were stable over 2016–2018 but decreased in 2019. The number of top-3 positions was related to the total (r = .66, P = .02) and LIT (r = .92, P < .001) volume and to several markers of supine parasympathetic activity. Conclusion: The improvement in performance of the participant was mainly determined by the progressive increase in training volume, especially performed at low intensity, and was correlated to parasympathetic activity markers. This case study confirms the effectiveness of the training method, with a large amount of LIT in an elite endurance athlete, and of regular HRV monitoring.

scholarly journals Assessment of Ultra-Short Heart Variability Indices Derived by Smartphone Accelerometers for Stress Detection

Sensors ◽  
2019 ◽  
Vol 19 (17) ◽  
pp. 3729 ◽  
Author(s):  
Landreani ◽  
Faini ◽  
Martin-Yebra ◽  
Morri ◽  
Parati ◽  
...  
Keyword(s):  
Heart Rate ◽  
Mental Stress ◽  
Cardiac Activity ◽  
Mean Square ◽  
Stress Detection ◽  
Short Term ◽  
Reaction Forces ◽  
The Mean ◽  
Electrocardiogram Ecg ◽  
Induced Reaction

Body acceleration due to heartbeat-induced reaction forces can be measured as mobile phone accelerometer (m-ACC) signals. Our aim was to test the feasibility of using m-ACC to detect changes induced by stress by ultra-short heart rate variability (USV) indices (standard deviation of normal-to-normal interval—SDNN and root mean square of successive differences—RMSSD). Sixteen healthy volunteers were recruited; m-ACC was recorded while in supine position, during spontaneous breathing at rest conditions (REST) and during one minute of mental stress (MS) induced by arithmetic serial subtraction task, simultaneous with conventional electrocardiogram (ECG). Beat occurrences were extracted from both ECG and m-ACC and used to compute USV indices using 60, 30 and 10s durations, both for REST and MS. A feasibility of 93.8% in the beat-to-beat m-ACC heart rate series extraction was reached. In both ECG and m-ACC series, compared to REST, in MS the mean beat duration was reduced by 15% and RMSSD decreased by 38%. These results show that short term recordings (up to 10 s) of cardiac activity using smartphone’s accelerometers are able to capture the decrease in parasympathetic tone, in agreement with the induced stimulus.

Dynamic heart rate variability: a tool for exploring sympathovagal balance continuously during sleep in men

1998 ◽  
Vol 275 (3) ◽  
pp. H946-H950 ◽  
Author(s):  
Hélène Otzenberger ◽  
Claude Gronfier ◽  
Chantal Simon ◽  
Anne Charloux ◽  
Jean Ehrhart ◽  
...  
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Spectral Power ◽  
Low Frequency ◽  
Correlation Coefficients ◽  
Sympathovagal Balance ◽  
Nonlinear Method ◽  
Mean Frequency ◽  
Mean Square Difference ◽  
Insight Into

We have recently demonstrated that the overnight profiles of cardiac interbeat autocorrelation coefficient of R-R intervals ( r RR) calculated at 1-min intervals are related to the changes in sleep electroencephalographic (EEG) mean frequency, which reflect depth of sleep. Other quantitative measures of the Poincaré plots, i.e., the standard deviation of normal R-R intervals (SDNN) and the root mean square difference among successive R-R normal intervals (RMSSD), are commonly used to evaluate heart rate variability. The present study was designed to compare the nocturnal profiles of r RR, SDNN, and RMSSD with the R-R spectral power components: high-frequency (HF) power, reflecting parasympathetic activity; low-frequency (LF) power, reflecting a predominance of sympathetic activity with a parasympathetic component; and the LF-to-HF ratio (LF/HF), regarded as an index of sympathovagal balance. r RR, SDNN, RMSSD, and the spectral power components were calculated every 5 min during sleep in 15 healthy subjects. The overnight profiles of r RR and LF/HF showed coordinate variations with highly significant correlation coefficients ( P < 0.001 in all subjects). SDNN correlated with LF power ( P < 0.001), and RMSSD correlated with HF power ( P < 0.001). The overnight profiles of r RR and EEG mean frequency were found to be closely related with highly cross-correlated coefficients ( P < 0.001). SDNN and EEG mean frequency were also highly cross correlated ( P < 0.001 in all subjects but 1). No systematic relationship was found between RMSSD and EEG mean frequency. In conclusion, r RR appears to be a new tool for evaluating the dynamic beat-to-beat interval behavior and the sympathovagal balance continuously during sleep. This nonlinear method may provide new insight into autonomic disorders.

scholarly journals Differential effects of the blood pressure state on pulse rate variability and heart rate variability in critically ill patients

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Elisa Mejía-Mejía ◽  
James M. May ◽  
Mohamed Elgendi ◽  
Panayiotis A. Kyriacou
Keyword(s):  
Blood Pressure ◽  
Heart Rate ◽  
Heart Rate Variability ◽  
Pulse Rate ◽  
Pulse Transit Time ◽  
Pulse Rate Variability ◽  
Physiological Factors ◽  
Ecg Signals ◽  
Non Invasive ◽  
Electrocardiogram Ecg

AbstractHeart rate variability (HRV) utilizes the electrocardiogram (ECG) and has been widely studied as a non-invasive indicator of cardiac autonomic activity. Pulse rate variability (PRV) utilizes photoplethysmography (PPG) and recently has been used as a surrogate for HRV. Several studies have found that PRV is not entirely valid as an estimation of HRV and that several physiological factors, including the pulse transit time (PTT) and blood pressure (BP) changes, may affect PRV differently than HRV. This study aimed to assess the relationship between PRV and HRV under different BP states: hypotension, normotension, and hypertension. Using the MIMIC III database, 5 min segments of PPG and ECG signals were used to extract PRV and HRV, respectively. Several time-domain, frequency-domain, and nonlinear indices were obtained from these signals. Bland–Altman analysis, correlation analysis, and Friedman rank sum tests were used to compare HRV and PRV in each state, and PRV and HRV indices were compared among BP states using Kruskal–Wallis tests. The findings indicated that there were differences between PRV and HRV, especially in short-term and nonlinear indices, and although PRV and HRV were altered in a similar manner when there was a change in BP, PRV seemed to be more sensitive to these changes.

Segmenting Star Images with Complex Backgrounds Based on Correlation between Objects and 1D Gaussian Morphology

2021 ◽  
Vol 11 (9) ◽  
pp. 3763
Author(s):  
Yunlong Zou ◽  
Jinyu Zhao ◽  
Yuanhao Wu ◽  
Bin Wang
Keyword(s):  
Mean Square Error ◽  
Selection Process ◽  
Minimum Mean Square Error ◽  
Correlation Coefficients ◽  
False Alarms ◽  
Mean Square ◽  
Segmentation Method ◽  
Space Objects ◽  
High Earth Orbits ◽  
Star Images

Space object recognition in high Earth orbits (between 2000 km and 36,000 km) is affected by moonlight and clouds, resulting in some bright or saturated image areas and uneven image backgrounds. It is difficult to separate dim objects from complex backgrounds with gray thresholding methods alone. In this paper, we present a segmentation method of star images with complex backgrounds based on correlation between space objects and one-dimensional (1D) Gaussian morphology, and the focus is shifted from gray thresholding to correlation thresholding. We build 1D Gaussian functions with five consecutive column data of an image as a group based on minimum mean square error rules, and the correlation coefficients between the column data and functions are used to extract objects and stars. Then, lateral correlation is repeated around the identified objects and stars to ensure their complete outlines, and false alarms are removed by setting two values, the standard deviation and the ratio of mean square error and variance. We analyze the selection process of each thresholding, and experimental results demonstrate that our proposed correlation segmentation method has obvious advantages in complex backgrounds, which is attractive for object detection and tracking on a cloudy and bright moonlit night.

scholarly journals Exercise Intensity and Technical Involvement in U9 Team Handball: Effect of Game Format

2021 ◽  
Vol 18 (11) ◽  
pp. 5663
Author(s):  
Georgios Ermidis ◽  
Rasmus C. Ellegard ◽  
Vincenzo Rago ◽  
Morten B. Randers ◽  
Peter Krustrup ◽  
...  
Keyword(s):  
Heart Rate ◽  
Locomotor Activity ◽  
Exercise Intensity ◽  
High Intensity ◽  
High Speed ◽  
Medium Size ◽  
Total Distance ◽  
Team Handball ◽  
Large Size ◽  
Game Format

The purpose of this study was to quantify the exercise intensity and technical involvement of U9 boys’ and girls’ team handball during different game formats, and the differences between genders. Locomotor activity (total distance, distance in speed zones, accelerations, and decelerations), heart rate (HR), and technical involvement (shots, goals, and duels) metrics were collected during various 15 min game formats from a total of 57 Danish U9 players (37 boys and 20 girls). Game formats were a small size pitch (20 × 13 m) with 3 vs 3 players and offensive goalkeepers (S3 + 1) and 4 vs 4 players (S4), a medium size pitch (25.8 × 20 m) with 4 vs 4 (M4) and 5 vs 5 (M5) players, and a large size pitch (40 × 20 m) with 5 vs 5 (L5) players. Boys and girls covered a higher total distance (TD) of high-speed running (HSR) and sprinting during L5 games compared to all other game formats (p < 0.05; ES = (−0.9 to −2.1), (−1.4 to −2.8), and (−0.9 to −1.3) respectively). Players covered the highest amount of sprinting distance in L5 games compared to all other game formats (p < 0.01; ES = 0.8 to 1.4). In all the game formats, players spent from 3.04 to 5.96 min in 180–200 bpm and 0.03 min to 0.85 min in >200 bpm of the total 15 min. In addition, both genders had more shots in S3 + 1 than M5 (p < 0.01; ES = 1.0 (0.4;1.7)) and L5 (p < 0.01; ES = 1.1 (0.6;2.2)). Team handball matches have high heart rates, total distances covered, and high-intensity running distances for U9 boys and girls irrespective of the game format. Locomotor demands appeared to be even higher when playing on larger pitches, whereas the smaller pitch size and fewer players led to elevated technical involvement.

Intersession reliability of GPS-based and accelerometer-based physical variables in small-sided games with and without the offside rule

2021 ◽  
pp. 175433712098764
Author(s):  
Igor Junio de Oliveira Custódio ◽  
Gibson Moreira Praça ◽  
Leandro Vinhas de Paula ◽  
Sarah da Glória Teles Bredt ◽  
Fabio Yuzo Nakamura ◽  
...  
Keyword(s):  
Root Mean Square ◽  
Global Positioning System ◽  
Intraclass Correlation ◽  
Correlation Coefficients ◽  
Mean Square ◽  
Physical Demands ◽  
Intraclass Correlation Coefficients ◽  
Total Distance ◽  
Global Positioning ◽  
High Level

This study aimed to analyze the intersession reliability of global positioning system (GPS-based) distances and accelerometer-based (acceleration) variables in small-sided soccer games (SSG) with and without the offside rule, as well as compare variables between the tasks. Twenty-four high-level U-17 soccer athletes played 3 versus 3 (plus goalkeepers) SSG in two formats (with and without the offside rule). SSG were performed on eight consecutive weeks (4 weeks for each group), twice a week. The physical demands were recorded using a GPS with an embedded triaxial accelerometer. GPS-based variables (total distance, average speed, and distances covered at different speeds) and accelerometer-based variables (Player Load™, root mean square of the acceleration recorded in each movement axis, and the root mean square of resultant acceleration) were calculated. Results showed that the inclusion of the offside rule reduced the total distance covered (large effect) and the distances covered at moderate speed zones (7–12.9 km/h – moderate effect; 13–17.9 km/h – large effect). In both SSG formats, GPS-based variables presented good to excellent reliability (intraclass correlation coefficients – ICC > 0.62) and accelerometer-based variables presented excellent reliability (ICC values > 0.89). Based on the results of this study, the offside rule decreases the physical demand of 3 versus 3 SSG and the physical demands required in these SSG present high intersession reliability.

Sign in / Sign up

Export Citation Format

Share Document