OBJECTIVE: To evaluate the accuracy of the smartphone application (app) HRV Expert (CardioMood) and a chest strap (H10 Polar) for recording R-R intervals compared with electrocardiogram (ECG). METHODS: A total of 31 male recreational runners (age 36.1 [6.3] y) volunteered for this study. R-R intervals were recorded simultaneously by the smartphone app and ECG for 5 minutes to analyze heart-rate variability in both the supine and sitting positions. Time-domain indexes (heart rate, mean R-R, SD of RR intervals, count of successive normal R-R intervals differing by more than 50 ms, percentage of successive normal R-R intervals differing by more than 50 ms, and root mean square of successive differences between normal R-R intervals), frequency-domain indexes (low frequency, normalized low frequency, high frequency, normalized high frequency, low-frequency to high-frequency ratio, and very low frequency), and nonlinear indexes (SD of instantaneous beat-to-beat variability and long-term SD of continuous R-R intervals) were compared by unpaired t test, Pearson correlation, simple linear regression, and Bland-Altman plot to evaluate the agreement between the devices. RESULTS: High similarity with P value varying between .97 and 1.0 in both positions was found. The correlation coefficient of the heart-rate-variability indexes was perfect (r = 1.0; P = .00) for all variables. The constant error, standard error of estimation, and limits of agreement between ECG and the smartphone app were considered small. CONCLUSION: The smartphone app and chest strap provide excellent ECG compliance for all variables in the time domain, frequency domain, and nonlinear indexes, regardless of the assessed position. Therefore, the smartphone app replaces ECG for any heart-rate-variability analysis in runners.
OBJECTIVE: To evaluate the accuracy of the smartphone application (app) HRV Expert (CardioMood) and a chest strap (H10 Polar) for recording R-R intervals compared with electrocardiogram (ECG). METHODS: A total of 31 male recreational runners (age 36.1 [6.3] y) volunteered for this study. R-R intervals were recorded simultaneously by the smartphone app and ECG for 5 minutes to analyze heart-rate variability in both the supine and sitting positions. Time-domain indexes (heart rate, mean R-R, SD of RR intervals, count of successive normal R-R intervals differing by more than 50 ms, percentage of successive normal R-R intervals differing by more than 50 ms, and root mean square of successive differences between normal R-R intervals), frequency-domain indexes (low frequency, normalized low frequency, high frequency, normalized high frequency, low-frequency to high-frequency ratio, and very low frequency), and nonlinear indexes (SD of instantaneous beat-to-beat variability and long-term SD of continuous R-R intervals) were compared by unpaired t test, Pearson correlation, simple linear regression, and Bland-Altman plot to evaluate the agreement between the devices. RESULTS: High similarity with P value varying between .97 and 1.0 in both positions was found. The correlation coefficient of the heart-rate-variability indexes was perfect (r = 1.0; P = .00) for all variables. The constant error, standard error of estimation, and limits of agreement between ECG and the smartphone app were considered small. CONCLUSION: The smartphone app and chest strap provide excellent ECG compliance for all variables in the time domain, frequency domain, and nonlinear indexes, regardless of the assessed position. Therefore, the smartphone app replaces ECG for any heart-rate-variability analysis in runners.
Authors: André Pontes-Silva; Daniela Bassi-Dibai; Cid André Fidelis-de-Paula-Gomes; Cesário da Silva Souza; Flavio de Oliveira Pires; Cristiano Teixeira Mostarda; Almir Vieira Dibai Filho Journal: Rev Assoc Med Bras (1992) Date: 2022-09 Impact factor: 1.712
Authors: F A de Oliveira Júnior; R A Pereira; A S Silva; J L de Brito Alves; J H Costa-Silva; V A Braga; C M Balarini Journal: Braz J Med Biol Res Date: 2022-02-04 Impact factor: 2.590