Evaluating reliability of ultrashort heart rate variability parameters in metabolic syndrome subjects

Darwin Astudilllo, Kenneth Palacio-Baus, Lizandro Solano-Quinde, Erika Severeyn, Sara Wong

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

Resumen

Heart rate variability (HRV) analysis is barely employed in healthcare environments mainly because of the lack of standard values determining the sympathovagal balance and the difficulty to register RR stationary series. Recent studies have proposed the use of shorter HRV series. For this work, we use a public metabolic syndrome subjects database retrieved during oral glucose tolerance test. In order to explore ultra-short HRV measures reliability we employ an autoregressive model using Burg method, such that short RR sequences can be evaluated while maintaining a good frequency resolution. RR, SD, rMSSD, LF, HF, LFn and LF/HF were computed for different RR sequences (10 min, 5 min, 1 min, 30 s, 10 s). To evaluate the reliability we used the intraclass correlation coefficient (ICC). Additionally, we compared the sympathovagal balance parameters (LFn, LF/HF) among the stages (basal and 30 min). Considering 10 min long registers as references, parameters obtained from 5 min long series present ICC values above 0.78 for all cases. One min long registers present ICC values above 0.70 only for temporal parameters in both RR series and rMSSD. By comparing LFn and LF/HF parameters among the basal state and 30 min, we observed a significant increase of the sympathetic tone (p < 0.05). However, these differences are important only for 10 and 5 min series. In general, we observe that temporal parameters exhibit higher reliability than those the spectral ones. Nonetheless, registers duration below one min do not present adequate results for the spectral parameters in this work.

Idioma originalInglés
Título de la publicación alojada2016 21st Symposium on Signal Processing, Images and Artificial Vision, STSIVA 2016
EditoresMiguel Altuve
EditorialInstitute of Electrical and Electronics Engineers Inc.
ISBN (versión digital)9781509037971
DOI
EstadoPublicada - 14 nov. 2016
Evento21st Symposium on Signal Processing, Images and Artificial Vision, STSIVA 2016 - Bucaramanga, Colombia
Duración: 30 ago. 20162 sep. 2016

Serie de la publicación

Nombre2016 21st Symposium on Signal Processing, Images and Artificial Vision, STSIVA 2016

Conferencia

Conferencia21st Symposium on Signal Processing, Images and Artificial Vision, STSIVA 2016
País/TerritorioColombia
CiudadBucaramanga
Período30/08/162/09/16

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