ECG processing algorithm in the QRS complex

Viera, Eduardo; Kaschel, Héctor; Valencia, Claudio

doi:10.1109/icaacca51523.2021.9465280

Cited by 2 publications

(3 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In this test, the HR of the individuals was monitored based on the duration of the R-R interval of the cardiac cycle [ 56 ], bicycle speed, algorithm occurrence time, and HRV over time. The last variable is expressed as the acceleration of HR with respect to the above parameters.…”

Section: Resultsmentioning

confidence: 99%

“…If we assume from Equation ( 1 ) and Figure 2 that the

peak travels a

distance in

time, this implies that the peak has a v speed that in an ECG corresponds to HR [ 56 ].

…”

Section: Methodsmentioning

confidence: 99%

“…The ECG collected is processed using the algorithm described in [ 56 ], obtaining the acceleration HR of each ECG.…”

Section: Methodsmentioning

confidence: 99%

See 2 more Smart Citations

Heart Rate Variability Control Using a Biofeedback and Wearable System

Viera

Kaschel

Valencia

2022

Sensors

Self Cite

View full text Add to dashboard Cite

Heart rate variability is an important physiological parameter in medicine. This parameter is used as an indicator of physiological and psychological well-being and even of certain pathologies. Research on biofeedback integrates the fields of biological application (physiological behavior), system modeling, and automated control. This study proposes a new method for modeling and controlling heart rate variability as heart rate acceleration, a model expressed in the frequency domain. The model is obtained from excitation and response signals from heart rate variability, which through the instrumental variables method and the minimization of a cost function delivers a transfer function that represents the physiological phenomenon. This study also proposes the design of an adaptive controller using the reference model. The controller controls heart rate variability based on the light actuators designed here, generating a conditioned reflex that allows individuals to self-regulate their state through biofeedback, synchronizing this action to homeostasis. Modeling is conducted in a target population of middle-aged men who work as firefighters and forest firefighters. This study validates the proposed model, as well as the design of the controllers and actuators, through a simple experiment based on indoor cycling. This experiment has different segments, namely leaving inertia, non-controlled segment, and actively controlled segment.

show abstract

Section: Resultsmentioning

confidence: 99%

“…If we assume from Equation ( 1 ) and Figure 2 that the

peak travels a

distance in

time, this implies that the peak has a v speed that in an ECG corresponds to HR [ 56 ].

…”

Section: Methodsmentioning

confidence: 99%