Browsing by Subject "RITMO CARDIACO"
Now showing 1 - 2 of 2
Results Per Page
Sort Options
ponencia en congreso.listelement.badge Autonomic modulation during a cognitive task using a wearable device(2019) Bonomini, Maria Paula; Val-Calvo, Mikel; Díaz-Morcillo, Alejandro; Ferrández Vicente, José Manuel; Fernández-Jover, Eduardo"Heart-brain interaction is by nature bidirectional, and then, it is sensible to expect the heart, via the autonomic nervous system (ANS), to induce changes in the brain. Respiration can originate differentiated ANS states reflected by HRV. In this work, we measured the changes in performance during a cognitive task due to four autonomic states originated by breath control: at normal breathing (NB), fast breathing (FB), slow breathing (SB) and control phases. ANS states were characterized by temporal (SDNN) and spectral (LF and HF power) HRV markers. Cognitive performance was measured by the response time (RT) and the success rate (SR). HRV parameters were acquired with the wristband Empatica E4. Classification was accomplished, firstly, to find the best ANS variables that discriminated the breathing phases (BPH) and secondly, to find whether ANS parameters were associated to changes in RT and SR. In order to compensate for possible bias of the test sets, 1000 classification iterations were run. The ANS parameters that better separated the four BPH were LF and HF power, with changes about 300% from controls and an average classification rate of 59.9%, a 34.9% more than random. LF and HF explained RT separation for every BPH pair, and so was HF for SR separation. The best RT classification was 63.88% at NB vs SB phases, while SR provided a 73.39% at SB vs NB phases. Results suggest that breath control could show a relation with the efficiency of certain cognitive tasks. For this goal the Empatica wristband together with the proposed methodology could help to clarify this hypothesis."artículo de publicación periódica.listelement.badge Real-time detection of imminent ventricular fibrillation using mean and standard deviation of beat-to-beat HRV(2018) Mosquera, Candelaria; Racca, Dora María; Quintero-Rincón, Antonio"It is estimated that 50% of all cardiovascular deaths are caused by a sudden cardiac arrest (SCA), which represents 15% of global mortality, and its main cause is ventricular fibrillation (VF). Therefore, it is of interest to design new methods capable to detect changes in heart rate (HR or RR interval) that could announce the beginning of an imminent fibrillation. In this work, an effective novel indicator, based on mean and standard deviation of Heart Rate Variability (HRV), was studied and used to develop an algorithm that predicts imminent VF with 100% sensitivity and 100% specificity. The study was based on 65 RR intervals signals. The algorithm’s simplicity provides a quick-to-use implementation in a micro controller unit (MCU) for real-time VF detection, allowing its application in a variety of medical devices with electrocardiogram (ECG) modules."