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Yoo, K., Rosenberg, M., Hsu, W., Zhang, S., Li, C., Scheinost, D., Constable, T. and Chun, M. (2018) Connectome-Based Predictive Modeling of Attention: Comparing Different Functional Connectivity Features and Prediction Methods across Datasets. NeuroImage, 167, 11-22.
https://doi.org/10.1016/j.neuroimage.2017.11.010

has been cited by the following article:

• TITLE: Attention Detection System Based on the Variability of Heart Rate

  AUTHORS: Ubaldo Enrique Rodríguez de Avila, Isaac Campos Braga, Fabíola Rodrigues de França Campos, Adriano Chiombacanga Nafital

  KEYWORDS: Arduino, RR Interval, Heart Rate Variability, Attention

  JOURNAL NAME: Journal of Sensor Technology, Vol.9 No.4, November 26, 2019

  ABSTRACT: Attention is a cognitive and psychobiological variable that lacks objective measures in natural contexts of formal learning. However, it can be objectively measured from the heart autonomic activity. In the present study, the validity and reliability of a system for recording heart rate variability are demonstrated. Twelve prototypes were created and paired with standard electrocardiogram. Long segments with cardiac pulse recordings were used within ten minutes. A highly significant correlation index (p