HRV Sympathetic and Parasympathetic Activity indices
SAI and PAI calculation is performed following the methodology described in [1-8]. Users must upload a .txt file comprising the timing of R events expressed in seconds (see example here). When you upload a file containing a series of N samples, our server will process it and generate a result file featuring three distinct output series, listed from left to right: SAI, PAI, and SAI/PAI. These output series are derived from a Kalman-based estimation [3]. They will consist of 'N-2' samples, with the first output sample corresponding to the third input sample. Please make sure that the file content and the file name do not contain sensitive data. The communication with our server is not encrypted and the data file might reside on our server beetween reboots. Any uploaded files will be deleted as soon as possible after the SAI-PAI computation. It is user's responsability to upload artifact-free series as an input to ensure a reliable SAI and PAI estimation. A point process-based artifact identification and correction algorithm for HRV series may be found here
[1] G Valenza, L Citi, JP Saul, R Barbieri, "Measures of Sympathetic and Parasympathetic Autonomic Outflow from Heartbeat Dynamics",
[2] G Valenza, L Citi, R Barbieri, Disentanglement of Sympathetic and Parasympathetic Activity by Instantaneous Analysis of Human Heartbeat Dynamics, Engineering in Medicine and Biology Society (EMBC), 38th Annual International Conference of the IEEE, Orlando (FL), USA, 2016
[3] G Valenza, L Citi, VB Wyller, R Barbieri, "ECG-Derived Sympathetic and Parasympathetic Activity in the Healthy: An Early Lower-Body Negative Pressure Study Using Adaptive Kalman Prediction", Engineering in Medicine and Biology Society (EMBC), 39th Annual International Conference of the IEEE, Honolulu (Hawaii), USA, 2018.
[4] G Valenza, L Citi, JP Saul, R Barbieri, "ECG-Derived Sympathetic and Parasympathetic Nervous System Dynamics: A Congestive Heart Failure Study"Computing in Cardiology, 2018
[5] G Valenza, A Duggento, L Passamonti, N Toschi, R Barbieri, Resting State Neural Correlates of Cardiac Sympathetic Dynamics in Healthy Subjects, 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2019.
[6] M. Nardelli, L. Citi, R. Barbieri and G. Valenza, "Irregularity Analysis of Sympathetic and Parasympathetic Activity Indices from HRV: A Pilot Study on Postural Changes," 11th Conference of the European Study Group on Cardiovascular Oscillations (ESGCO), Pisa, Italy, 2020, pp. 1-2.
[7] M. Nardelli, L. Citi, R. Barbieri and G. Valenza, "Intrinsic Complexity of Sympathetic and Parasympathetic Dynamics from HRV series: a Preliminary Study on Postural Changes," 42nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Montreal, QC, Canada, 2020, pp. 2577-2580.
[8] G Valenza, F Faita, L Citi, J.P. Saul, RM Bruno, R Barbieri, Validation of Sympathetic Activity Index from Heart Rate Variability series: A Preliminary Muscle Sympathetic Nerve Activity Study, Proceedings of the Computing in Cardiology conference, Rimini (Italy), 2020
Point Process-based arrhtyhmia detection and beat correction for HRV series
Real-Time Automated Point Process Method for Detection and Correction of Erroneous and Ectopic Heartbeats. This tool allows scientists and researchers to test our algorithm for the detection and correction of erroneous and ectopic heartbeats.
Permission is hereby granted, free of charge, to any person to use it for academic purposes, subject to the conditions outlined in section “Conditions of use” at http://neurostat-mit.appspot.com/.
Copyright (C) Luca Citi, Emery N Brown, and Riccardo Barbieri, 2010-2020.
All Rights Reserved.
When you upload a file with a series of R events, our server will process it and return a results file with the processed series. Please make sure that the file content and the file name do not contain sensitive data. The communication with our server is not encrypted and the data file might reside on our server beetween reboots.
Citi, L., Brown, E. N., & Barbieri, R. (2012). A real-time automated point-process method for the detection and correction of erroneous and ectopic heartbeats. IEEE transactions on biomedical engineering, 59(10), 2828-2837.