ntroduction: Autonomic Nervous System (ANS) is composed by two branches (Sympathetic and Parasympathetic Systems) working together to maintain inner homeostasis in the body. The evaluation of ANS is mainly done within hospital environment and limited to a short period of time. To improve diagnose of autonomic dysfunctions, the evaluation out of clinical context in the day-life context is a crucial task.
Objectives: In this work we use classical spectral approach to detect changes in the Sympathovagal Balance (SVB) whose data were obtained during long periods of the day-life activity.
Methods: Classical frequency analysis using Fast Fourier Transform (FFT) applied to Heart Rate Variability (HRV) is used to compute the low frequency content (LF)/ high frequency content (HF) index, assigning HF to the parasympathetic system and LF to Sympathetic System. Inertial parameters using the accelerometer’s output were also extracted to identify body positions during the time period under analysis.
Results and Conclusions: SVB were obtained in different periods of the day and also during the sleep, reveling consistent results with typical answers associated to autonomic maneuvers/conditions (i.e., post prandial period, standing, isometric contraction, Valsalva Maneuver, etc.). The use of a portable device allows to obtain long records of clinical relevance, as this enables to study the Very-Low Frequency band (VLF) in the spectrum.