The application of the SS as sympathetic-activity index and the S:PS ratio as a representation of autonomic balance (SS:SD1) provides a better understanding of the Poincaré-plot method in HRV.

Abstract-Phantom-limb pain (PLP) is a phenomenon that may appear among people with amputation. Some studies reveal that 70% of people with amputation experience PLP years postamputation. There is a lack of scientific evidence about the cause of PLP. It has been hypothesized that the autonomic nervous system (ANS) could be involved in the mechanism that triggers PLP, but this hypothesis remains unclear. The aim of this study was to correlate ANS function, through heart rate variability (HRV) analysis, with PLP in adult males with amputation. The study population comprised 35 subjects, with 27 reporting PLP often or always. The rest of the subjects did not report any PLP. In order to calculate linear and nonlinear parameters of HRV, all subjects underwent 10 min of resting heart rate monitoring. The study did not find correlations between HRV parameters and PLP. Most of the subjects showed decreased values in linear parameters of HRV while nonlinear values were normal. HRV is not implicated in PLP. Linear and nonlinear methods for HRV analysis might reflect different physiological phenomena; while linear values place people with amputation at cardiovascular risk, nonlinear values indicate normality.

Peripheral arterial disease (PAD) is an artherosclerotic occlusive disorder of distal arteries, which can give rise to the intermittent claudication (IC) phenomenon, i.e., limb pain and necessity to stop. PAD patients with IC have altered their gait, increasing the fall risk. Several gait analysis works have studied acceleration signals (from sensors) to characterize the gait. One common technique is spectral analysis. However, this approach mainly uses dominant frequency (fd) to characterize gait patterns, and in a narrow spectral band, disregarding the full spectra information. We propose to use a full band spectral analysis (up to 15 Hz) and the fundamental frequency (f0) in order to completely characterize gait for both control subjects and PAD patients. Acceleration gait signals were recorded using an acquisition equipment consisting of four wireless sensor nodes located at ankle and hip height on both sides. Subjects had to walk, free-fashion, up to 10 min. The analysis of the periodicity of the gait acceleration signals, showed that f0 is statistically higher (p < 0.05) in control subjects (0.9743 ± 0.0716) than in PAD patients (0.8748 ± 0.0438). Moreover, the spectral envelope showed that, in controls, the power spectral density distribution is higher than in PAD patients, and that the power concentration is hither around the fd. In conclusion, full spectra analysis allowed to better characterize gait in PAD patients than classical spectral analysis. It allowed to better discriminate PAD patients and control subjects, and it also showed promising results to assess severity of PAD.

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