| Autor: |
Chidean MI; Signal Theory and Communications Department, University Rey Juan Carlos, Fuenlabrada, Spain., Barquero-Pérez Ó; Signal Theory and Communications Department, University Rey Juan Carlos, Fuenlabrada, Spain., Goya-Esteban R; Signal Theory and Communications Department, University Rey Juan Carlos, Fuenlabrada, Spain., Sánchez Sixto A; Physical Activity and Sports Department, University CEU San Pablo, Seville, Spain., de la Cruz Torres B; Physiotherapy Department, University of Seville, Seville, Spain., Naranjo Orellana J; Sports and Computer Science Department, University Pablo de Olavide, Seville, Spain., Sarabia Cachadiña E; Physical Activity and Sports Department, University CEU San Pablo, Seville, Spain., Caamaño AJ; Signal Theory and Communications Department, University Rey Juan Carlos, Fuenlabrada, Spain. |
| Abstrakt: |
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 ( f d ) 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 ( f 0 ) 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 f 0 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 f d . 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. |
