Full Band Spectra Analysis of Gait Acceleration Signals for Peripheral Arterial Disease Patients

• Main Authors: Mihaela I. Chidean, Óscar Barquero-Pérez, Rebeca Goya-Esteban, Alberto Sánchez Sixto, Blanca de la Cruz Torres, Jose Naranjo Orellana, Elena Sarabia Cachadiña, Antonio J. Caamaño
• Format: Article
• Language: English
• Published: Frontiers Media S.A. 2018-08-01
• Series: Frontiers in Physiology
• Subjects: peripheral arterial disease; gait; full spectral; fundamental frequency; spectral envelope
• Online Access: https://www.frontiersin.org/article/10.3389/fphys.2018.01061/full

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.