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Assessment of the cardiovascular regulation during robotic assisted locomotion in normal subjects: Autoregressive spectral analysis vs empirical mode decomposition

V. Magagnin, Enrico G. Caiani, Laura Fusini, Maurizio Turiel, V. Licari, Ivano Bo, S. Cerutti, Alberto Porta

发表年份
2008
引用次数
6

摘要

Robotic assisted locomotion systems are recently gaining appreciation as methods to rehabilitate individuals with lost sensory motor function. In the present study we compare autoregressive power spectral analysis and empirical mode decomposition (EMD) applied to the analysis of short-term heart period variability regarding their ability to typify autonomic response during a robotic assisted locomotion session consisting in the following phases: 1) sitting position; 2) standing position; 3) suspension during subject instrumentation; 4) robotic assisted treadmill locomotion with partial body weight support; 5) standing recovery after exercise. Results showed a significant tachycardia during the suspension phase, but no significant changes of spectral indexes. On the contrary, when spectral indexes were derived according to EMD, changes were evidenced during the suspension and walking phases. The EMD method is more powerful than autoregressive spectral analysis in detecting variations of parasympathetic and sympathetic modulations elicited by a robotic-assisted locomotion protocol.

关键词

Autoregressive modelSittingSpectral analysisHilbert–Huang transformTreadmillSuspension (topology)Computer scienceSimulationControl theory (sociology)Artificial intelligence

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