Journal of medical engineering & technology
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Heart rate variability (HRV) refers to the regulation of the sinoatrial node, the natural pacemaker of the heart, by the sympathetic and parasympathetic branches of the autonomic nervous system. Heart rate variability analysis is an important tool to observe the heart's ability to respond to normal regulatory impulses that affect its rhythm. A computer-based intelligent system for analysis of cardiac states is very useful in diagnostics and disease management. ⋯ We present some general characteristics for each of these classes of HRV signals in the bispectrum and bicoherence plots. We also extracted features from the HOS and performed an analysis of variance (ANOVA) test. The results are very promising for cardiac arrhythmia classification with a number of features yielding a p-value < 0.02 in the ANOVA test.
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In this paper an algorithm for a functional electrical stimulation (FES) gait re-education system for incomplete spinal cord injured persons, providing efficient stimulation triggering, is presented. During neurological impaired gait FES was provided as motor augmentation support. Simultaneously the gait kinematics were recorded using the proposed sensory system, which is equipped with a dual-axial accelerometer and a gyroscope. ⋯ Trial measurements were verified with a contactless optical measurement system, with FES only simulated on controller output. Later on a treadmill training in combination with FES triggering was carried out. The outcome of the measurements shows that the use of sensory integration may successfully solve the problem of data assessment in dynamic movement where an inclinometer does not provide sufficient information for efficient control of FES.