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To improve the effect of walking-assistive devices, there is a need for it to develop devices controlled by spontaneous intention of patients. In recent study, we identified spontaneous motion intention of walking step based on cerebral hemoglobin information. Twenty healthy subjects performed walking tasks in three levels of step size (small, normal and large). According to distribution features of signals’ power spectral-density, six frequency bands (0-0.18Hz with an interval of 0.03Hz for each band width) divided by applying wavelet packets decomposition were mainly analyzed. Feature vectors were extracted from the difference between oxygenated hemoglobin (oxyHb) and deoxygenated hemoglobin (dexoyHb) in different measuring channels in the six frequency bands. Support vector machine (SVM) method was utilized to classify the three levels of step sizes. Mean recognition accuracy achieved up to 83.3%. The result indicated that it is possible to identify spontaneous walking by using cerebral hemoglobin information. This is helpful for enhancing the intelligence of walking-assistive devices and motivating the active control of patients, which further is profitable for enhancing self-confidence of patients

To Classify Spontaneous Motion Intention of Step Size by Using Cerebral Hemoglobin Information