| Summary: | Strength training using patients’ desired force level is helpful to improve training effect and promote rehabilitation. Generally, force levels are recognized by applying EMG or biomechanical information, these methods were not suitable for patients who lost important muscle groups or have weakened muscle functions. This paper proposed a method for identifying force level based on cerebral hemoglobin information, rather than the information depending on limbs. Ten subjects performed pedaling movement in three force levels. Features were extracted in both the time-domain and frequency-domain, with deoxygenated hemoglobin (deoxy) and the difference between oxygenated hemoglobin (oxy) and deoxy as parameters. Important frequency bands (0.01-0.03Hz, 0.03-0.06Hz, 0.06-0.09Hz, 0.09-0.12Hz) were confirmed by performing power spectrum density analysis. And significant measure channels were selected by performing one-way analyses of variance on three time periods around the start of movement. Force level was recognized by applying extreme learning machine (ELM). The corresponding precision rate was up to 78.7%. The proposed identification method was not restricted to the existence of limbs or the strength of limb information. It was realized based on brain information recorded in a real movement environment; it is helpful to realize the desired force level of subjects and to provide a control command for rehabilitation training equipment.
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