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We report on the first experimental demonstration of low-light-level cross-phase modulation (XPM) with double slow light pulses based on the double electromagnetically induced transparency (EIT) in cold cesium atoms. The double EIT is implemented with two control fields and two weak fields that drive populations prepared in the two doubly spin-polarized states. Group velocity matching can be obtained by tuning the intensity of either of the control fields. The XPM is based on the asymmetric M-type five-level system formed by the two sets of EIT. Enhancement in the XPM by group velocity matching is observed. Our work advances studies of low-light-level nonlinear optics based on double slow light pulses.

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Powered prostheses are effective for helping amputees walk on level ground, but these devices are inconvenient to use in complex environments. Prostheses need to understand the motion intent of amputees to help them walk in complex environments. Recently, researchers have found that they can use vision sensors to classify environments and predict the motion intent of amputees. Previous researchers can classify environments accurately in the offline analysis, but they neglect to decrease the corresponding time delay. To increase the accuracy and decrease the time delay of environmental classification, we propose a new decision fusion method in this paper. We fuse sequential decisions of environmental classification by constructing a hidden Markov model and designing a transition probability matrix. We evaluate our method by inviting ablebodied subjects and amputees to implement indoor and outdoor experiments. Experimental results indicate that our method can classify environments more accurately and with less time delay than previous methods. Besides classifying environments, the proposed decision fusion method may also optimize sequential predictions of the human motion intent in the future.

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