Micro macro neural network to recognize rollover movement

Takeshi Ando*, Jun Okamoto, Masakatsu G. Fujie


    研究成果: Article査読

    6 被引用数 (Scopus)


    Many motion support robots for the elderly and disabled have been studied all over the world. We have developed a rollover support system (rollover is one of the activities of daily living). Our ultimate goal is to develop an effective rollover support system for patients with cancer bone metastasis. The core of this system is a pneumatic rubber muscle that is operated by electromyogram (EMG) signals from the trunk muscle. Thr traditional neural network, the time delay neural network (TDNN), used to recognize movement shares the problems of response delay and false recognition. In this paper, we proposed a new neural network, called the micro macro neural network (MMNN), to recognize the rollover movement earlier and with more accuracy. The MMNN is composed of a micro part, which detects rapid changes in the strength of the EMG signal, and a macro part, which detects the tendency of the EMG signal to continually increase or decrease. As a result, recognition using the MMNN with an optimized structure is 40 ± 49 ms faster than recognition using the TDNN. Additionally, the number of false recognitions using the MMNN is one-third of that using the TDNN.

    ジャーナルAdvanced Robotics
    出版ステータスPublished - 2011 1月 1

    ASJC Scopus subject areas

    • 制御およびシステム工学
    • 人間とコンピュータの相互作用
    • コンピュータ サイエンスの応用
    • ハードウェアとアーキテクチャ
    • ソフトウェア


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