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一个可重新配置的近传感器处理器,用于检测肢体假肢中的异常.

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    科学领域:

    • 生物医学工程 生物医学工程
    • 计算机工程 计算机工程
    • 人工智能的人工智能

    背景情况:

    • 使用肢体假肢的截肢者实时监测对于检测异常行为至关重要.
    • 现有的系统往往缺乏用于设备上的假肢应用所需的低功耗,低延迟处理.

    研究的目的:

    • 介绍一款用于假肢应用的可重新配置的近传感器异常检测处理器.
    • 开发一个能够实时监控和异常检测的集成微型系统.

    主要方法:

    • 处理器集成了一个可重新配置的变异自动编码器 (VAE),一个可扩展的自组织地图 (SOM) 阵列,以及一个可调整窗口大小的马尔科夫链.
    • 它支持多达64个可编程传感器通道,并使用时间序列分析来检测异常.
    • 使用UMC 40nm LP技术制造,设计优先考虑低功耗和最小面积.

    主要成果:

    • 在微秒内实现了实时检测,高F1分数 (0.933为FSP,0.956为SFDLA-12) 在微秒内.
    • 证明了特殊的能源效率 (43.84 nJ/功能为FSP,55.17 nJ/功能为SFDLA-12).
    • 在能源和面积效率方面,ARM Cortex-M4 / M33微控制器的性能明显优于ARM Cortex-M4 / M33微控制器 (高达257倍).

    结论:

    • 开发的处理器提供了一个高效的,可重新配置的解决方案,用于在假肢上的异常检测.
    • 它的低功耗和低延迟特性使其适合实时监测截肢者的肢体行为.
    • 这项技术有可能提高先进假肢设备的安全性和功能.