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A novel energy-efficient data acquisition method for wearable devices

机译:可穿戴设备的新型节能数据采集方法

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On wearable devices where an MCU primarily remains in an idle state, keeping the MCU in a deep sleep mode during idle periods can lead to significant power reduction. Since the deep sleep mode has a relatively high wake-up overhead, one of the effective techniques for power reduction is to decrease the wake-up frequency of the MCU. Meanwhile, due to the recent trend of increasing the number of sensors embedded in wearable devices, the MCU must wake up more frequently for data acquisitions from the sensors. This indicates an increase in power consumption caused by frequent wakeups. In this paper, we propose a new method to achieve power reduction of the MCU for wearable applications. The applications acquire data periodically from multiple sensors. Our proposed method achieves low power consumption by gathering the scattered data acquisitions of the sensors and decreasing the wake-up frequency. The experimental result shows that the proposed method achieved an 8.5-31% power reduction in the MCU.
机译:在可穿戴设备上,MCU主要保持在空闲状态,在空闲时段期间将MCU保持在深度睡眠模式中可能导致显着的功率降低。由于深度睡眠模式具有相对较高的唤醒开销,因此功率降低的有效技术之一是降低MCU的唤醒频率。同时,由于近期增加了嵌入穿戴设备中的传感器数量的趋势,MCU必须更频繁地从传感器获取数据获取。这表示频繁唤醒引起的功耗增加。在本文中,我们提出了一种新方法来实现可穿戴应用的MCU的功率降低。应用程序从多个传感器周期性地获取数据。我们所提出的方法通过收集传感器的散射数据采集并降低唤醒频率来实现低功耗。实验结果表明,该方法在MCU中实现了8.5-31%的功率降低。

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