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Wireless Body Region Networks Abnormality Identification And Energy Saving A Study

机译:无线体域网异常识别与节能研究

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摘要

Current advances in wireless body networking technologies help to escape any of the healthcare industry-related problems. Wearable biomedical devices and their related innovations are in vogue lately, with constant health surveillance being mandatory for many chronic patients. Energy conservation is critical in wireless body area networks (WBANs) since the sensor nodes are energy constraint devices. Energy conservation through data reduction approaches in WBANs is a comparatively less explored area in which the detection of probabilistic anomaly models is becoming inevitable for the prevention of serious health problems. This paper reviews wireless body area networks for anomaly detection in various applications and discusses how models can be made for the energy conservation of WBAN devices.
机译:无线人体联网技术的最新进展有助于避免任何与医疗保健行业相关的问题。近年来,可穿戴生物医学设备及其相关创新正在流行,许多慢性患者必须进行持续的健康监测。由于传感器节点是能量约束设备,因此节能在无线人体局域网(WBAN)中至关重要。在WBAN中,通过数据缩减方法进行节能是一个相对较少探索的领域,为了防止严重的健康问题,概率异常模型的检测已成为不可避免的领域。本文回顾了用于各种应用中异常检测的无线人体局域网,并讨论了如何为WBAN设备的节能建立模型。

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