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首页> 美国卫生研究院文献>Sensors (Basel Switzerland) >Dry Electrode-Based Body Fat Estimation System with Anthropometric Data for Use in a Wearable Device
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Dry Electrode-Based Body Fat Estimation System with Anthropometric Data for Use in a Wearable Device

机译：具有人体测量数据的基于干电极的人体脂肪估计系统可在可穿戴设备中使用

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The bioelectrical impedance analysis (BIA) method is widely used to predict percent body fat (PBF). However, it requires four to eight electrodes, and it takes a few minutes to accurately obtain the measurement results. In this study, we propose a faster and more accurate method that utilizes a small dry electrode-based wearable device, which predicts whole-body impedance using only upper-body impedance values. Such a small electrode-based device typically needs a long measurement time due to increased parasitic resistance, and its accuracy varies by measurement posture. To minimize these variations, we designed a sensing system that only utilizes contact with the wrist and index fingers. The measurement time was also reduced to five seconds by an effective parameter calibration network. Finally, we implemented a deep neural network-based algorithm to predict the PBF value by the measurement of the upper-body impedance and lower-body anthropometric data as auxiliary input features. The experiments were performed with 163 amateur athletes who exercised regularly. The performance of the proposed system was compared with those of two commercial systems that were designed to measure body composition using either a whole-body or upper-body impedance value. The results showed that the correlation coefficient (r2) value was improved by about 9%, and the standard error of estimate (SEE) was reduced by 28%.
机译：生物电阻抗分析（BIA）方法被广泛用于预测人体脂肪百分比（PBF）。但是，它需要四到八个电极，并且要花费几分钟才能准确获得测量结果。在这项研究中，我们提出了一种更快，更准确的方法，该方法利用了基于干电极的小型可穿戴设备，该设备仅使用上身阻抗值来预测全身阻抗。这种小型的基于电极的设备由于寄生电阻的增加而通常需要较长的测量时间，并且其精度随测量姿势而变化。为了最大程度地减少这些变化，我们设计了一种仅利用与手腕和食指接触的传感系统。有效的参数校准网络还可以将测量时间减少到五秒钟。最后，我们实现了一种基于深度神经网络的算法，通过测量作为辅助输入特征的上身阻抗和下身人体测量数据来预测PBF值。实验是对163名定期运动的业余运动员进行的。将拟议系统的性能与设计用于使用全身或上身阻抗值测量人体成分的两个商用系统的性能进行了比较。结果表明，相关系数（ r 2 ）值提高了大约9％，并且估计的标准误差（SEE ）减少了28％。

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