A contactless monitoring system for accurately predicting walking energy expenditure based on an ensemble neural network

The monitoring of walking energy expenditure (EE) plays an important role in health evaluations and management. Here, we present a datasets to develop a ensemble neural network model for accurately predicting walking EE of younger and older adults and stroke survivors. The datasets including original data, processed data, mechine learning model, ensemble neural network model and the Leave-One-Out Cross-Validation results.

行走能量消耗（walking energy expenditure, EE）的监测在健康评估与管理中具有重要意义。本文构建了一套数据集，用于开发集成神经网络模型，以精准预测青年、老年人群及脑卒中幸存者的行走能量消耗。该数据集涵盖原始数据、预处理后的数据、机器学习模型、集成神经网络模型以及留一交叉验证（Leave-One-Out Cross-Validation）结果。