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

Description

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.

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