Host: The Japan Society of Mechanical Engineers
Name : [in Japanese]
Date : September 08, 2024 - September 11, 2024
In recent years, workers' long working hours have become an issue, and there is a need to improve work efficiency. In order to improve work efficiency, it is necessary to enable workers to understand their work efficiency. In this study, four subjects were subjected to a continuous addition task with the aim of creating a model to estimate work efficiency during computational work using electrocardiograms and relative concentration changes of oxy-Hb and deoxy-Hb in cerebral blood flow, and their biological information was measured during the task. The model was created using a convolutional neural network, a machine learning technique. As a result of the training, the model using only electrocardiograms was not sufficient for estimation, while the oxy-Hb and deoxy-Hb in cerebral blood flow in the prefrontal cortex were able to provide highly accurate estimation. The PFI values suggested that the dorsomedial prefrontal cortex and the left dorsolateral prefrontal cortex were relatively important.
