A novel ViT-BILSTM model for physical activity intensity classification in adults using gravity-based acceleration

A novel ViT-BILSTM model for physical activity intensity classification in adults using gravity-based acceleration

Abstract Aim The aim of this study is to apply a novel hybrid framework incorporating a Vision Transformer (ViT) and bidirectional long short-term memory (Bi-LSTM) model for classifying physical activity intensity (PAI) in adults using gravity-based acceleration. Additionally, it further investigate...

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Bibliographic Details
Main Authors: Lin Wang, Zizhang Luo, Tianle Zhang
Format: Article
Language:English
Published: BMC 2025-02-01
Series:BMC Biomedical Engineering
Subjects:
Deep learning
Raw accelerometer data
Variation
Generalisation
Physical activity patterns
Online Access:https://doi.org/10.1186/s42490-025-00088-2
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https://doi.org/10.1186/s42490-025-00088-2

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