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...
Saved in:
Main Authors: | Lin Wang, Zizhang Luo, Tianle Zhang |
---|---|
Format: | Article |
Language: | English |
Published: |
BMC
2025-02-01
|
Series: | BMC Biomedical Engineering |
Subjects: | |
Online Access: | https://doi.org/10.1186/s42490-025-00088-2 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Cross-ViT based benign and malignant classification of pulmonary nodules.
by: Qinfang Zhu, et al.
Published: (2025-01-01) -
Older adults’ Internet use behavior and its association with accelerometer-derived physical activity
by: Yen-Yu Chung, et al.
Published: (2025-02-01) -
Physical activity parameters as determinants of cardiovascular disease risk in kidney transplant recipients: an accelerometer-based study
by: Hatice N. Bozkurt, et al.
Published: (2024-09-01) -
From physical activity patterns to cognitive status: development and validation of novel digital biomarkers for cognitive assessment in older adults
by: Ling-Jie Fan, et al.
Published: (2025-01-01) -
Perception and impact of customized physical activity programs on objective physical activity parameters in prediabetes
by: Radhika Aditya Jadhav, et al.
Published: (2025-03-01)