Dense & Attention Convolutional Neural Networks for Toe Walking Recognition

Authors

Junde Chen, Chapman UniversityFollow
Rahul Soangra, Chapman UniversityFollow
Marybeth Grant-Beuttler, Oregon Institute of Technology
Y. A. Nanehkaran, Yancheng Teachers University
Yuxin Wen, Chapman UniversityFollow

Document Type

Article

Publication Date

5-2-2023

Abstract

Idiopathic toe walking (ITW) is a gait disorder where children’s initial contacts show limited or no heel touch during the gait cycle. Toe walking can lead to poor balance, increased risk of falling or tripping, leg pain, and stunted growth in children. Early detection and identification can facilitate targeted interventions for children diagnosed with ITW. This study proposes a new one-dimensional (1D) Dense & Attention convolutional network architecture, which is termed as the DANet, to detect idiopathic toe walking. The dense block is integrated into the network to maximize information transfer and avoid missed features. Further, the attention modules are incorporated into the network to highlight useful features while suppressing unwanted noises. Also, the Focal Loss function is enhanced to alleviate the imbalance sample issue. The proposed approach outperforms other methods and obtains a superior performance. It achieves a test recall of 88.91% for recognizing idiopathic toe walking on the local dataset collected from real-world experimental scenarios. To ensure the scalability and generalizability of the proposed approach, the algorithm is further validated through the publicly available datasets, and the proposed approach achieves an average precision, recall, and F1-Score of 89.34%, 91.50%, and 92.04%, respectively. Experimental results present a competitive performance and demonstrate the validity and feasibility of the proposed approach.

Comments

This article was originally published in IEEE Transactions on Neural Systems and Rehabilitation Engineering, volume 31, in 2023. https://doi.org/10.1109/TNSRE.2023.3272362

Recommended Citation

J. Chen, R. Soangra, M. Grant-Beuttler, Y. A. Nanehkaran and Y. Wen, "Dense & Attention Convolutional Neural Networks for Toe Walking Recognition," IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 31, pp. 2235-2245, 2023, https://doi.org/10.1109/TNSRE.2023.3272362.

Peer Reviewed

1

Copyright

The authors

Creative Commons License

This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.