BabyNet: A Lightweight Network for Infant Reaching Action Recognition in Unconstrained Environments to Support Future Pediatric Rehabilitation Applications

TL;DR

BabyNet is a lightweight, data-driven neural network designed to recognize infant reaching actions in unconstrained environments, aiding pediatric rehabilitation with high accuracy and efficiency.

Contribution

This paper introduces BabyNet, a novel lightweight network architecture specifically for infant action recognition in real-world settings, with an annotated dataset and improved performance over larger models.

Findings

BabyNet achieves higher accuracy than larger networks.

It effectively captures temporal dependencies in infant reaching actions.

The dataset includes diverse infant reaching behaviors in natural environments.

Abstract

Action recognition is an important component to improve autonomy of physical rehabilitation devices, such as wearable robotic exoskeletons. Existing human action recognition algorithms focus on adult applications rather than pediatric ones. In this paper, we introduce BabyNet, a light-weight (in terms of trainable parameters) network structure to recognize infant reaching action from off-body stationary cameras. We develop an annotated dataset that includes diverse reaches performed while in a sitting posture by different infants in unconstrained environments (e.g., in home settings, etc.). Our approach uses the spatial and temporal connection of annotated bounding boxes to interpret onset and offset of reaching, and to detect a complete reaching action. We evaluate the efficiency of our proposed approach and compare its performance against other learning-based network structures in terms of capability of capturing temporal inter-dependencies and accuracy of detection of reaching onset and offset. Results indicate our BabyNet can attain solid performance in terms of (average) testing accuracy that exceeds that of other larger networks, and can hence serve as a light-weight data-driven framework for video-based infant reaching action recognition.