This is a three-year project. The main goal of this project is to develop algorithms for detecting postures of infants and children and then apply the posture detection algorithms to implement health caring systems for different periods of infants and children. Clinical assessments for infant’s risk of developing neuromotor impairment either are assessed through visual examination by specialized clinicians via recorded videos or involve expensive equipment, which are usually time-consuming, expensive, and only available in highly-resourced environments. This makes assessment inaccessible for families of limited means and in low resource countries. Therefore, it is desirable to automate the process of evaluating the quality of infant movements; otherwise, the early identification is not possible. In recent years, the OpenPose is a very popular human pose estimation algorithm; however, it focuses on adults, leading a degradation of accuracy if applied to infants. Therefore, In the first year, we will fist develop a pose estimation algorithm especially for infants and then apply it to develop an intelligent premature infant risk detection system for automatically assessing infant neuromotor risks. In the next year's plan, we will use this infant pose detection algorithm to develop (1) an intelligent baby danger detection system and (2) an intelligent baby music interactive system. If the baby lying in the crib has some dangerous movements (such as long sleep, stuffy nose and vomiting, etc.), the " intelligent baby danger detection system " will send a warning signal to the caregiver. The " intelligent baby music interactive system " is to allow the baby to trigger the music bell beside the crib through the movement of the limbs, so that the baby can explore the interaction between its body movements and music. In the third year's plan, we will develop (1) an intelligent reading posture recognition system and (2) an intelligent child's danger warning system for children. The intelligent reading posture recognition system can fully monitor the degree of concentration of children in their studies and promptly remind them whether the eyes are too close to the books or they have poor reading postures (e.g., humpback, one hand supporting his/her head). The intelligent child's danger warning system can prompt parents or kindergarten teachers to notice the status of children's activities when some dangerous actions (such as fighting, jumping after climbing high, putting objects into the mouth, etc.) occur. The goal of these two systems is to reduce the burden on parents and master the status of children learning.
|Effective start/end date||1/08/22 → 31/07/23|
UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This project contributes towards the following SDG(s):
- posture detection system
- learning machine
- neural networks
- infant risk detection system
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