Imagine trying to recognize a dance routine that is different every time it is performed. That’s a bit like identifying tics in children with tic disorders. Tics are repetitive movements that can vary in space and time, making them challenging to detect and classify. Deep learning methods have been explored, but the limited availability of tic disorder datasets has made it difficult to achieve accurate results. To address this, researchers developed the Slow-Fast and Light-Efficient Channel Attention Network (SFLCA-Net). This network utilizes two branch subnetworks and a Light-Efficient Channel Attention (LCA) module to extract visual information for precise tic recognition. The SFLCA-Net was tested on a custom tic disorder dataset, and the results showed impressive effectiveness in identifying tic actions. With further advancements, this research could pave the way for improved diagnosis and treatment of tic disorders in children!
Tic is a combination of a series of static facial and limb movements over a certain period in some children. However, due to the scarcity of tic disorder (TD) datasets, the existing work on tic recognition using deep learning does not work well. It is that spatial complexity and time-domain variability directly affect the accuracy of tic recognition. How to extract effective visual information for temporal and spatial expression and classification of tic movement is the key of tic recognition. We designed the slow-fast and light-efficient channel attention network (SFLCA-Net) to identify tic action. The whole network adopted two fast and slow branch subnetworks, and light-efficient channel attention (LCA) module, which was designed to solve the problem of insufficient complementarity of spatial-temporal channel information. The SFLCA-Net is verified on our TD dataset and the experimental results demonstrate the effectiveness of our method.
Dr. David Lowemann, M.Sc, Ph.D., is a co-founder of the Institute for the Future of Human Potential, where he leads the charge in pioneering Self-Enhancement Science for the Success of Society. With a keen interest in exploring the untapped potential of the human mind, Dr. Lowemann has dedicated his career to pushing the boundaries of human capabilities and understanding.
Armed with a Master of Science degree and a Ph.D. in his field, Dr. Lowemann has consistently been at the forefront of research and innovation, delving into ways to optimize human performance, cognition, and overall well-being. His work at the Institute revolves around a profound commitment to harnessing cutting-edge science and technology to help individuals lead more fulfilling and intelligent lives.
Dr. Lowemann’s influence extends to the educational platform BetterSmarter.me, where he shares his insights, findings, and personal development strategies with a broader audience. His ongoing mission is shaping the way we perceive and leverage the vast capacities of the human mind, offering invaluable contributions to society’s overall success and collective well-being.