The Pre-impact Fall Detection using the quantization based on ResNet
B. M. Koo, J. M. Kim, S. M. Yang, S. H. Lee, M. H. Hong, Y. H. Kim
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AbstractFall is one of the major health risks for older people. Hip fractures are considered the most dangerous among various injuries, as they can reduce mobility and lead to many complications, and even death (Hagen, G et al., 2020). Some researchers tried to protect the user using a wearable airbag based on the threshold-based algorithm (Jung, H et al., 2021). The more accurate algorithm was developed using the deep learning methods, but it was heavy and needed GPU or PC (Yu, X et al., 2021). This study was focused on developing the lightweight deep learning algorithm to detect pre-impact falls for targeting edge devices.Keywords: fall, deep learning, ResNet, TinyML, quantization
B. M. Koo, J. M. Kim, S. M. Yang, S. H. Lee, M. H. Hong, Y. H. Kim (2022). The Pre-impact Fall Detection using the quantization based on ResNet. Gerontechnology, 21(s),1-1
https://doi.org/10.4017/gt.2022.21.s.675.pp1