Résumé
OBJECTIVES: Human motion analysis can be applied to the diagnosis of musculoskeletal diseases, rehabilitation therapies, fall detection, and estimation of energy expenditure. To analyze human motion with micro-Doppler signatures measured by radar, a deep learning algorithm is one of the most effective approaches. Because deep learning requires a large data set, the high cost involved in measuring large amounts of human data is an intrinsic problem. The objective of this study is to augment human motion micro-Doppler data employing generative adversarial networks (GANs) to improve the accuracy of human motion classification. METHODS: To test data augmentation provided by GANs, authentic data for 7 human activities were collected using micro-Doppler radar. Each motion yielded 144 data samples. Software including GPU driver, CUDA library, cuDNN library, and Anaconda were installed to train the GANs. Keras-GPU, SciPy, Pillow, OpenCV, Matplotlib, and Git were used to create an Anaconda environment. The data produced by GANs were saved every 300 epochs, and the training was stopped at 3,000 epochs. The images generated from each epoch were evaluated, and the best images were selected. RESULTS: Each data set of the micro-Doppler signatures, consisting of 144 data samples, was augmented to produce 1,472 synthesized spectrograms of 64 × 64. Using the augmented spectrograms, the deep neural network was trained, increasing the accuracy of human motion classification. CONCLUSIONS: Data augmentation to increase the amount of training data was successfully conducted through the use of GANs. Thus, augmented micro-Doppler data can contribute to improving the accuracy of human motion recognition.
Sujets)
Humains , Boidae , Classification , Ensemble de données , Diagnostic , Métabolisme énergétique , Activités humaines , Apprentissage , Perception du mouvement , Maladies ostéomusculaires , Réadaptation , Apprentissage machine superviséRésumé
Delayed anoxic encephalopathy after carbon monoxide (CO) poisoning is characterized by neurological deterioration that occurs after recovery from acute CO intoxication. There has been no established therapy. We report a patient recovered from acute CO intoxication developed various neurological symptoms. After the administration of high dose prednisolone and anticholinesterase inhibitor, the therapeutic effect was remarkable and confirmed by quantitative analysis of diffusion-tensor imaging (DTI). DTI could be used to evaluate the therapeutic effect for delayed anoxic encephalopathy after CO poisoning.
Sujets)
Humains , Intoxication au monoxyde de carbone , Monoxyde de carbone , Carbone , Imagerie par tenseur de diffusion , Hypoxie cérébrale , Leucoencéphalopathies , Imagerie par résonance magnétique , Intoxication , PrednisoloneRésumé
No abstract available.