A5022705903- EEG and Brain-Computer Interfaces
- Neurological disorders and treatments
- Muscle activation and electromyography studies
- Low-power high-performance VLSI design
- Parkinson's Disease Mechanisms and Treatments
Universidade Estadual de Campinas (UNICAMP)
2019-2021
Hospital de Clínicas da Unicamp
2021
This paper proposes two new data augmentation approaches based on Deep Convolutional Generative Adversarial Networks (DCGANs) and Style Transfer for augmenting Parkinson’s Disease (PD) electromyography (EMG) signals. The experimental results indicate that the proposed models can adapt to different frequencies amplitudes of tremor, simulating each patient’s tremor patterns extending them sets movement protocols. Therefore, one could use these existing patient dataset generating simulations...
This paper proposes a comparison between different neural network models, using multilayer perceptron (MLPs) and recurrent (RNN) for predicting Parkinson's disease electromyography (EMG) signals, to anticipate resulting resting tremor patterns. The experimental results indicate that the proposed models can adapt frequencies amplitudes of tremor, provide reasonable predictions both EMG envelopes raw signals. Therefore, one could use these as input control strategy functional electrical...
A Doença de Parkinson (DP) é uma doença neurodegenerativa caracterizada por sintomas como tremores repouso e ação, que causam graves prejuízos à vida do paciente. Recentemente, diversas dispositivos assistivos têm sido propostos para minimizar o impacto da na dos pacientes. No entanto, a maioria desses depende dados eletromiografia superfície (sEMG) paciente, são escassos. Neste trabalho, propomos os primeiros métodos, baseados em Redes Neurais, prever gerar sinais sEMG pacientes com (PP)....
Parkinson’s Disease (PD) is a neurodegenerative disorder characterized by symptoms like resting and action tremors, which cause severe impairments to the patient’s life. Recently, many assistance techniques have been proposed minimize disease’s impact on patients’ However, most of these methods depend data from PD’s surface electromyography (sEMG), scarce. In this work, we propose first methods, based Neural Networks, for predicting, generating, transferring style patient-specific PD sEMG...