Inertial sensors

Gait Assessment of Patients with Parkinson’s Disease using Inertial Sensors and Non-Linear Dynamics Features

Ingeniería electrónica, Universidad de Antioquia, 2018

Representaciones en Tiempo-Frecuencia en señales de marcha para la detección automática de la enfermedad de Parkinson

Ingeniería electrónica, Universidad de Antioquia, 2018

A Non-linear Dynamics Approach to Classify Gait Signals of Patients with Parkinson’s Disease

Parkinson’s disease is a neuro-degenerative disorder characterized by different motor symptoms, including several gait impairments. Gait analysis is a suitable tool to support the diagnosis and to monitor the state of the disease. This study proposes …

Multimodal assessment of Parkinson's disease: a deep learning approach

Parkinson's disease is a neurodegenerative disorder characterized by a variety of motor symptoms. Particularly, difficulties to start/stop movements have been observed in patients. From a technical/diagnostic point of view, these movement changes can …

Representaciones tiempo-frecuencia basadas en sensores inerciales para caracterizar la marcha en la enfermedad de Parkinson

La Enfermedad de Parkinson (EP) es un desorden neurodegenerativo del sistema nervioso central, cuyas características principales incluyen entre otras la rigidez, bradicinesia y pérdida de los reflejos posturales. El diagnóstico de la EP está basado …

Multi-view representation learning via GCCA for multimodal analysis of Parkinson's disease

Information from different bio-signals such as speech, handwriting, and gait have been used to monitor the state of Parkinson's disease (PD) patients, however, all the multimodal bio-signals may not always be available. We propose a method based on …