Machine learning

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 I-vectors to Detect and Evaluate Parkinson's Disease

Parkinson's Disease (PD) is a neurodegenerative disorder characterized by a variety of motor symptoms. PD patients show several motor deficits, including speech deficits, impaired handwriting and gait disturbances. In this work we propose a …

Phonological i-Vectors to Detect Parkinson's Disease

Speech disorders are common symptoms among Parkinson’s disease patients and affect the speech of patients in different aspects. Currently, there are few studies that consider the phonological dimension of Parkinson’s speech. In this work, we use a …

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 …

Speaker models for monitoring Parkinson’s disease progression considering different communication channels and acoustic conditions

Symptoms of Parkinson’s disease vary from patient to patient. Additionally, the progression of those symptoms also differs among patients. Most of the studies on the analysis of speech of people with Parkinson’s disease do not consider such an …

Towards an automatic evaluation of the dysarthria level of patients with Parkinson's disease

Background: Parkinson's disease (PD) is a neurological disorder that produces motor and non-motor impairments. The evaluation of motor symptoms is currently performed following the third section of the Movement Disorder Society – Unified Parkinson's …

Unobtrusive Monitoring of Speech Impairments of Parkinson's Disease Patients Through Mobile Devices

Parkinson's disease (PD) produces several speech impairments in the patients. Automatic classification of PD patients is performed considering speech recordings collected in noncontrolled acoustic conditions during normal phone calls in a unobtrusive …

Characterisation of voice quality of Parkinson’s disease using differential phonological posterior features

Change in voice quality (VQ) is one of the first precursors of Parkinson’s disease (PD). Specifically, impacted phonation and articulation causes the patient to have a breathy, husky-semiwhisper and hoarse voice. A goal of this paper is to …

Convolutional Neural Network to Model Articulation Impairments in Patients with Parkinson's Disease.

Speech impairments are one of the earliest manifestations in patients with Parkinson’s disease. Particularly, articulation deficits related to the capability of the speaker to start/stop the vibration of the vocal folds have been observed in the …

Effect of acoustic conditions on algorithms to detect Parkinson's disease from speech

Automatic detection of Parkinson's disease (PD) from speech is a basic step towards computer-aided tools supporting the diagnosis and monitoring of the disease. Although several methods have been proposed, their applicability to real-world situations …