Machine Learning Classifiers to Evaluate Data From Gait Analysis With Depth Cameras in Patients With Parkinson's Disease.

Introduction: The assessments of the motor symptoms in Parkinson's disease (PD) are usually limited to clinical rating scales (MDS UPDRS III), and it depends on the clinician's experience. This study aims to propose a machine learning technique algorithm using the variables from upper and lower limbs, to classify people with PD from healthy people, using data from a portable low-cost device (RGB-D camera). And can be used to support the diagnosis and follow-up of patients in developing countries and remote areas.

Parkinson's disease prevalence, age distribution and staging in Colombia.

Parkinson's disease (PD) has the second highest prevalence among neurodege - nerative diseases. In Colombia, PD population dynamics are currently unknown. Health records offer a unique resource to study frequency and multi-morbidity of chronic diseases.

Age Matters: Objective Gait Assessment in Early Parkinson's Disease Using an RGB-D Camera.

Background: Gait alterations are hallmarks for the diagnosis and follow-up of patients with Parkinson's disease (PD). In normal conditions, age could affect gait dynamics. Although it is known that objective assessment of gait is a valuable tool for diagnosis and follow-up of patients with PD, only few studies evaluate the effect of aging on the gait pattern of patients with PD.

Objective Arm Swing Analysis in Early-Stage Parkinson's Disease Using an RGB-D Camera (Kinect®).

Background: Arm swing changes are common even in the early stages of Parkinson's disease (PD). We hypothesized that arm swing changes decrease with age and can be detected using a low-cost, RGB-D depth-sensing camera.

Objective: This study aimed to assess the differences in arm swing between PD patients and healthy participants and to investigate the possible effects of aging on these differences.