Parkinson's Disease (PD) being the second most hazardous neurological disorder has
developed its roots in damaging people's quality of life (QOL). The ineffectiveness of clinical …

This article presents a machine learning methodology for diagnosing Parkinson's disease
(PD) based on the use of vertical Ground Reaction Forces (vGRFs) data collected from the …

In this paper, an interpretable classifier for Parkinson's Disease (PD) diagnosis based on
analyzing the gait cycle is presented. The proposed method utilizes clinical features …

The prevalence of musculoskeletal and neurological diseases such as knee osteoarthritis
(KOA) and Parkinson's disease (PD) has grown speedily in recent years. The direct impact …

Objective: single-camera-based gait monitoring is unobtrusive, inexpensive, and easy-to-
use to monitor daily gait of seniors in their homes. However, most studies require subjects to …

Nearly 1 million people in the USA and 10 million people worldwide are living with
Parkinson's disease (PD)[1]. The progression of the disease can be inferred from the …

Access to space has expanded dramatically over the past decade. The growing popularity of
small satellites, specifically cubesats, and the following launch initiatives have resulted in …

Step length, an essential component in gait analysis, is becoming appealing in many
aspects of our life. It can reflect physical fitness among the young and the senior, eg, obesity …

The objective characterization of human motion is required in a variety of fields including
competitive sports, rehabilitation and the detection of motor deficits. Nowadays, typically …

In this paper, an interpretable classifier using an interval type-2 fuzzy neural network for
detecting patients suffering from Parkinson's Disease (PD) based on analyzing the gait cycle …