Computer-Vision Based Diagnosis of Parkinson’s Disease via Gait: A Survey

Abstract

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 rating scales makes the PD diagnosis a very complicated task. Thus, more efficient systems are required to perform an automated evaluation of PD for its earlier detection and to enhance life expectancy rate. Gait based clinical diagnosis can provide useful indications regarding the presence of PD. From recent years, computer vision-based (VB) analysis is in great demand and seems to be highly effective in PD inspection. The objective of this article is to systematically analyze the applications of computer vision in PD evaluation through gait. This paper surveys the VB PD gait acquisition modalities as well as provides a concise overview of preprocessing techniques. The study presents a description of PD related gait features, extraction and selection methods used for PD analysis. A number of machine learning techniques for classification of PD and healthy gait are also discussed. This article extensively surveys PD gait datasets considering data from 1997 to 2018. Also, several research gaps in existing studies have identified that need to be addressed in the future. At last, an outline of the proposed idea is given that can cope up with the related issues and can lead to quality VB PD gait investigation.

Human Gait Analysis and Prediction Using the Levenberg-Marquardt Method

“…Gait comprises of alternative repetition of these two (swing and stance) phases, one after the other, tracing a continuous cycle. It is evident from Figure 2 , and it has been demonstrated by Kour et al [ 18 ] and Vaughan et al [ 19 ] in their work that human gait continuously changes in angles of the hip joint, knee joint as well as ankle joint. These changes are brought about by the energy gradient in the human skeletal muscles of the lower limb [ 20 , 21 ].…”

Human Gait Analysis in Neurodegenerative Diseases: A Review

“…Among vision-based systems, the most commonly used for gait analysis are RBG monocular cameras, stereo cameras, thermal cameras and the most recently developed RGB-D cameras such as Microsoft Kinect or Intel RealSense [68]. A panoramic description of three-dimensional camera systems is provided in [69] with a critical discussion about the validity and clinical utility of these devices for assessing physical dysfunctions.…”

Role of Wearable Sensors with Machine Learning Approaches in Gait Analysis for Parkinson's Disease Assessment: A Review

“…Quantitative gait analysis techniques comprise devices that are basically of two types: Wearables [19,27,28] and Non-Wearables. [29] Non-wearable type signal acquisition system is commonly categorized into vision-based systems [30][31][32] and instrumented walkways for PD assessment. RGB-D cameras such as MS-Kinect [33][34] and 3-D motion analysis systems [35] have been used to capture motion data for PD analysis.…”