Human Gait Analysis in Neurodegenerative Diseases: a Review

This paper reviews the recent literature on technologies and methodologies for quantitative human gait analysis in the context of neurodegnerative diseases. The use of technological instruments can be of great support in both clinical diagnosis and severity assessment of these pathologies. In this paper, sensors, features and processing methodologies have been reviewed in order to provide a highly consistent work that explores the issues related to gait analysis. First, the phases of the human gait cycle are briefly explained, along with some non-normal gait patterns (gait abnormalities) typical of some neurodegenerative diseases. The work continues with a survey on the publicly available datasets principally used for comparing results. Then the paper reports the most common processing techniques for both feature selection and extraction and for classification and clustering. Finally, a conclusive discussion on current open problems and future directions is outlined

Gait Analysis for Early Neurodegenerative Diseases Classification through the Kinematic Theory of Rapid Human Movements

Neurodegenerative diseases are particular diseases whose decline can partially or completely compromise the normal course of life of a human being. In order to increase the quality of patient's life, a timely diagnosis plays a major role. The analysis of neurodegenerative diseases, and their stage, is also carried out by means of gait analysis. Performing early stage neurodegenerative disease assessment is still an open problem. In this paper, the focus is on modeling the human gait movement pattern by using the kinematic theory of rapid human movements and its sigma-lognormal model. The hypothesis is that the kinematic theory of rapid human movements, originally developed to describe handwriting patterns, and used in conjunction with other spatio-temporal features, can discriminate neurodegenerative diseases patterns, especially in early stages, while analyzing human gait with 2D cameras. The thesis empirically demonstrates its effectiveness in describing neurodegenerative patterns, when used in conjunction with state-of-the-art pose estimation and feature extraction techniques. The solution developed achieved 99.1% of accuracy using velocity-based, angle-based and sigma-lognormal features and left walk orientation

Towards a personal at-home lab for motion video tracking in patients with Parkinson's disease

Many digital healthcare services now employ the opportunities of mobile and smart Internet technologies. The Internet is used to deliver such services as medical consultations, diagnosis, and prescriptions. The services are constructed and delivered in the ubiquitous style - anywhere, anytime, and using surrounding devices of our everyday life. In this paper, we discuss the opportunities of motion video tracking in at-home settings for a patient. Parkinson's disease (PD) serves as a case study. First, we define the problem of motion video tracking in PD patients. Then, we consider Internet-enabled methods for motion video tracking, which are essentially restricted with professional settings of a medical environment. Finally, we propose to create a personal at-home lab based on such cheap home-based cameras as any smartphone has. Our early experiment shows that such cameras provide reliable capture quality for the practical use in PD patient motion video tracking

Gait Analysis for Early Neurodegenerative Diseases Classification Through the Kinematic Theory of Rapid Human Movements

Neurodegenerative diseases are particular diseases whose decline can partially or completely compromise the normal course of life of a human being. In order to increase the quality of patient's life, a timely diagnosis plays a major role. The analysis of neurodegenerative diseases, and their stage, is also carried out by means of gait analysis. Performing early stage neurodegenerative disease assessment is still an open problem. In this paper, the focus is on modeling the human gait movement pattern by using the kinematic theory of rapid human movements and its sigma-lognormal model. The hypothesis is that the kinematic theory of rapid human movements, originally developed to describe handwriting patterns, and used in conjunction with other spatio-temporal features, can discriminate neurodegenerative diseases patterns, especially in early stages, while analyzing human gait with 2D cameras. The thesis empirically demonstrates its effectiveness in describing neurodegenerative patterns, when used in conjunction with state-of-the-art pose estimation and feature extraction techniques. The solution developed achieved 99.1% of accuracy using velocity-based, angle-based and sigma-lognormal features and left walk orientation

The development, validation and demonstration of an automated rodent tracker and whisker detector

Quantitatively assessing behaviour to measure animal behaviour and motor control is challenging because there is a lack of unobtrusive behavioural models. Some studies have suggested that measuring whisker movements might be a good, quantitative behavioural model. However, whiskers are very thin, small and move very fast; and there is not yet an automated program that can detect whiskers in a fully-intact, freely-moving animal. Therefore, this thesis develops, validates and demonstrates a novel, fullyautomated rodent tracker and a whisker annotator, that simultaneously measures locomotion and exploration behaviours as well as whisker movements. The �rst step in designing an automated rodent tracker and whisker detector, is to extract a reliable ground truth from which to compare any tracked points to. Therefore, the Manual Whisker Annotator (MWA) was designed as a validator and calibrator for the subsequent trackers and detectors. The second step is to provide a reliable body and head contour. Therefore, the Automated Rodent Tracker (ART) was developed and validated, compared to a semi-automated tracker (Ethovision) and the MWA. Finally, a fully-automated whisker detector (FAWD) was designed and validated, using two existing semi-automatic whisker trackers (BWTT and Whisk) and the MWA. FAWD incorporates a variety of image-processing algorithms, including super sampling, dilation and subtraction and frangi �ltering to reliably detect whiskers. Both ART and FAWD were also successfully demonstrated on videos collected from SOD1 mice, a model of Amyotrophic Lateral Sclerosis, from day 30 to 120. The development of this software enables whisker movements and locomotion to be tracked in a repeatable fashion, and the fully-automated nature of the software means that many videos can be collected and quickly processed with minimal user input. This thesis develops and validates a suite of behavioural software that provides robust and quantitative measures of rodent behaviour for basic research or drug discovery. Future work will be to demonstrate this software on a larger range of rodent models of neurodegeneration, to further showcase the exibility and quantitative nature of this behavioural model

TCitySmartF: A comprehensive systematic framework for transforming cities into smart cities

A shared agreed-upon definition of "smart city" (SC) is not available and there is no "best formula" to follow in transforming each and every city into SC. In a broader inclusive definition, it can be described as an opportunistic concept that enhances harmony between the lives and the environment around those lives perpetually in a city by harnessing the smart technology enabling a comfortable and convenient living ecosystem paving the way towards smarter countries and the smarter planet. SCs are being implemented to combine governors, organisations, institutions, citizens, environment, and emerging technologies in a highly synergistic synchronised ecosystem in order to increase the quality of life (QoL) and enable a more sustainable future for urban life with increasing natural resource constraints. In this study, we analyse how to develop citizen- and resource-centric smarter cities based on the recent SC development initiatives with the successful use cases, future SC development plans, and many other particular SC development solutions. The main features of SC are presented in a framework fuelled by recent technological advancement, particular city requirements and dynamics. This framework - TCitySmartF 1) aims to aspire a platform that seamlessly forges engineering and technology solutions with social dynamics in a new philosophical city automation concept - socio-technical transitions, 2) incorporates many smart evolving components, best practices, and contemporary solutions into a coherent synergistic SC topology, 3) unfolds current and future opportunities in order to adopt smarter, safer and more sustainable urban environments, and 4) demonstrates a variety of insights and orchestrational directions for local governors and private sector about how to transform cities into smarter cities from the technological, social, economic and environmental point of view, particularly by both putting residents and urban dynamics at the forefront of the development with participatory planning and interaction for the robust community- and citizen-tailored services. The framework developed in this paper is aimed to be incorporated into the real-world SC development projects in Lancashire, UK

IoMT-based biomedical measurement systems for healthcare monitoring: a review

Biomedical measurement systems (BMS) have provided new solutions for healthcare monitoring and the diagnosis of various chronic diseases. With a growing demand for BMS in the field of medical applications, researchers are focusing on advancing these systems, including Internet of Medical Things (IoMT)-based BMS, with the aim of improving bioprocesses, healthcare systems and technologies for biomedical equipment. This paper presents an overview of recent activities towards the development of IoMT-based BMS for various healthcare applications. Different methods and approaches used in the development of these systems are presented and discussed, taking into account some metrological aspects related to the requirement for accuracy, reliability and calibration. The presented IoMT-based BMS are applied to healthcare applications concerning, in particular, heart, brain and blood sugar diseases as well as internal body sound and blood pressure measurements. Finally, the paper provides a discussion about the shortcomings and challenges that need to be addressed along with some possible directions for future research activities.</p