Airport Security: Passenger's Perception and Design Issues

The main goal of this thesis is to report patterns of perceived safety in the context of airport infrastructure, taking the airport of Bologna as reference. Many personal and environmental attributes are investigated to paint the profile of the sensitive passenger and to understand why precise factors of the transit environment are so impactful on the individual. The main analyses are based on a 2014-2015 passengers’ survey, involving almost six thousand of incoming and outgoing passengers. Other reports are used to implement and support the resource. The analysis is carried out by using a combination of Chi-square tests and binary logistic regressions. Findings shows that passengers result to be particularly affected by the perception of airport’s environment (e.g., state and maintenance of facilities, clarity and efficacy of information system, functionality of elevators and escalators), but also by the way how the passenger reaches the airport and the quality of security checks. In relation to such results, several suggestions are provided for the improvement of passenger satisfaction with safety. The attention is then focused on security checkpoints and related operations, described on a theoretical and technical ground. We present an example of how to realize a proper model of the security checks area of Bologna’s airport, with the aim to assess present performances of the system and consequences of potential variations. After a brief introduction to Arena, a widespread simulation software, the existing model is described, pointing out flaws and limitations. Such model is finally updated and changed in order to make it more reliable and more representative of the reality. Different scenarios are tested and results are compared using graphs and tables.

Description and Prediction of Freezing of Gait in Parkinson's Disease from Wearable Inertial Measurements Units

Parkinson's disease (PD) is a neuro-degenerative disorder, the second most common after Alzheimer's disease. After diagnosis, treatments can help to relieve the symptoms, but there is no known cure for PD. PD is characterized by a combination of motor and no-motor dysfunctions. Among the motor symptoms there is the so called Freezing of Gait (FoG). The FoG is a phenomenon in PD patients in which the feet stock to the floor and is difficult for the patient to initiate movement. FoG is a severe problem, since it is associated with falls, anxiety, loss of mobility, accidents, mortality and it has substantial clinical and social consequences decreasing the quality of life in PD patients. Medicine can be very successful in controlling movements disorders and dealing with some of the PD symptoms. However, the relationship between medication and the development of FoG remains unclear. Several studies have demonstrated that visual or auditory rhythmical cuing allows PD patients to improve their motor abilities. Rhythmic auditory stimulation (RAS) was shown to be particularly effective at improving gait, specially with patients that manifest FoG. While RAS allows to reduce the time and the effects of FoGs occurrence in PD patients after the FoG is detected, it can not avoid the episode due to the latency of detection. An improvement of the system would be the prediction of the FoG. This thesis was developed following two main objectives: (1) the finding of specifics properties during pre FoG periods different from normal walking context and other walking events like turns and stops using the information provided by the inertial measurements units (IMUs) and (2) the formulation of a model for automatically detect the pre FoG patterns in order to completely avoid the upcoming freezing event in PD patients. The first part focuses on the analysis of different methods for feature extraction which might lead in the FoG occurrence.