La caratterizzazione endofenotipica del rimuginio

Rumination, defined as the tendency to think about the negative affect evoked by stressful events, has been identified as potentially playing a role in the development of cardiovascular diseases. Specifically, recent studies suggest that ruminative thoughts might be mediators of the prolonged physiological effects of stress. The main goal of this research was to study the effect of rumination, evoked in the laboratory, during the subsequent 24 hours. As rumination has been associated with the activity of several physiological systems, including the cardiovascular, endocrine, and immune system, we also aimed at studying the process from a psychoneuroendocrine point of view. Levels of anxiety, depression, anger, hostility, and trait rumination were assessed by the use of validated questionnaires. Impedance cardiography-derived measures, skin conductance, respiration, and beat-to-beat blood pressure (BP) were monitored continuously in 60 subjects during baseline, the Anger Recall Inteview, a reading task and two recovery periods. Half of the sample was randomly assigned to a distracter condition after the Anger Recall Inteview. Cortisol, plasma concentrations of epinephrine, norepinephrine, and inflammatory biomarkers (CRP, sICAM-1) were also obtained at baseline and at the end of the session. Then, all subjects were asked to wear an ambulatory BP monitor for 24 hours. Results show that the distracter was effective in stopping rumination in the laboratory but did not have a long-lasting effect in the subsequent 24 hours. Rumination was associated with prolonged sympathetic activity, vagal withdrawal, cortisol secrection, pro-inflammatory reaction and mood impairment compared to the reading task. After controlling for age and body mass index, rumination also proved to be a strong predictor of daily moods, and ambulatory HR and BP. Personality traits did not have an effect in determining the frequency or duration of daily rumination. Findings suggest that perseverative cognition can prolong stress- related affective and physiological activation and might act directly on somatic disease via the cardiovascular, immune, endocrine, and neurovisceral systems.

From fall-risk assessment to fall detection: inertial sensors in the clinical routine and daily life

Falls are caused by complex interaction between multiple risk factors which may be modified by age, disease and environment. A variety of methods and tools for fall risk assessment have been proposed, but none of which is universally accepted. Existing tools are generally not capable of providing a quantitative predictive assessment of fall risk. The need for objective, cost-effective and clinically applicable methods would enable quantitative assessment of fall risk on a subject-specific basis. Tracking objectively falls risk could provide timely feedback about the effectiveness of administered interventions enabling intervention strategies to be modified or changed if found to be ineffective. Moreover, some of the fundamental factors leading to falls and what actually happens during a fall remain unclear. Objectively documented and measured falls are needed to improve knowledge of fall in order to develop more effective prevention strategies and prolong independent living. In the last decade, several research groups have developed sensor-based automatic or semi-automatic fall risk assessment tools using wearable inertial sensors. This approach may also serve to detect falls. At the moment, i) several fall-risk assessment studies based on inertial sensors, even if promising, lack of a biomechanical model-based approach which could provide accurate and more detailed measurements of interests (e.g., joint moments, forces) and ii) the number of published real-world fall data of older people in a real-world environment is minimal since most authors have used simulations with healthy volunteers as a surrogate for real-world falls. With these limitations in mind, this thesis aims i) to suggest a novel method for the kinematics and dynamics evaluation of functional motor tasks, often used in clinics for the fall-risk evaluation, through a body sensor network and a biomechanical approach and ii) to define the guidelines for a fall detection algorithm based on a real-world fall database availability.

Assessment of Daily Life Mobility Levels using Wearable Inertial Sensors and Minimun Measured Input Models

Tracking activities during daily life and assessing movement parameters is essential for complementing the information gathered in confined environments such as clinical and physical activity laboratories for the assessment of mobility. Inertial measurement units (IMUs) are used as to monitor the motion of human movement for prolonged periods of time and without space limitations. The focus in this study was to provide a robust, low-cost and an unobtrusive solution for evaluating human motion using a single IMU. First part of the study focused on monitoring and classification of the daily life activities. A simple method that analyses the variations in signal was developed to distinguish two types of activity intervals: active and inactive. Neural classifier was used to classify active intervals; the angle with respect to gravity was used to classify inactive intervals. Second part of the study focused on extraction of gait parameters using a single inertial measurement unit (IMU) attached to the pelvis. Two complementary methods were proposed for gait parameters estimation. First method was a wavelet based method developed for the estimation of gait events. Second method was developed for estimating step and stride length during level walking using the estimations of the previous method. A special integration algorithm was extended to operate on each gait cycle using a specially designed Kalman filter. The developed methods were also applied on various scenarios. Activity monitoring method was used in a PRIN’07 project to assess the mobility levels of individuals living in a urban area. The same method was applied on volleyball players to analyze the fitness levels of them by monitoring their daily life activities. The methods proposed in these studies provided a simple, unobtrusive and low-cost solution for monitoring and assessing activities outside of controlled environments.