Movement Analysis by means of inertial sensors: from bench to bedside

in the everyday clinical practice. Having this in mind, the choice of a simple setup would not be enough because, even if the setup is quick and simple, the instrumental assessment would still be in addition to the daily routine. The will to overcome this limit has led to the idea of instrumenting already existing and widely used functional tests. In this way the sensor based assessment becomes an integral part of the clinical assessment. Reliable and validated signal processing methods have been successfully implemented in Personal Health Systems based on smartphone technology. At the end of this research project there is evidence that such solution can really and easily used in clinical practice in both supervised and unsupervised settings. Smartphone based solution, together or in place of dedicated wearable sensing units, can truly become a pervasive and low-cost means for providing suitable testing solutions for quantitative movement analysis with a clear clinical value, ultimately providing enhanced balance and mobility support to an aging population.

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.

Manipolazione del metabolismo degli xenobiotici da frutta convenzionale ed attività chemiopreventiva

A reduced cancer risk associated with fruit and vegetable phytochemicals initially dictated chemopreventive approaches focused on specific green variety consumption or even single nutrient supplementations. However, these strategies not only failed to provide any health benefits but gave rise to detrimental effects. In parallel, public-health chemoprevention programmes were developed in the USA and Europe to increase whole vegetable consumption. Among these, the National Cancer Institute (NCI) sponsored plan “5 to 9 a day for a better health” was one of the most popular. This campaign promoted wide food choice through the consumption of at least 5 to 9 servings a day of colourful fruits and vegetables. In this study the effects of the diet suggested by NCI on transcription, translation and catalytic activity of both xenobiotic metabolizing (XME) and antioxidant enzymes were studied in the animal model. In fact, the boost of both antioxidant defences and “good” phase-II together with down-regulation of “bad” phase-I XMEs is still considered one of the most widely-used strategies of cancer control. Six male Sprague Dawley rats for each treatment group were used. According to the Italian Society of Human Nutrition, a serving of fruit, vegetables and leafy greens corresponds to 150, 250 and 50 g, respectively, in a 70 kg man. Proportionally, rats received one or five servings of lyophilized onion, tomato, peach, black grape or lettuce – for white, red, yellow, violet or green diet, respectively - or five servings of each green (“5 a day” diet) by oral gavage daily for 10 consecutive days. Liver subcellular fractions were tested for various cytochrome P450 (CYP) linked-monooxygenases, phase-II supported XMEs such as glutathione S-transferase (GST) and UDP-glucuronosyl transferase (UDPGT) as well as for some antioxidant enzymes. Hepatic transcriptional and translational effects were evaluated by reverse transcription-polymerase chain reaction (RT-PCR) and Western blot analysis, respectively. dROMs test was used to measure plasmatic oxidative stress. Routine haematochemical parameters were also monitored. While the five servings administration didn’t significantly vary XME catalytic activity, the lower dose caused a complex pattern of CYP inactivation with lettuce exerting particularly strong effects (a loss of up to 43% and 45% for CYP content and CYP2B1/2-linked XME, respectively; P<0.01). “5 a day” supplementation produced the most pronounced modulations (a loss of up to 60% for CYP2E1-linked XME and a reduction of CYP content of 54%; P<0.01). Testosterone hydroxylase activity confirmed these results. RT-PCR and Western blot analysis revealed that the “5 a day” diet XMEs inactivations were a result of both a transcriptional and a translational effect while lettuce didn’t exert such effects. All administrations brought out none or fewer modulation of phase-II supported XMEs. Apart from “5 a day” supplementation and the single serving of lettuce, which strongly induced DT- diaphorase (an increase of up to 141 and 171%, respectively; P<0.01), antioxidant enzymes were not significantly changed. RT-PCR analysis confirmed DT-diaphorase induction brought about by the administration of both “5 a day” diet and a single serving of lettuce. Furthermore, it unmasked a similar result for heme-oxygenase. dROMs test provided insight into a condition of high systemic oxidative stress as a consequence of animal diet supplementation with “5 a day” diet and a single serving of lettuce (an increase of up to 600% and 900%, respectively; P<0.01). Haematochemical parameters were mildly affected by such dietary manipulations. According to the classical chemopreventive theory, these results could be of particular relevance. In fact, even if antioxidant enzymes were only mildly affected, the phase-I inactivating ability of these vegetables would be a worthy strategy to cancer control. However, the recorded systemic considerable amount of reactive oxygen species and the complexity of these enzymes and their functions suggest caution in the widespread use of vegan/vegetarian diets as human chemopreventive strategies. In fact, recent literature rather suggests that only diets rich in fruits and vegetables and poor in certain types of fat, together with moderate caloric intake, could be associated with reduced cancer risk.

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.