From inverted pendulum to N-link chain: inertial sensors-based assessment of movement kinematics and dynamics for functional evaluation and rehabilitation

Despite several clinical tests that have been developed to qualitatively describe complex motor tasks by functional testing, these methods often depend on clinicians' interpretation, experience and training, which make the assessment results inconsistent, without the precision required to objectively assess the effect of the rehabilitative intervention. A more detailed characterization is required to fully capture the various aspects of motor control and performance during complex movements of lower and upper limbs. The need for cost-effective and clinically applicable instrumented tests would enable quantitative assessment of performance on a subject-specific basis, overcoming the limitations due to the lack of objectiveness related to individual judgment, and possibly disclosing subtle alterations that are not clearly visible to the observer. Postural motion measurements at additional locations, such as lower and upper limbs and trunk, may be necessary in order to obtain information about the inter-segmental coordination during different functional tests involved in clinical practice. With these considerations in mind, this Thesis aims: i) to suggest a novel quantitative assessment tool for the kinematics and dynamics evaluation of a multi-link kinematic chain during several functional motor tasks (i.e. squat, sit-to-stand, postural sway), using one single-axis accelerometer per segment, ii) to present a novel quantitative technique for the upper limb joint kinematics estimation, considering a 3-link kinematic chain during the Fugl-Meyer Motor Assessment and using one inertial measurement unit per segment. The suggested methods could have several positive feedbacks from clinical practice. The use of objective biomechanical measurements, provided by inertial sensor-based technique, may help clinicians to: i) objectively track changes in motor ability, ii) provide timely feedback about the effectiveness of administered rehabilitation interventions, iii) enable intervention strategies to be modified or changed if found to be ineffective, and iv) speed up the experimental sessions when several subjects are asked to perform different functional tests.

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.

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.

Assessment of gait spatio-temporal parameters in neurological disorders using wearable inertial sensors

Movement analysis carried out in laboratory settings is a powerful, but costly solution since it requires dedicated instrumentation, space and personnel. Recently, new technologies such as the magnetic and inertial measurement units (MIMU) are becoming widely accepted as tools for the assessment of human motion in clinical and research settings. They are relatively easy-to-use and potentially suitable for estimating gait kinematic features, including spatio-temporal parameters. The objective of this thesis regards the development and testing in clinical contexts of robust MIMUs based methods for assessing gait spatio-temporal parameters applicable across a number of different pathological gait patterns. First, considering the need of a solution the least obtrusive as possible, the validity of the single unit based approach was explored. A comparative evaluation of the performance of various methods reported in the literature for estimating gait temporal parameters using a single unit attached to the trunk first in normal gait and then in different pathological gait conditions was performed. Then, the second part of the research headed towards the development of new methods for estimating gait spatio-temporal parameters using shank worn MIMUs on different pathological subjects groups. In addition to the conventional gait parameters, new methods for estimating the changes of the direction of progression were explored. Finally, a new hardware solution and relevant methodology for estimating inter-feet distance during walking was proposed. Results of the technical validation of the proposed methods at different walking speeds and along different paths against a gold standard were reported and showed that the use of two MIMUs attached to the lower limbs associated with a robust method guarantee a much higher accuracy in determining gait spatio-temporal parameters. In conclusion, the proposed methods could be reliably applied to various abnormal gaits obtaining in some cases a comparable level of accuracy with respect to normal gait.

Movement analysis on the field in young football players: biomechanical patterns of performance and injury prevention

The integration of quantitative data from movement analysis technologies is reshaping the analysis of athletes’ performances and injury mitigation, e.g., anterior cruciate ligament (ACL) rupture. Most of the movement assessments are performed in laboratory environments. Recent progress provides the chance to shift the paradigm to a more ecological approach with sport-specific elements and a closer examination of “real” movement patterns associated with performance and (ACL) injury risk. The present PhD thesis aimed at investigating the on-field motion patterns related to performance and injury prevention in young football players. The objectives of the thesis were: (I) in-lab measures of high-dynamics movements were used to validate wearable inertial sensors technology; (II) in-laboratory and on-field agility movement tasks were compared to inspect the effect of football-specific environment; (III) on-field analysis was conducted to challenge wearable sensors technology in the assessment of dangerous movement patterns towards the ACL rupture; (IV) an overview of technologies that could shape present and future assessment of ACL injury risk in daily practice was presented. The validity of wearables in the assessment of high-dynamics movements was confirmed. Relevant differences emerged between the movements performed in a laboratory setting and on the football pitch, supporting the inclusion of an ecological dynamics approach in preventive protocols. The on-field analysis of football-specific movement tasks demonstrated good reliability of wearable sensors and the presence of residual dangerous patterns in the injured players. A tool to inspect at-risk movement patterns on the field through objective measurements was presented. It discussed how potential alternatives to wearable inertial sensors embrace artificial intelligence and closer collaboration between clinical and technical expertise. The present thesis was meant to contribute to setting the basis for data-driven prevention protocols. A deeper comprehension of injury-related principles and counteractions will contribute to preserving athletes’ careers and health over time.

Central autonomic control in spontaneously hypertensive rats: a study on phasic phenomena during rapid-eye-movement sleep

The cardiovascular regulation undergoes wide changes in the different states of sleepwake cycle. In particular, the relationship between spontaneous fluctuations in heart period and arterial pressure clearly shows differences between the two sleep states. In non rapid-eye-movement sleep, heart rhythm is under prevalent baroreflex control, whereas in rapid-eye-movement sleep central autonomic commands prevail (Zoccoli et al., 2001). Moreover, during rapid-eye-movement sleep the cardiovascular variables show wide fluctuations around their mean value. In particular, during rapid-eyemovement sleep, the arterial pressure shows phasic hypertensive events which are superimposed upon the tonic level of arterial pressure. These phasic increases in arterial pressure are accompanied by an increase in heart rate (Sei & Morita, 1996; Silvani et al., 2005). Thus, rapid-eye-movement sleep may represent an “autonomic stress test” for the cardiovascular system, able to unmask pathological patterns of cardiovascular regulation (Verrier et al. 2005), but this hypothesis has never been tested experimentally. The aim of this study was to investigate whether rapid-eye-movement sleep may reveal derangements in central autonomic cardiovascular control in an experimental model of essential hypertension. The study was performed in Spontaneously Hypertensive Rats, which represent the most widely used model of essential hypertension, and allow full control of genetic and environmental confounding factors. In particular, we analyzed the cardiovascular, electroencephalogram, and electromyogram changes associated with phasic hypertensive events during rapid-eyemovement sleep in Spontaneously Hypertensive Rats and in their genetic Wistar Kyoto control strain. Moreover, we studied also a group of Spontaneously Hypertensive Rats made phenotypically normotensive by means of a chronic treatment with an angiotensin converting enzyme inhibitor, the Enalapril maleate, from the age of four weeks to the end of the experiment. All rats were implanted with electrodes for electroencephalographic and electromyographic recordings and with an arterial catheter for arterial pressure measurement. After six days for postoperative recovery, the rats were studied for five days, at an age of ten weeks.The study indicated that the peak of mean arterial pressure increase during the phasic hypertensive events in rapid-eye-movement sleep did not differ significantly between Spontaneously Hypertensive Rats and Wistar Kyoto rats, while on the other hand Spontaneously Hypertensive Rats showed a reduced increase in the frequency of theta rhythm and a reduced tachicardia with respect to Wistar Kyoto rats. The same pattern of changes in mean arterial pressure, heart period, and theta frequency was observed between Spontaneously Hypertensive Rats and Spontaneously Hypertensive Rats treated with Enalapril maleate. Spontaneously Hypertensive Rats do not differ from Wistar Kyoto rats only in terms of arterial hypertension, but also due to multiple unknown genetic differences. Spontaneously Hypertensive Rats were developed by selective breeding of Wistar Kyoto rats based only on the level of arterial pressure. However, in this process, multiple genes possibly unrelated to hypertension may have been selected together with the genetic determinants of hypertension (Carley et al., 2000). This study indicated that Spontaneously Hypertensive Rats differ from Wistar Kyoto rats, but not from Spontaneously Hypertensive Rats treated with Enalapril maleate, in terms of arterial pH and theta frequency. This feature may be due to genetic determinants unrelated to hypertension. In sharp contrast, the persistence of differences in the peak of heart period decrease and the peak of theta frequency increase during phasic hypertensive events between Spontaneously Hypertensive Rats and Spontaneously Hypertensive Rats treated with Enalapril maleate demonstrates that the observed reduction in central autonomic control of the cardiovascular system in Spontaneously Hypertensive Rats is not an irreversible consequence of inherited genetic determinants. Rather, the comparison between Spontaneously Hypertensive Rats and Spontaneously Hypertensive Rats treated with Enalapril maleate indicates that the observed differences in central autonomic control are the result of the hypertension per se. This work supports the view that the study of cardiovascular regulation in sleep provides fundamental insight on the pathophysiology of hypertension, and may thus contribute to the understanding of this disease, which is a major health problem in European countries (Wolf-Maier et al., 2003) with its burden of cardiac, vascular, and renal complications.

Tools and methods for the quality assurance of force platforms in human movement analysis

The human movement analysis (HMA) aims to measure the abilities of a subject to stand or to walk. In the field of HMA, tests are daily performed in research laboratories, hospitals and clinics, aiming to diagnose a disease, distinguish between disease entities, monitor the progress of a treatment and predict the outcome of an intervention [Brand and Crowninshield, 1981; Brand, 1987; Baker, 2006]. To achieve these purposes, clinicians and researchers use measurement devices, like force platforms, stereophotogrammetric systems, accelerometers, baropodometric insoles, etc. This thesis focus on the force platform (FP) and in particular on the quality assessment of the FP data. The principal objective of our work was the design and the experimental validation of a portable system for the in situ calibration of FPs. The thesis is structured as follows: Chapter 1. Description of the physical principles used for the functioning of a FP: how these principles are used to create force transducers, such as strain gauges and piezoelectrics transducers. Then, description of the two category of FPs, three- and six-component, the signals acquisition (hardware structure), and the signals calibration. Finally, a brief description of the use of FPs in HMA, for balance or gait analysis. Chapter 2. Description of the inverse dynamics, the most common method used in the field of HMA. This method uses the signals measured by a FP to estimate kinetic quantities, such as joint forces and moments. The measures of these variables can not be taken directly, unless very invasive techniques; consequently these variables can only be estimated using indirect techniques, as the inverse dynamics. Finally, a brief description of the sources of error, present in the gait analysis. Chapter 3. State of the art in the FP calibration. The selected literature is divided in sections, each section describes: systems for the periodic control of the FP accuracy; systems for the error reduction in the FP signals; systems and procedures for the construction of a FP. In particular is detailed described a calibration system designed by our group, based on the theoretical method proposed by ?. This system was the “starting point” for the new system presented in this thesis. Chapter 4. Description of the new system, divided in its parts: 1) the algorithm; 2) the device; and 3) the calibration procedure, for the correct performing of the calibration process. The algorithm characteristics were optimized by a simulation approach, the results are here presented. In addiction, the different versions of the device are described. Chapter 5. Experimental validation of the new system, achieved by testing it on 4 commercial FPs. The effectiveness of the calibration was verified by measuring, before and after calibration, the accuracy of the FPs in measuring the center of pressure of an applied force. The new system can estimate local and global calibration matrices; by local and global calibration matrices, the non–linearity of the FPs was quantified and locally compensated. Further, a non–linear calibration is proposed. This calibration compensates the non– linear effect in the FP functioning, due to the bending of its upper plate. The experimental results are presented. Chapter 6. Influence of the FP calibration on the estimation of kinetic quantities, with the inverse dynamics approach. Chapter 7. The conclusions of this thesis are presented: need of a calibration of FPs and consequential enhancement in the kinetic data quality. Appendix: Calibration of the LC used in the presented system. Different calibration set–up of a 3D force transducer are presented, and is proposed the optimal set–up, with particular attention to the compensation of non–linearities. The optimal set–up is verified by experimental results.

Design and development of new pressure sensors for aerodynamic applications

This artwork reports on two different projects that were carried out during the three years of Doctor of the Philosophy course. In the first years a project regarding Capacitive Pressure Sensors Array for Aerodynamic Applications was developed in the Applied Aerodynamic research team of the Second Faculty of Engineering, University of Bologna, Forlì, Italy, and in collaboration with the ARCES laboratories of the same university. Capacitive pressure sensors were designed and fabricated, investigating theoretically and experimentally the sensor’s mechanical and electrical behaviours by means of finite elements method simulations and by means of wind tunnel tests. During the design phase, the sensor figures of merit are considered and evaluated for specific aerodynamic applications. The aim of this work is the production of low cost MEMS-alternative devices suitable for a sensor network to be implemented in air data system. The last two year was dedicated to a project regarding Wireless Pressure Sensor Network for Nautical Applications. Aim of the developed sensor network is to sense the weak pressure field acting on the sail plan of a full batten sail by means of instrumented battens, providing a real time differential pressure map over the entire sail surface. The wireless sensor network and the sensing unit were designed, fabricated and tested in the faculty laboratories. A static non-linear coupled mechanical-electrostatic simulation, has been developed to predict the pressure versus capacitance static characteristic suitable for the transduction process and to tune the geometry of the transducer to reach the required resolution, sensitivity and time response in the appropriate full scale pressure input A time dependent viscoelastic error model has been inferred and developed by means of experimental data in order to model, predict and reduce the inaccuracy bound due to the viscolelastic phenomena affecting the Mylar® polyester film used for the sensor diaphragm. The development of the two above mentioned subjects are strictly related but presently separately in this artwork.

A new snowfall detection algorithm for high latitude regions based on a combination of active and passive sensors

Precipitation retrieval over high latitudes, particularly snowfall retrieval over ice and snow, using satellite-based passive microwave spectrometers, is currently an unsolved problem. The challenge results from the large variability of microwave emissivity spectra for snow and ice surfaces, which can mimic, to some degree, the spectral characteristics of snowfall. This work focuses on the investigation of a new snowfall detection algorithm specific for high latitude regions, based on a combination of active and passive sensors able to discriminate between snowing and non snowing areas. The space-borne Cloud Profiling Radar (on CloudSat), the Advanced Microwave Sensor units A and B (on NOAA-16) and the infrared spectrometer MODIS (on AQUA) have been co-located for 365 days, from October 1st 2006 to September 30th, 2007. CloudSat products have been used as truth to calibrate and validate all the proposed algorithms. The methodological approach followed can be summarised into two different steps. In a first step, an empirical search for a threshold, aimed at discriminating the case of no snow, was performed, following Kongoli et al. [2003]. This single-channel approach has not produced appropriate results, a more statistically sound approach was attempted. Two different techniques, which allow to compute the probability above and below a Brightness Temperature (BT) threshold, have been used on the available data. The first technique is based upon a Logistic Distribution to represent the probability of Snow given the predictors. The second technique, defined Bayesian Multivariate Binary Predictor (BMBP), is a fully Bayesian technique not requiring any hypothesis on the shape of the probabilistic model (such as for instance the Logistic), which only requires the estimation of the BT thresholds. The results obtained show that both methods proposed are able to discriminate snowing and non snowing condition over the Polar regions with a probability of correct detection larger than 0.5, highlighting the importance of a multispectral approach.

Progetto di reti Sensori Wireless e tecniche di Fusione Sensoriale

Ambient Intelligence (AmI) envisions a world where smart, electronic environments are aware and responsive to their context. People moving into these settings engage many computational devices and systems simultaneously even if they are not aware of their presence. AmI stems from the convergence of three key technologies: ubiquitous computing, ubiquitous communication and natural interfaces. The dependence on a large amount of fixed and mobile sensors embedded into the environment makes of Wireless Sensor Networks one of the most relevant enabling technologies for AmI. WSN are complex systems made up of a number of sensor nodes, simple devices that typically embed a low power computational unit (microcontrollers, FPGAs etc.), a wireless communication unit, one or more sensors and a some form of energy supply (either batteries or energy scavenger modules). Low-cost, low-computational power, low energy consumption and small size are characteristics that must be taken into consideration when designing and dealing with WSNs. In order to handle the large amount of data generated by a WSN several multi sensor data fusion techniques have been developed. The aim of multisensor data fusion is to combine data to achieve better accuracy and inferences than could be achieved by the use of a single sensor alone. In this dissertation we present our results in building several AmI applications suitable for a WSN implementation. The work can be divided into two main areas: Multimodal Surveillance and Activity Recognition. Novel techniques to handle data from a network of low-cost, low-power Pyroelectric InfraRed (PIR) sensors are presented. Such techniques allow the detection of the number of people moving in the environment, their direction of movement and their position. We discuss how a mesh of PIR sensors can be integrated with a video surveillance system to increase its performance in people tracking. Furthermore we embed a PIR sensor within the design of a Wireless Video Sensor Node (WVSN) to extend its lifetime. Activity recognition is a fundamental block in natural interfaces. A challenging objective is to design an activity recognition system that is able to exploit a redundant but unreliable WSN. We present our activity in building a novel activity recognition architecture for such a dynamic system. The architecture has a hierarchical structure where simple nodes performs gesture classification and a high level meta classifiers fuses a changing number of classifier outputs. We demonstrate the benefit of such architecture in terms of increased recognition performance, and fault and noise robustness. Furthermore we show how we can extend network lifetime by performing a performance-power trade-off. Smart objects can enhance user experience within smart environments. We present our work in extending the capabilities of the Smart Micrel Cube (SMCube), a smart object used as tangible interface within a tangible computing framework, through the development of a gesture recognition algorithm suitable for this limited computational power device. Finally the development of activity recognition techniques can greatly benefit from the availability of shared dataset. We report our experience in building a dataset for activity recognition. Such dataset is freely available to the scientific community for research purposes and can be used as a testbench for developing, testing and comparing different activity recognition techniques.

Design and Characterization of New Luminescent Sensors and Labels

The aim of this Ph.D. project has been the design and characterization of new and more efficient luminescent tools, in particular sensors and labels, for analytical chemistry, medical diagnostics and imaging. Actually both the increasing temporal and spatial resolutions that are demanded by those branches, coupled to a sensitivity that is required to reach the single molecule resolution, can be provided by the wide range of techniques based on luminescence spectroscopy. As far as the development of new chemical sensors is concerned, as chemists we were interested in the preparation of new, efficient, sensing materials. In this context, we kept developing new molecular chemosensors, by exploiting the supramolecular approach, for different classes of analytes. In particular we studied a family of luminescent tetrapodal-hosts based on aminopyridinium units with pyrenyl groups for the detection of anions. These systems exhibited noticeable changes in the photophysical properties, depending on the nature of the anion; in particular, addition of chloride resulted in a conformational change, giving an initial increase in excimeric emission. A good selectivity for dicarboxylic acid was also found. In the search for higher sensitivities, we moved our attention also to systems able to perform amplification effects. In this context we described the metal ion binding properties of three photoactive poly-(arylene ethynylene) co-polymers with different complexing units and we highlighted, for one of them, a ten-fold amplification of the response in case of addition of Zn2+, Cu2+ and Hg2+ ions. In addition, we were able to demonstrate the formation of complexes with Yb3+ an Er3+ and an efficient sensitization of their typical metal centered NIR emission upon excitation of the polymer structure, this feature being of particular interest for their possible applications in optical imaging and in optical amplification for telecommunication purposes. An amplification effect was also observed during this research in silica nanoparticles derivatized with a suitable zinc probe. In this case we were able to prove, for the first time, that nanoparticles can work as “off-on” chemosensors with signal amplification. Fluorescent silica nanoparticles can be thus seen as innovative multicomponent systems in which the organization of photophysically active units gives rise to fruitful collective effects. These precious effects can be exploited for biological imaging, medical diagnostic and therapeutics, as evidenced also by some results reported in this thesis. In particular, the observed amplification effect has been obtained thanks to a suitable organization of molecular probe units onto the surface of the nanoparticles. In the effort of reaching a deeper inside in the mechanisms which lead to the final amplification effects, we also attempted to find a correlation between the synthetic route and the final organization of the active molecules in the silica network, and thus with those mutual interactions between one another which result in the emerging, collective behavior, responsible for the desired signal amplification. In this context, we firstly investigated the process of formation of silica nanoparticles doped with pyrene derivative and we showed that the dyes are not uniformly dispersed inside the silica matrix; thus, core-shell structures can be formed spontaneously in a one step synthesis. Moreover, as far as the design of new labels is concerned, we reported a new synthetic approach to obtain a class of robust, biocompatible silica core-shell nanoparticles able to show a long-term stability. Taking advantage of this new approach we also showed the synthesis and photophysical properties of core-shell NIR absorbing and emitting materials that proved to be very valuable for in-vivo imaging. In general, the dye doped silica nanoparticles prepared in the framework of this project can conjugate unique properties, such as a very high brightness, due to the possibility to include many fluorophores per nanoparticle, high stability, because of the shielding effect of the silica matrix, and, to date, no toxicity, with a simple and low-cost preparation. All these features make these nanostructures suitable to reach the low detection limits that are nowadays required for effective clinical and environmental applications, fulfilling in this way the initial expectations of this research project.

Rehabilitation Engineering in Parkinson's disease

Impairment of postural control is a common consequence of Parkinson's disease (PD) that becomes more and more critical with the progression of the disease, in spite of the available medications. Postural instability is one of the most disabling features of PD and induces difficulties with postural transitions, initiation of movements, gait disorders, inability to live independently at home, and is the major cause of falls. Falls are frequent (with over 38% falling each year) and may induce adverse consequences like soft tissue injuries, hip fractures, and immobility due to fear of falling. As the disease progresses, both postural instability and fear of falling worsen, which leads patients with PD to become increasingly immobilized. The main aims of this dissertation are to: 1) detect and assess, in a quantitative way, impairments of postural control in PD subjects, investigate the central mechanisms that control such motor performance, and how these mechanism are affected by levodopa; 2) develop and validate a protocol, using wearable inertial sensors, to measure postural sway and postural transitions prior to step initiation; 3) find quantitative measures sensitive to impairments of postural control in early stages of PD and quantitative biomarkers of disease progression; and 4) test the feasibility and effects of a recently-developed audio-biofeedback system in maintaining balance in subjects with PD. In the first set of studies, we showed how PD reduces functional limits of stability as well as the magnitude and velocity of postural preparation during voluntary, forward and backward leaning while standing. Levodopa improves the limits of stability but not the postural strategies used to achieve the leaning. Further, we found a strong relationship between backward voluntary limits of stability and size of automatic postural response to backward perturbations in control subjects and in PD subjects ON medication. Such relation might suggest that the central nervous system presets postural response parameters based on perceived maximum limits and this presetting is absent in PD patients OFF medication but restored with levodopa replacement. Furthermore, we investigated how the size of preparatory postural adjustments (APAs) prior to step initiation depend on initial stance width. We found that patients with PD did not scale up the size of their APA with stance width as much as control subjects so they had much more difficulty initiating a step from a wide stance than from a narrow stance. This results supports the hypothesis that subjects with PD maintain a narrow stance as a compensation for their inability to sufficiently increase the size of their lateral APA to allow speedy step initiation in wide stance. In the second set of studies, we demonstrated that it is possible to use wearable accelerometers to quantify postural performance during quiet stance and step initiation balance tasks in healthy subjects. We used a model to predict center of pressure displacements associated with accelerations at the upper and lower back and thigh. This approach allows the measurement of balance control without the use of a force platform outside the laboratory environment. We used wearable accelerometers on a population of early, untreated PD patients, and found that postural control in stance and postural preparation prior to a step are impaired early in the disease when the typical balance and gait intiation symptoms are not yet clearly manifested. These novel results suggest that technological measures of postural control can be more sensitive than clinical measures. Furthermore, we assessed spontaneous sway and step initiation longitudinally across 1 year in patients with early, untreated PD. We found that changes in trunk sway, and especially movement smoothness, measured as Jerk, could be used as an objective measure of PD and its progression. In the third set of studies, we studied the feasibility of adapting an existing audio-biofeedback device to improve balance control in patients with PD. Preliminary results showed that PD subjects found the system easy-to-use and helpful, and they were able to correctly follow the audio information when available. Audiobiofeedback improved the properties of trunk sway during quiet stance. Our results have many implications for i) the understanding the central mechanisms that control postural motor performance, and how these mechanisms are affected by levodopa; ii) the design of innovative protocols for measuring and remote monitoring of motor performance in the elderly or subjects with PD; and iii) the development of technologies for improving balance, mobility, and consequently quality of life in patients with balance disorders, such as PD patients with augmented biofeedback paradigms.

Smart Sensors For Interoperable Smart Environment

Smart Environments are currently considered a key factor to connect the physical world with the information world. A Smart Environment can be defined as the combination of a physical environment, an infrastructure for data management (called Smart Space), a collection of embedded systems gathering heterogeneous data from the environment and a connectivity solution to convey these data to the Smart Space. With this vision, any application which takes advantages from the environment could be devised, without the need to directly access to it, since all information are stored in the Smart Space in a interoperable format. Moreover, according to this vision, for each entity populating the physical environment, i.e. users, objects, devices, environments, the following questions can be arise: “Who?”, i.e. which are the entities that should be identified? “Where?” i.e. where are such entities located in physical space? and “What?” i.e. which attributes and properties of the entities should be stored in the Smart Space in machine understandable format, in the sense that its meaning has to be explicitly defined and all the data should be linked together in order to be automatically retrieved by interoperable applications. Starting from this the location detection is a necessary step in the creation of Smart Environments. If the addressed entity is a user and the environment a generic environment, a meaningful way to assign the position, is through a Pedestrian Tracking System. In this work two solution for these type of system are proposed and compared. One of the two solution has been studied and developed in all its aspects during the doctoral period. The work also investigates the problem to create and manage the Smart Environment. The proposed solution is to create, by means of natural interactions, links between objects and between objects and their environment, through the use of specific devices, i.e. Smart Objects

Development of motion analysis protocols based on inertial sensors

The aim of this thesis was to describe the development of motion analysis protocols for applications on upper and lower limb extremities, by using inertial sensors-based systems. Inertial sensors-based systems are relatively recent. Knowledge and development of methods and algorithms for the use of such systems for clinical purposes is therefore limited if compared with stereophotogrammetry. However, their advantages in terms of low cost, portability, small size, are a valid reason to follow this direction. When developing motion analysis protocols based on inertial sensors, attention must be given to several aspects, like the accuracy of inertial sensors-based systems and their reliability. The need to develop specific algorithms/methods and software for using these systems for specific applications, is as much important as the development of motion analysis protocols based on them. For this reason, the goal of the 3-years research project described in this thesis was achieved first of all trying to correctly design the protocols based on inertial sensors, in terms of exploring and developing which features were suitable for the specific application of the protocols. The use of optoelectronic systems was necessary because they provided a gold standard and accurate measurement, which was used as a reference for the validation of the protocols based on inertial sensors. The protocols described in this thesis can be particularly helpful for rehabilitation centers in which the high cost of instrumentation or the limited working areas do not allow the use of stereophotogrammetry. Moreover, many applications requiring upper and lower limb motion analysis to be performed outside the laboratories will benefit from these protocols, for example performing gait analysis along the corridors. Out of the buildings, the condition of steady-state walking or the behavior of the prosthetic devices when encountering slopes or obstacles during walking can also be assessed. The application of inertial sensors on lower limb amputees presents conditions which are challenging for magnetometer-based systems, due to ferromagnetic material commonly adopted for the construction of idraulic components or motors. INAIL Prostheses Centre stimulated and, together with Xsens Technologies B.V. supported the development of additional methods for improving the accuracy of MTx in measuring the 3D kinematics for lower limb prostheses, with the results provided in this thesis. In the author’s opinion, this thesis and the motion analysis protocols based on inertial sensors here described, are a demonstration of how a strict collaboration between the industry, the clinical centers, the research laboratories, can improve the knowledge, exchange know-how, with the common goal to develop new application-oriented systems.