Body ares networks for human motor assessment

Healthcare, Human Computer Interfaces (HCI), Security and Biometry are the most promising application scenario directly involved in the Body Area Networks (BANs) evolution. Both wearable devices and sensors directly integrated in garments envision a word in which each of us is supervised by an invisible assistant monitoring our health and daily-life activities. New opportunities are enabled because improvements in sensors miniaturization and transmission efficiency of the wireless protocols, that achieved the integration of high computational power aboard independent, energy-autonomous, small form factor devices. Application’s purposes are various: (I) data collection to achieve off-line knowledge discovery; (II) user notification of his/her activities or in case a danger occurs; (III) biofeedback rehabilitation; (IV) remote alarm activation in case the subject need assistance; (V) introduction of a more natural interaction with the surrounding computerized environment; (VI) users identification by physiological or behavioral characteristics. Telemedicine and mHealth [1] are two of the leading concepts directly related to healthcare. The capability to borne unobtrusiveness objects supports users’ autonomy. A new sense of freedom is shown to the user, not only supported by a psychological help but a real safety improvement. Furthermore, medical community aims the introduction of new devices to innovate patient treatments. In particular, the extension of the ambulatory analysis in the real life scenario by proving continuous acquisition. The wide diffusion of emerging wellness portable equipment extended the usability of wearable devices also for fitness and training by monitoring user performance on the working task. The learning of the right execution techniques related to work, sport, music can be supported by an electronic trainer furnishing the adequate aid. HCIs made real the concept of Ubiquitous, Pervasive Computing and Calm Technology introduced in the 1988 by Marc Weiser and John Seeley Brown. They promotes the creation of pervasive environments, enhancing the human experience. Context aware, adaptive and proactive environments serve and help people by becoming sensitive and reactive to their presence, since electronics is ubiquitous and deployed everywhere. In this thesis we pay attention to the integration of all the aspects involved in a BAN development. Starting from the choice of sensors we design the node, configure the radio network, implement real-time data analysis and provide a feedback to the user. We present algorithms to be implemented in wearable assistant for posture and gait analysis and to provide assistance on different walking conditions, preventing falls. Our aim, expressed by the idea to contribute at the development of a non proprietary solutions, driven us to integrate commercial and standard solutions in our devices. We use sensors available on the market and avoided to design specialized sensors in ASIC technologies. We employ standard radio protocol and open source projects when it was achieved. The specific contributions of the PhD research activities are presented and discussed in the following. • We have designed and build several wireless sensor node providing both sensing and actuator capability making the focus on the flexibility, small form factor and low power consumption. The key idea was to develop a simple and general purpose architecture for rapid analysis, prototyping and deployment of BAN solutions. Two different sensing units are integrated: kinematic (3D accelerometer and 3D gyroscopes) and kinetic (foot-floor contact pressure forces). Two kind of feedbacks were implemented: audio and vibrotactile. • Since the system built is a suitable platform for testing and measuring the features and the constraints of a sensor network (radio communication, network protocols, power consumption and autonomy), we made a comparison between Bluetooth and ZigBee performance in terms of throughput and energy efficiency. Test in the field evaluate the usability in the fall detection scenario. • To prove the flexibility of the architecture designed, we have implemented a wearable system for human posture rehabilitation. The application was developed in conjunction with biomedical engineers who provided the audio-algorithms to furnish a biofeedback to the user about his/her stability. • We explored off-line gait analysis of collected data, developing an algorithm to detect foot inclination in the sagittal plane, during walk. • In collaboration with the Wearable Lab – ETH, Zurich, we developed an algorithm to monitor the user during several walking condition where the user carry a load. The remainder of the thesis is organized as follows. Chapter I gives an overview about Body Area Networks (BANs), illustrating the relevant features of this technology and the key challenges still open. It concludes with a short list of the real solutions and prototypes proposed by academic research and manufacturers. The domain of the posture and gait analysis, the methodologies, and the technologies used to provide real-time feedback on detected events, are illustrated in Chapter II. The Chapter III and IV, respectively, shown BANs developed with the purpose to detect fall and monitor the gait taking advantage by two inertial measurement unit and baropodometric insoles. Chapter V reports an audio-biofeedback system to improve balance on the information provided by the use centre of mass. A walking assistant based on the KNN classifier to detect walking alteration on load carriage, is described in Chapter VI.

Statistical methods for analysis and processing of medical ultrasound: applications to segmentation and restoration

In this thesis two major topics inherent with medical ultrasound images are addressed: deconvolution and segmentation. In the first case a deconvolution algorithm is described allowing statistically consistent maximum a posteriori estimates of the tissue reflectivity to be restored. These estimates are proven to provide a reliable source of information for achieving an accurate characterization of biological tissues through the ultrasound echo. The second topic involves the definition of a semi automatic algorithm for myocardium segmentation in 2D echocardiographic images. The results show that the proposed method can reduce inter- and intra observer variability in myocardial contours delineation and is feasible and accurate even on clinical data.

Quantifying the Economics of Medical Malpractice - A View from a Civil Law Perspective

Life is full of uncertainties. Legal rules should have a clear intention, motivation and purpose in order to diminish daily uncertainties. However, practice shows that their consequences are complex and hard to predict. For instance, tort law has the general objectives of deterring future negligent behavior and compensating the victims of someone else's negligence. Achieving these goals are particularly difficult in medical malpractice cases. To start with, when patients search for medical care they are typically sick in the first place. In case harm materializes during the treatment, it might be very hard to assess if it was due to substandard medical care or to the patient's poor health conditions. Moreover, the practice of medicine has a positive externality on the society, meaning that the design of legal rules is crucial: for instance, it should not result in physicians avoiding practicing their activity just because they are afraid of being sued even when they acted according to the standard level of care. The empirical literature on medical malpractice has been developing substantially in the past two decades, with the American case being the most studied one. Evidence from civil law tradition countries is more difficult to find. The aim of this thesis is to contribute to the empirical literature on medical malpractice, using two civil law countries as a case-study: Spain and Italy. The goal of this thesis is to investigate, in the first place, some of the consequences of having two separate sub-systems (administrative and civil) coexisting within the same legal system, which is common in civil law tradition countries with a public national health system (such as Spain, France and Portugal). When this holds, different procedures might apply depending on the type of hospital where the injury took place (essentially whether it is a public hospital or a private hospital). Therefore, a patient injured in a public hospital should file a claim in administrative courts while a patient suffering an identical medical accident should file a claim in civil courts. A natural question that the reader might pose is why should both administrative and civil courts decide medical malpractice cases? Moreover, can this specialization of courts influence how judges decide medical malpractice cases? In the past few years, there was a general concern with patient safety, which is currently on the agenda of several national governments. Some initiatives have been taken at the international level, with the aim of preventing harm to patients during treatment and care. A negligently injured patient might present a claim against the health care provider with the aim of being compensated for the economic loss and for pain and suffering. In several European countries, health care is mainly provided by a public national health system, which means that if a patient harmed in a public hospital succeeds in a claim against the hospital, public expenditures increase because the State takes part in the litigation process. This poses a problem in a context of increasing national health expenditures and public debt. In Italy, with the aim of increasing patient safety, some regions implemented a monitoring system on medical malpractice claims. However, if properly implemented, this reform shall also allow for a reduction in medical malpractice insurance costs. This thesis is organized as follows. Chapter 1 provides a review of the empirical literature on medical malpractice, where studies on outcomes and merit of claims, costs and defensive medicine are presented. Chapter 2 presents an empirical analysis of medical malpractice claims arriving to the Spanish Supreme Court. The focus is on reversal rates for civil and administrative decisions. Administrative decisions appealed by the plaintiff have the highest reversal rates. The results show a bias in lower administrative courts, which tend to focus on the State side. We provide a detailed explanation for these results, which can rely on the organization of administrative judges career. Chapter 3 assesses predictors of compensation in medical malpractice cases appealed to the Spanish Supreme Court and investigates the amount of damages attributed to patients. The results show horizontal equity between administrative and civil decisions (controlling for observable case characteristics) and vertical inequity (patients suffering more severe injuries tend to receive higher payouts). In order to execute these analyses, a database of medical malpractice decisions appealed to the Administrative and Civil Chambers of the Spanish Supreme Court from 2006 until 2009 (designated by the Spanish Supreme Court Medical Malpractice Dataset (SSCMMD)) has been created. A description of how the SSCMMD was built and of the Spanish legal system is presented as well. Chapter 4 includes an empirical investigation of the effect of a monitoring system for medical malpractice claims on insurance premiums. In Italy, some regions adopted this policy in different years, while others did not. The study uses data on insurance premiums from Italian public hospitals for the years 2001-2008. This is a significant difference as most of the studies use the insurance company as unit of analysis. Although insurance premiums have risen from 2001 to 2008, the increase was lower for regions adopting a monitoring system for medical claims. Possible implications of this system are also provided. Finally, Chapter 5 discusses the main findings, describes possible future research and concludes.

Efficient ultrasonic signal processing techniques for aided medical diagnostics

Ultrasound imaging is widely used in medical diagnostics as it is the fastest, least invasive, and least expensive imaging modality. However, ultrasound images are intrinsically difficult to be interpreted. In this scenario, Computer Aided Detection (CAD) systems can be used to support physicians during diagnosis providing them a second opinion. This thesis discusses efficient ultrasound processing techniques for computer aided medical diagnostics, focusing on two major topics: (i) Ultrasound Tissue Characterization (UTC), aimed at characterizing and differentiating between healthy and diseased tissue; (ii) Ultrasound Image Segmentation (UIS), aimed at detecting the boundaries of anatomical structures to automatically measure organ dimensions and compute clinically relevant functional indices. Research on UTC produced a CAD tool for Prostate Cancer detection to improve the biopsy protocol. In particular, this thesis contributes with: (i) the development of a robust classification system; (ii) the exploitation of parallel computing on GPU for real-time performance; (iii) the introduction of both an innovative Semi-Supervised Learning algorithm and a novel supervised/semi-supervised learning scheme for CAD system training that improve system performance reducing data collection effort and avoiding collected data wasting. The tool provides physicians a risk map highlighting suspect tissue areas, allowing them to perform a lesion-directed biopsy. Clinical validation demonstrated the system validity as a diagnostic support tool and its effectiveness at reducing the number of biopsy cores requested for an accurate diagnosis. For UIS the research developed a heart disease diagnostic tool based on Real-Time 3D Echocardiography. Thesis contributions to this application are: (i) the development of an automated GPU based level-set segmentation framework for 3D images; (ii) the application of this framework to the myocardium segmentation. Experimental results showed the high efficiency and flexibility of the proposed framework. Its effectiveness as a tool for quantitative analysis of 3D cardiac morphology and function was demonstrated through clinical validation.

Cosmic-Lab: Optical companions to binary Millisecond Pulsars

Millisecond Pulsars (MSPs) are fast rotating, highly magnetized neutron stars. According to the "canonical recycling scenario", MSPs form in binary systems containing a neutron star which is spun up through mass accretion from the evolving companion. Therefore, the final stage consists of a binary made of a MSP and the core of the deeply peeled companion. In the last years, however an increasing number of systems deviating from these expectations has been discovered, thus strongly indicating that our understanding of MSPs is far to be complete. The identification of the optical companions to binary MSPs is crucial to constrain the formation and evolution of these objects. In dense environments such as Globular Clusters (GCs), it also allows us to get insights on the cluster internal dynamics. By using deep photometric data, acquired both from space and ground-based telescopes, we identified 5 new companions to MSPs. Three of them being located in GCs and two in the Galactic Field. The three new identifications in GCs increased by 50% the number of such objects known before this Thesis. They all are non-degenerate stars, at odds with the expectations of the "canonical recycling scenario". These results therefore suggest either that transitory phases should also be taken into account, or that dynamical processes, as exchange interactions, play a crucial role in the evolution of MSPs. We also performed a spectroscopic follow-up of the companion to PSRJ1740-5340A in the GC NGC 6397, confirming that it is a deeply peeled star descending from a ~0.8Msun progenitor. This nicely confirms the theoretical expectations about the formation and evolution of MSPs.