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.

Design and Performance Evaluation of Network-on-Chip Communication Protocols and Architectures

The scale down of transistor technology allows microelectronics manufacturers such as Intel and IBM to build always more sophisticated systems on a single microchip. The classical interconnection solutions based on shared buses or direct connections between the modules of the chip are becoming obsolete as they struggle to sustain the increasing tight bandwidth and latency constraints that these systems demand. The most promising solution for the future chip interconnects are the Networks on Chip (NoC). NoCs are network composed by routers and channels used to inter- connect the different components installed on the single microchip. Examples of advanced processors based on NoC interconnects are the IBM Cell processor, composed by eight CPUs that is installed on the Sony Playstation III and the Intel Teraflops pro ject composed by 80 independent (simple) microprocessors. On chip integration is becoming popular not only in the Chip Multi Processor (CMP) research area but also in the wider and more heterogeneous world of Systems on Chip (SoC). SoC comprehend all the electronic devices that surround us such as cell-phones, smart-phones, house embedded systems, automotive systems, set-top boxes etc... SoC manufacturers such as ST Microelectronics , Samsung, Philips and also Universities such as Bologna University, M.I.T., Berkeley and more are all proposing proprietary frameworks based on NoC interconnects. These frameworks help engineers in the switch of design methodology and speed up the development of new NoC-based systems on chip. In this Thesis we propose an introduction of CMP and SoC interconnection networks. Then focusing on SoC systems we propose: • a detailed analysis based on simulation of the Spidergon NoC, a ST Microelectronics solution for SoC interconnects. The Spidergon NoC differs from many classical solutions inherited from the parallel computing world. Here we propose a detailed analysis of this NoC topology and routing algorithms. Furthermore we propose aEqualized a new routing algorithm designed to optimize the use of the resources of the network while also increasing its performance; • a methodology flow based on modified publicly available tools that combined can be used to design, model and analyze any kind of System on Chip; • a detailed analysis of a ST Microelectronics-proprietary transport-level protocol that the author of this Thesis helped developing; • a simulation-based comprehensive comparison of different network interface designs proposed by the author and the researchers at AST lab, in order to integrate shared-memory and message-passing based components on a single System on Chip; • a powerful and flexible solution to address the time closure exception issue in the design of synchronous Networks on Chip. Our solution is based on relay stations repeaters and allows to reduce the power and area demands of NoC interconnects while also reducing its buffer needs; • a solution to simplify the design of the NoC by also increasing their performance and reducing their power and area consumption. We propose to replace complex and slow virtual channel-based routers with multiple and flexible small Multi Plane ones. This solution allows us to reduce the area and power dissipation of any NoC while also increasing its performance especially when the resources are reduced. This Thesis has been written in collaboration with the Advanced System Technology laboratory in Grenoble France, and the Computer Science Department at Columbia University in the city of New York.

Application Platforms for the Internet of Things: Theory, Architecture, Protocols, Data Formats, and Privacy

The Internet of Things (IoT) is the next industrial revolution: we will interact naturally with real and virtual devices as a key part of our daily life. This technology shift is expected to be greater than the Web and Mobile combined. As extremely different technologies are needed to build connected devices, the Internet of Things field is a junction between electronics, telecommunications and software engineering. Internet of Things application development happens in silos, often using proprietary and closed communication protocols. There is the common belief that only if we can solve the interoperability problem we can have a real Internet of Things. After a deep analysis of the IoT protocols, we identified a set of primitives for IoT applications. We argue that each IoT protocol can be expressed in term of those primitives, thus solving the interoperability problem at the application protocol level. Moreover, the primitives are network and transport independent and make no assumption in that regard. This dissertation presents our implementation of an IoT platform: the Ponte project. Privacy issues follows the rise of the Internet of Things: it is clear that the IoT must ensure resilience to attacks, data authentication, access control and client privacy. We argue that it is not possible to solve the privacy issue without solving the interoperability problem: enforcing privacy rules implies the need to limit and filter the data delivery process. However, filtering data require knowledge of how the format and the semantics of the data: after an analysis of the possible data formats and representations for the IoT, we identify JSON-LD and the Semantic Web as the best solution for IoT applications. Then, this dissertation present our approach to increase the throughput of filtering semantic data by a factor of ten.

Wireless Network Analytics for Next Generation Spectrum Awareness

The importance of networks, in their broad sense, is rapidly and massively growing in modern-day society thanks to unprecedented communication capabilities offered by technology. In this context, the radio spectrum will be a primary resource to be preserved and not wasted. Therefore, the need for intelligent and automatic systems for in-depth spectrum analysis and monitoring will pave the way for a new set of opportunities and potential challenges. This thesis proposes a novel framework for automatic spectrum patrolling and the extraction of wireless network analytics. It aims to enhance the physical layer security of next generation wireless networks through the extraction and the analysis of dedicated analytical features. The framework consists of a spectrum sensing phase, carried out by a patrol composed of numerous radio-frequency (RF) sensing devices, followed by the extraction of a set of wireless network analytics. The methodology developed is blind, allowing spectrum sensing and analytics extraction of a network whose key features (i.e., number of nodes, physical layer signals, medium access protocol (MAC) and routing protocols) are unknown. Because of the wireless medium, over-the-air signals captured by the sensors are mixed; therefore, blind source separation (BSS) and measurement association are used to estimate the number of sources and separate the traffic patterns. After the separation, we put together a set of methodologies for extracting useful features of the wireless network, i.e., its logical topology, the application-level traffic patterns generated by the nodes, and their position. The whole framework is validated on an ad-hoc wireless network accounting for MAC protocol, packet collisions, nodes mobility, the spatial density of sensors, and channel impairments, such as path-loss, shadowing, and noise. The numerical results obtained by extensive and exhaustive simulations show that the proposed framework is consistent and can achieve the required performance.

Induction of Hebbian associative plasticity through paired non-invasive brain stimulation of premotor-motor areas to elucidate the network's functional role

The ventral premotor cortex (PMv) is believed to play a pivotal role in a multitude of visuomotor behaviors, such as sensory-guided goal-directed visuomotor transformations, arbitrary visuomotor mapping, and hyper-learnt visuomotor associations underlying automatic imitative tendencies. All these functions are likely carried out through the copious projections connecting PMv to the primary motor cortex (M1). Yet, causal evidence investigating the functional relevance of the PMv-M1 network remains elusive and scarce. In the studies reported in this thesis we addressed this issue using a transcranial magnetic stimulation (TMS) protocol called cortico-cortical paired associative stimulation (ccPAS), which relies on multisite stimulation to induce Hebbian spike-timing dependent plasticity (STDP) by repeatedly stimulating the pathway connecting two target areas to manipulate their connectivity. Firstly, we show that ccPAS protocols informed by both short- and long-latency PMv-M1 interactions effectively modulate connectivity between the two nodes. Then, by pre-activating the network to apply ccPAS in a state-dependent manner, we were able to selectively target specific functional visuo-motor pathways, demonstrating the relevance of PMv-M1 connectivity to arbitrary visuomotor mapping. Subsequently, we addressed the PMv-to-M1 role in automatic imitation, and demonstrated that its connectivity manipulation has a corresponding impact on automatic imitative tendencies. Finally, by combining dual-coil TMS connectivity assessments and ccPAS in young and elderly individuals, we traced effective connectivity of premotor-motor networks and tested their plasticity and relevance to manual dexterity and force in healthy ageing. Our findings provide unprecedent causal evidence of the functional role of the PMv-to-M1 network in young and elderly individuals. The studies presented in this thesis suggest that ccPAS can effectively modulate the strength of connectivity between targeted areas, and coherently manipulate a networks’ behavioral output. Results open new research prospects into the causal role of cortico-cortical connectivity, and provide necessary information to the development of clinical interventions based on connectivity manipulation.

An architecture for network acceleration as a service in the cloud continuum

The pervasive availability of connected devices in any industrial and societal sector is pushing for an evolution of the well-established cloud computing model. The emerging paradigm of the cloud continuum embraces this decentralization trend and envisions virtualized computing resources physically located between traditional datacenters and data sources. By totally or partially executing closer to the network edge, applications can have quicker reactions to events, thus enabling advanced forms of automation and intelligence. However, these applications also induce new data-intensive workloads with low-latency constraints that require the adoption of specialized resources, such as high-performance communication options (e.g., RDMA, DPDK, XDP, etc.). Unfortunately, cloud providers still struggle to integrate these options into their infrastructures. That risks undermining the principle of generality that underlies the cloud computing scale economy by forcing developers to tailor their code to low-level APIs, non-standard programming models, and static execution environments. This thesis proposes a novel system architecture to empower cloud platforms across the whole cloud continuum with Network Acceleration as a Service (NAaaS). To provide commodity yet efficient access to acceleration, this architecture defines a layer of agnostic high-performance I/O APIs, exposed to applications and clearly separated from the heterogeneous protocols, interfaces, and hardware devices that implement it. A novel system component embodies this decoupling by offering a set of agnostic OS features to applications: memory management for zero-copy transfers, asynchronous I/O processing, and efficient packet scheduling. This thesis also explores the design space of the possible implementations of this architecture by proposing two reference middleware systems and by adopting them to support interactive use cases in the cloud continuum: a serverless platform and an Industry 4.0 scenario. A detailed discussion and a thorough performance evaluation demonstrate that the proposed architecture is suitable to enable the easy-to-use, flexible integration of modern network acceleration into next-generation cloud platforms.

Grant-free protocols for massive multiple access

In next generation Internet-of-Things, the overhead introduced by grant-based multiple access protocols may engulf the access network as a consequence of the proliferation of connected devices. Grant-free access protocols are therefore gaining an increasing interest to support massive multiple access. In addition to scalability requirements, new demands have emerged for massive multiple access, including latency and reliability. The challenges envisaged for future wireless communication networks, particularly in the context of massive access, include: i) a very large population size of low power devices transmitting short packets; ii) an ever-increasing scalability requirement; iii) a mild fixed maximum latency requirement; iv) a non-trivial requirement on reliability. To this aim, we suggest the joint utilization of grant-free access protocols, massive MIMO at the base station side, framed schemes to let the contention start and end within a frame, and succesive interference cancellation techniques at the base station side. In essence, this approach is encapsulated in the concept of coded random access with massive MIMO processing. These schemes can be explored from various angles, spanning the protocol stack from the physical (PHY) to the medium access control (MAC) layer. In this thesis, we delve into both of these layers, examining topics ranging from symbol-level signal processing to succesive interference cancellation-based scheduling strategies. In parallel with proposing new schemes, our work includes a theoretical analysis aimed at providing valuable system design guidelines. As a main theoretical outcome, we propose a novel joint PHY and MAC layer design based on density evolution on sparse graphs.