Studio e sviluppo di sistemi innovativi per eHealth e mHealth tramite l’impiego di WBSN e mobile computing

L'evoluzione nel campo dell'elettronica, dell'informatica e delle telecomunicazioni, sempre più imponente negli ultimi anni, ha prodotto nuove tecnologie la cui diffusione sta diventando progressivamente più capillare. Queste innovazioni stanno apportando notevoli cambiamenti in molti settori della società e rivoluzionando le abitudini di tutti noi. Questa tesi di dottorato è rivolta al mondo del Remote Patient Monitoring mediante la ricerca e lo sviluppo di tecnologie altamente innovative che possano apportare innegabili vantaggi in tale settore. Lo scopo principale è, quindi, di proporre soluzioni all'avanguardia per un monitoraggio remoto completo e continuativo di pazienti nelle loro abitazioni o in mobilità. In particolare, le soluzioni che verranno descritte sono caratterizzate da una profonda multidisciplinarità, riguardando la cooperazione tra i settori dei sensori indossabili, delle Wireless Sensor Network, dell'elaborazione di segnali biomedicali, e della gestione tramite applicazioni web dei dati e delle telecomunicazioni in ambito medico. I vari capitoli dell'elaborato presentano una serie di sistemi che sfruttano le tecnologie abilitanti appena citate e che riguardano il monitoraggio dell'attività cardiaca, dell'attività respiratoria e della temperatura corporea localizzata, nonché l'analisi del movimento per applicazioni di fall detection. In aggiunta viene presentato un sistema di tele-consulenza medica peer-to-peer, basato esclusivamente su un applicativo web che permette anche la condivisione in tempo reale di segnali e parametri vitali acquisiti tramite sensori indossabili. Infine, viene presentato un possibile anello di congiunzione tra i vari sistemi di monitoraggio qui proposti, ovvero una Wireless Sensor Network integrante uno stack TCP/IP completo e compatibile con le reti IP tradizionali. Questa soluzione mira a garantire l'interoperabilità tra i sensori indossabili (o reti di sensori indossabili) e altre tipologie di sistemi, come ad esempio sensori ambientali per l'Ambient Assisted Living, reti di sensori per il monitoraggio di parametri ambientali, o impianti di Home Automation, il tutto sfruttando un unico protocollo per le comunicazioni, ovvero lo standard IP, ed aprendo le porte allo scenario dell'Internet of Things.The latest innovations in electronics, informatics and telecommunications have introduced new technologies that now are increasingly spread. These innovations are bringing notable changes in many areas of society, and are revolutionizing our habits. This PhD thesis is addressed to the world of Remote Patient Monitoring, and to the research and development of highly innovative technologies that can bring undeniable advantages in this sector. Therefore, the main purpose is to propose advanced solutions for a comprehensive and continuous remote monitoring of patients in their homes or on the move. In particular, the solutions discussed herein are characterized by a multidisciplinary approach, involving fields of wearable sensors, Wireless Sensor Networks, processing of biomedical signals, and management and communication of patients data via web applications. The various chapters of the elaborate describe a series of systems that exploit the just mentioned enabling technologies, concerning the monitoring of cardiac activity, respiratory activity and localized body temperature, and motion analysis for fall detection applications. In addition, the proposal of a peer-to-peer medical tele-consultation system is detailed. It is exclusively based on a web application that enables the real-time sharing of vital signals and parameters acquired via wearable sensors. Finally, a Wireless Sensor Network based on a full TCP/IP stack is presented. It may be the link between the various monitoring systems proposed in the thesis and is completely compatible with traditional IP networks. This solution is designed to ensure the interoperability between wearable sensors (or networks of wearable sensors) and other types of systems, such as environmental sensors for Ambient Assisted Living, sensor networks for environmental parameters monitoring, or Home Automation equipment. All of this is ensured by the use of a unique communication protocol - the IP - that leads us in the Internet of Things world

Real-time apnea detection using pressure sensor and tri-axial accelerometer

Respiratory disorders, if diagnosed late and untreated, may cause the advancement of many pathologies especially pertaining the cardiovascular system. This study proposes a method for a fast and certain detection of apnea events. For this purpose we used a commercial device that contains a pressure sensor helpful for the measurement of breath and a tri-axial accelerometer necessary to improve the detection reliability. There are numerous commercial devices able to detect breathing, but the totality of them is oriented to sport activity monitoring and so calibrated on the upper thresholds of respiratory rate. These devices are therefore not directly used as biomedical devices specific for the detection of sleep apneas or as life-saving devices in the case of “voluntary” apneas that occur in patients with severe neurological or pathological disorders. Then, we have developed complex algorithms to process the signals in real-time for the detection of apnea events with a maximum delay of 10 s, a sensitivity of 99%, and a specificity of 100%. This paper shows how an inexpensive approach is possible to control dependably the occurrence of apneas, avoiding hospitalization and the use of complex, invasive, and expensive devices

An Android-Based Heart Monitoring System for the Elderly and for Patients with Heart Disease

The current trend in health monitoring systems is to move from the hospital to portable personal devices. This work shows how consumer devices like heart rate monitors can be used not only for applications in sports, but also for medical research and diagnostic purposes. The goal pursued by our group was to develop a simple, accurate, and inexpensive system that would use a few pieces of data acquired by the heart rate monitor and process them on a smartphone to (i) provide detailed test reports about the user’s health state; (ii) store report records; (iii) generate emergency calls or SMSs; and (iv) connect to a remote telemedicine portal to relay the data to an online database. The system developed by our team uses sophisticated algorithms to detect stress states, detect and classify arrhythmia events, and calculate energy consumption. It is suitable for use by elderly subjects and by patients with heart disease (e.g., those recovering from myocardial infarction) or neurological conditions such as Parkinson’s disease. Easy, immediate, and economical remote health control can therefore be achieved without the need for expensive hospital equipment, using only portable consumer devices

A High Reliability Wearable Device for Elderly Fall Detection

Falls are critical events among elderly people that requires timely rescue. In this paper, we propose a fall detection system consisting of an inertial unit that includes triaxial accelerometer, gyroscope, and magnetometer with efficient data fusion and fall detection algorithms. Starting from the raw data, the implemented orientation filter provides the correct orientation of the subject in terms of yaw, pitch, and roll angles. The system is tested according to experimental protocols, engaging volunteers who performed simulated falls, simulated falls with recovery, and activities of daily living. By placing our wearable sensor on the waist of the subject, the unit is able to achieve fall detection performance above those of similar systems proposed in literature. The results obtained through commonly adopted protocols show excellent accuracy, sensitivity and specificity, improving the results of other techniques proposed in the literature

IPv6 WSN solution for integration and interoperation between smart home and AAL systems

The latest advances in electronic and telecommunication have led to the introduction of intelligent and complex systems: the Wireless Sensor Networks. This technology has become even more important with the advent of the Internet of Things: each node acquires an IPv6 address and can be directly accessed from remote when the switch from IPv4 to IPv6 will take place. Such systems are actually applied in environment monitoring, home automation, industry, and lot of other fields. The Ambient Assisted Living scenery is a perfect field of application for sensor networks based on the IP protocol. The monitoring of elderly people, the automation of home appliances and the assistance to the person can be easily achieved through a network based on IPv6. Furthermore, such a system allows to obtain a maximum interoperability with existent networks, avoiding the need for inconvenient gateways to interface systems with different communication protocols. The presented work describes a complete hardware and software system able to solve the interoperability issue among Smart Home and Ambient Assisted Living. Sub GHz frequency, mesh topology and low power consumption give a competitive advantage to the system against Bluetooth Low Energy or ZigBee technology

Indoor localization system for AAL over IPv6 WSN

Wireless Sensor Networks are becoming even more a key element in networking and telecommunications especially with the advent of the Internet of Things paradigm, where each single device obtains a unique IPv6 address and is potentially reachable from everywhere through the Internet. Such technologies can be applied in many application fields with great success in terms of optimization of costs and resources, variety of implemented features, level of customization and expandability of each solution. Ambient Assisted Living is definitely one of the most interesting area for WSN and IoT application. In this scenery we propose an applicative example of the use of a IPv6 self configuring WSN with mesh topology. The network is formed by low cost and low power sensor nodes that integrate sub-GHz radio connectivity, belonging to the so-called LLN (Low Power and Lossy Network) scenery. The network stack is fully compatible with the major RFCs about Internet and wireless communications (CSMA, 6LowPAN, uIP, UDP, CoAP, etc.). The case study is a localization system using RSSI feature and does not need additional expensive hardware to be integrated into the nodes. The system proves to be fundamental in indoor environments (houses, clinics, nursing homes) for AAL systems that require localization or tracking of patients and medical equipments. Our tests are performed in extremely complex environment and shown good results localizing targets with an average error of about 2 meters that allows to properly detect the room where targets are located

A WSN Integrated Solution System for Technological Support to the Self-Sufficient Elderly

The proposed system is basically an automatic dispenser of medicines which integrates functionalities of remote and real-time monitoring of the activities of the elderly in home environment. It includes the generation of alarms resulting from the omission of taking medicines and other critical events such as the permanence of the elderly in a room for a period not consistent with normal daily activities. The main elements of this system are a pair of LED smart lamps called MARCH’ingegno and Sibilla, the first one is the dispenser of medicines which embeds WSN coordinator role, located in the house of the elderly, the other is the displays of real-time alarms, located in the house of relatives or caregiver. The mobility monitoring system is composed of wireless sensor nodes distributed in the house of the elderly. MARCH’ingegno acquires information from these sensors through its RF interface, processes it and transfers the report to a remote web server together with the notes of taking medicines. The tests show that the system operates properly and the wireless sensor nodes ditributed at home provide an adequate coverage area and correct response times

Performance evaluation of a Pedestrian Navigation System based on an objective experimental method

The ability to estimate the distance covered and the orientation of a person, regardless from where he or she is located, is an important aspect in various research areas and in particular in Pedestrian Navigation Systems (PNS) for emergency responders. In this paper we present a PNS based on a wearable wireless device attached to the instep of the pedestrian. The implemented real time algorithm, is able to identify pedestrian's strides, estimating theirs length and direction by using information provided from an embedded Inertial Measurement Unit (IMU). The proposed device is also equipped with MicroSD slot and Bluetooth module for data storage and for sending information in real time. The proposed system has been tested through an objective experimental method in which ten volunteers were walking along three different tracks, five times each, keeping the IMU attached to the instep. In the first trial subjects walked along a straight path that is 90m long, in the second they walked twice along a rectangular path with long side equal to 15m and short side equal to 7.5m and in the last they walked 400m along a standard athletics track. For each test we computed absolute and average error. The results show that the average error is 3.52% for the straight track, 1.09% for the rectangular track and 3.71% for the elliptic track

A Versatile WSN Approach for Smart Environments in AAL Application

We propose the general architecture of a scaled physical world that is richly and invisibly interwoven with a variety of heterogeneous sensors, actuators, seamlessly embedded in everyday live objects, and connected through a unique IPv6 wireless network. The use of the Internet Protocol (IP) stack in Wireless Sensor Networks architecture is a key prerequisite for the Internet of Things (IoT) paradigm. The ability to connect thousands of smart objects, scattered across physical environment, directly to the Internet opens exciting scenarios for a variety of application areas, such as e-health, smart metering, smart home, logistics, home automation, AAL, etc. Furthermore, it allows to achieve the desired interoperability requirement between the previous systems that to date make use of heterogeneous protocols and G2G communications. The strength of the developed system is its versatility and scalability relatively to the number and density of deployed nodes, network typology and types of actuators and sensing units that can be easily integrated in each node. The variety of measurements for the constant care and safety of person living in the environment monitored by the WSN can be easily extended by adding to the network new types of nodes. The paper describes the proposed system’s major building blocks, its functionalities, the implementation approach and the realized application for indoor localization

SVM-based fall detection method for elderly people using Android low-cost smartphones

Nowadays society is moving to a scenery where autonomous elderly live alone in their houses. An automatic remote monitoring system using wearable and ambient sensors is becoming even more important, and is a challenge for the future in WSNs, AAL, and Home Automation areas. Relating to this, one of the most critical events for the safety and the health of the elderly is the fall. Lot of methods, applications, and stand-alone devices have been presented so far. This work proposes a novel method based on the Support Vector Machine technique and addressed to Android low-cost smartphones. Our method starts from data acquired from accelerometer and magnetometer, now available in all the low-end devices, and uses a set of features extracted from a processing of the two signals. After an initial training, the classification of fall events and non-fall events is performed by the Support Vector Machine algorithm. Since we have decided to use the smartphone as monitoring device, the use of other invasive wearable sensors is avoided, and the user have simply to hold the phone on his pocket. Moreover, we can use the cellular network for the eventual sending of notifications and alerts to relatives in case of falls. Actually, our tests show a good performance with a sensitivity of 99.3% and a specificity of 96%