A Customizable Camera-based Human Computer Interaction System Allowing People With Disabilities Autonomous Hands Free Navigation of Multiple Computing Task

Many people suffer from conditions that lead to deterioration of motor control and makes access to the computer using traditional input devices difficult. In particular, they may loose control of hand movement to the extent that the standard mouse cannot be used as a pointing device. Most current alternatives use markers or specialized hardware to track and translate a user's movement to pointer movement. These approaches may be perceived as intrusive, for example, wearable devices. Camera-based assistive systems that use visual tracking of features on the user's body often require cumbersome manual adjustment. This paper introduces an enhanced computer vision based strategy where features, for example on a user's face, viewed through an inexpensive USB camera, are tracked and translated to pointer movement. The main contributions of this paper are (1) enhancing a video based interface with a mechanism for mapping feature movement to pointer movement, which allows users to navigate to all areas of the screen even with very limited physical movement, and (2) providing a customizable, hierarchical navigation framework for human computer interaction (HCI). This framework provides effective use of the vision-based interface system for accessing multiple applications in an autonomous setting. Experiments with several users show the effectiveness of the mapping strategy and its usage within the application framework as a practical tool for desktop users with disabilities.

A time-domain approach to the analysis and modeling of on-body propagation characteristics using synchronized measurements at 2.45 GHz

Modeling of on-body propagation channels is of paramount importance to those wishing to evaluate radio channel performance for wearable devices in body area networks (BANs). Difficulties in modeling arise due to the highly variable channel conditions related to changes in the user's state and local environment. This study characterizes these influences by using time-series analysis to examine and model signal characteristics for on-body radio channels in user stationary and mobile scenarios in four different locations: anechoic chamber, open office area, hallway, and outdoor environment. Autocorrelation and cross-correlation functions are reported and shown to be dependent on body state and surroundings. Autoregressive (AR) transfer functions are used to perform time-series analysis and develop models for fading in various on-body links. Due to the non-Gaussian nature of the logarithmically transformed observed signal envelope in the majority of mobile user states, a simple method for reproducing the failing based on lognormal and Nakagami statistics is proposed. The validity of the AR models is evaluated using hypothesis testing, which is based on the Ljung-Box statistic, and the estimated distributional parameters of the simulator output compared with those from experimental results.

Upper limb tremor suppression in ADL via an orthosis incorporating a controllable double viscous beam actuator

Neuromuscular disorders affect millions of people world-wide. Upper limb tremor is a common symptom, and due to its complex aetiology it is difficult to compensate for except, in particular cases by surgical intervention or drug therapy. Wearable devices that mechanically compensate for limb tremor could benefit a considerable number of patients, but the technology to assist suffers in this way is under-developed. In this paper we propose an innovative orthosis that can dynamically suppress pathological tremor, by applying viscous damping to the affected limb in a controlled manner. The orthosis design utilises a new actuator design based on Magneto-Rheological Fluids that efficiently deliver damping action in response to the instantaneous tremor frequency and amplitude.

Strategie di elaborazione di tracciati GPS per reti veicolari

Il proliferare di dispositivi di elaborazione e comunicazione mobili (telefoni cellulari, computer portatili, PDA, wearable devices, personal digital assistant) sta guidando un cambiamento rivoluzionario nella nostra società dell'informazione. Si sta migrando dall'era dei Personal Computer all'era dell'Ubiquitous Computing, in cui un utente utilizza, parallelamente, svariati dispositivi elettronici attraverso cui può accedere a tutte le informazioni, ovunque e quantunque queste gli si rivelino necessarie. In questo scenario, anche le mappe digitali stanno diventando sempre più parte delle nostre attività quotidiane; esse trasmettono informazioni vitali per una pletora di applicazioni che acquistano maggior valore grazie alla localizzazione, come Yelp, Flickr, Facebook, Google Maps o semplicemente le ricerche web geo-localizzate. Gli utenti di PDA e Smartphone dipendono sempre più dai GPS e dai Location Based Services (LBS) per la navigazione, sia automobilistica che a piedi. Gli stessi servizi di mappe stanno inoltre evolvendo la loro natura da uni-direzionale a bi-direzionale; la topologia stradale è arricchita da informazioni dinamiche, come traffico in tempo reale e contenuti creati dagli utenti. Le mappe digitali aggiornabili dinamicamente sono sul punto di diventare un saldo trampolino di lancio per i sistemi mobili ad alta dinamicità ed interattività, che poggiando su poche informazioni fornite dagli utenti, porteranno una moltitudine di applicazioni innovative ad un'enorme base di consumatori. I futuri sistemi di navigazione per esempio, potranno utilizzare informazioni estese su semafori, presenza di stop ed informazioni sul traffico per effettuare una ottimizzazione del percorso che valuti simultaneamente fattori come l'impronta al carbonio rilasciata, il tempo di viaggio effettivamente necessario e l'impatto della scelta sul traffico locale. In questo progetto si mostra come i dati GPS raccolti da dispositivi fissi e mobili possano essere usati per estendere le mappe digitali con la locazione dei segnali di stop, dei semafori e delle relative temporizzazioni. Queste informazioni sono infatti oggi rare e locali ad ogni singola municipalità, il che ne rende praticamente impossibile il pieno reperimento. Si presenta quindi un algoritmo che estrae utili informazioni topologiche da agglomerati di tracciati gps, mostrando inoltre che anche un esiguo numero di veicoli equipaggiati con la strumentazione necessaria sono sufficienti per abilitare l'estensione delle mappe digitali con nuovi attributi. Infine, si mostrerà come l'algoritmo sia in grado di lavorare anche con dati mancanti, ottenendo ottimi risultati e mostrandosi flessibile ed adatto all'integrazione in sistemi reali.

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.

Progettazione ed implementazione di un dispositivo portabile per l'acquisizione ed il filtraggio di segnali biomedici

The use of wearable devices for the monitoring of biological potentials is an ever-growing area of research. Wearable devices for the monitoring of vital signs such as heart-rate, respiratory rate, cardiac output and blood oxygenation are necessary in determining the overall health of a patient and allowing earlier detection of adverse events such as heart attacks and strokes and earlier diagnosis of disease. This thesis describes a bio-potential acquisition embedded system designed with an innovative analog front-end, showing the performance in EMG and ECG applications and the comparison between different noise reduction algorithms. We demonstrate that the proposed system is able to acquire bio-potentials with a signal quality equivalent to state of the art bench-top biomedical devices and can be therefore used for monitoring purpose, with the advantages of a low-cost low-power wearable device.

Architetture per smart health: il caso FitStadium

L'obiettivo della tesi è progettare un'architettura abilitante per scenari smart health, concentrandosi sulla parte end-user (non sulla parte server-cloud), ossia sperimentando l'ambito dei wearable devices e facendo riferimento al binomio fitness-Apple Watch, comodo perchè presente nell'azienda FitStadium che ci fornisce motivazioni, requisiti e goals. Nel primo capitolo si analizzeranno le soluzioni offerte attualmente dal mercato per la realizzazione di servizi legati al fitness, focalizzandosi in particolare sulle architetture proposte e come quest'ultime possano convivere con l'ecosistema FitStadium. Il secondo capitolo è riservato invece all'approfondimento delle tecnologie Apple, che verranno utilizzate concretamente per la realizzazione del caso di studio. Ancora una volta si farà attenzione alle possibilità architetturali offerte da queste tecnologie. Nel terzo capitolo viene trattato nella sua interezza il caso di studio, analizzandone in particolare lo stato pre e post tesi. Verrà cioè descritta l'applicazione implementata insieme alla presentazione di un'architettura abilitante anche per gli scenari smart health. Infine, all'interno del capito 4 viene descritto più precisamente il concetto di smart health e il percorso che ha condotto alla sua definizione.

An Adjustable Compliant Joint for Lower-Limb Exoskeletons

The field of exoskeletons and wearable devices for walking assistance and rehabilitation has advanced considerably over the past few years. Currently, commercial devices contain joints with stiff actuators that cannot adapt to unpredictable environments. These actuators consume more energy and may not be appropriate for human-machine interactions. Thus, adjustable compliant actuators are being cautiously incorporated into new exoskeletons and active orthoses. Some simulation-based studies have evaluated the benefits of incorporating compliant joints into such devices. Another reason that compliant actuators are desirable is that spasticity and spasmodic movements are common among patients with motor deficiencies; compliant actuators could efficiently absorb these perturbations and improve joint control. In this paper, we provide an overview of the requirements that must be fulfilled by these actuators while evaluating the behavior of leg joints in the locomotion cycle. A brief review of existing compliant actuators is conducted, and our proposed variable stiffness actuator prototype is presented and evaluated. The actuator prototype is implemented in an exoskeleton knee joint operated by a state machine that exploits the dynamics of the leg, resulting in a reduction in actuation energy demand and better adaptability to disturbances.

Efficient Multi-hop Broadcast Data Dissemination in IoT and Smart Cities

Internet of Things (IoT) can be defined as a “network of networks” composed by billions of uniquely identified physical Smart Objects (SO), organized in an Internet-like structure. Smart Objects can be items equipped with sensors, consumer devices (e.g., smartphones, tablets, or wearable devices), and enterprise assets that are connected both to the Internet and to each others. The birth of the IoT, with its communications paradigms, can be considered as an enabling factor for the creation of the so-called Smart Cities. A Smart City uses Information and Communication Technologies (ICT) to enhance quality, performance and interactivity of urban services, ranging from traffic management and pollution monitoring to government services and energy management. This thesis is focused on multi-hop data dissemination within IoT and Smart Cities scenarios. The proposed multi-hop techniques, mostly based on probabilistic forwarding, have been used for different purposes: from the improvement of the performance of unicast protocols for Wireless Sensor Networks (WSNs) to the efficient data dissemination within Vehicular Ad-hoc NETworks (VANETs).

A paradigm shift for mobile interaction:a decade later

In the proceedings of CASCON'2003 we published an article entitled "A Paradigm Shift: Alternative Interaction Techniques for Use with Mobile & Wearable Devices" and were honoured to receive the Best Paper Award for that year's conference. A decade on, we are equally honoured to have the same paper recognised as the Most Influential Paper of the 2003 conference. To this end, we have been asked to provide a brief overview of our intervening research in relation to that original publication, and so that is the purpose of this extended abstract.

Riconoscimento real-time di gesture tramite tecniche di machine learning

Il riconoscimento delle gesture è un tema di ricerca che sta acquisendo sempre più popolarità, specialmente negli ultimi anni, grazie ai progressi tecnologici dei dispositivi embedded e dei sensori. Lo scopo di questa tesi è quello di utilizzare alcune tecniche di machine learning per realizzare un sistema in grado di riconoscere e classificare in tempo reale i gesti delle mani, a partire dai segnali mioelettrici (EMG) prodotti dai muscoli. Inoltre, per consentire il riconoscimento di movimenti spaziali complessi, verranno elaborati anche segnali di tipo inerziale, provenienti da una Inertial Measurement Unit (IMU) provvista di accelerometro, giroscopio e magnetometro. La prima parte della tesi, oltre ad offrire una panoramica sui dispositivi wearable e sui sensori, si occuperà di analizzare alcune tecniche per la classificazione di sequenze temporali, evidenziandone vantaggi e svantaggi. In particolare, verranno considerati approcci basati su Dynamic Time Warping (DTW), Hidden Markov Models (HMM), e reti neurali ricorrenti (RNN) di tipo Long Short-Term Memory (LSTM), che rappresentano una delle ultime evoluzioni nel campo del deep learning. La seconda parte, invece, riguarderà il progetto vero e proprio. Verrà impiegato il dispositivo wearable Myo di Thalmic Labs come caso di studio, e saranno applicate nel dettaglio le tecniche basate su DTW e HMM per progettare e realizzare un framework in grado di eseguire il riconoscimento real-time di gesture. Il capitolo finale mostrerà i risultati ottenuti (fornendo anche un confronto tra le tecniche analizzate), sia per la classificazione di gesture isolate che per il riconoscimento in tempo reale.

Electrical characterization of electronic circuits produced by inkjet printing

Dissertação de Mestrado, Engenharia Electrónica e Telecomunicações, Faculdade de Ciências e Tecnologia, Universidade do Algarve, 2014

Beyond wearable medical devices

An overview of the human side of the wearable technology trend in the medical industry. Forecasted as the next wave of technological innovations, wearable and physically embedded medical devices to help manage patients’ health conditions are set to change the healthcare experience for both patients and healthcare providers. The idea here is to pay closer attention to how particular patients experience these devices, so they can be designed with empathy for specific patient needs to maintain optimum health.

Calibration and validation of wearable monitors

Background Wearable monitors are increasingly being used to objectively monitor physical activity in research studies within the field of exercise science. Calibration and validation of these devices are vital to obtaining accurate data. This article is aimed primarily at the physical activity measurement specialist, although the end user who is conducting studies with these devices also may benefit from knowing about this topic. Best Practices Initially, wearable physical activity monitors should undergo unit calibration to ensure interinstrument reliability. The next step is to simultaneously collect both raw signal data (e.g., acceleration) from the wearable monitors and rates of energy expenditure, so that algorithms can be developed to convert the direct signals into energy expenditure. This process should use multiple wearable monitors and a large and diverse subject group and should include a wide range of physical activities commonly performed in daily life (from sedentary to vigorous). Future Directions New methods of calibration now use "pattern recognition" approaches to train the algorithms on various activities, and they provide estimates of energy expenditure that are much better than those previously available with the single-regression approach. Once a method of predicting energy expenditure has been established, the next step is to examine its predictive accuracy by cross-validating it in other populations. In this article, we attempt to summarize the best practices for calibration and validation of wearable physical activity monitors. Finally, we conclude with some ideas for future research ideas that will move the field of physical activity measurement forward.