Practical interface experiments with implant technology

In this paper results are shown to indicate the efficacy of a direct connection between the human nervous system and a computer network. Experimental results obtained thus far from a study lasting for over 3 months are presented, with particular emphasis placed on the direct interaction between the human nervous system and a piece of wearable technology. An overview of the present state of neural implants is given, as well as a range of application areas considered thus far. A view is also taken as to what may be possible with implant technology as a general purpose human-computer interface for the future.

Cloud-assisted body area networks: state-of-the-art and future challenges

Body area networks (BANs) are emerging as enabling technology for many human-centered application domains such as health-care, sport, fitness, wellness, ergonomics, emergency, safety, security, and sociality. A BAN, which basically consists of wireless wearable sensor nodes usually coordinated by a static or mobile device, is mainly exploited to monitor single assisted livings. Data generated by a BAN can be processed in real-time by the BAN coordinator and/or transmitted to a server-side for online/offline processing and long-term storing. A network of BANs worn by a community of people produces large amount of contextual data that require a scalable and efficient approach for elaboration and storage. Cloud computing can provide a flexible storage and processing infrastructure to perform both online and offline analysis of body sensor data streams. In this paper, we motivate the introduction of Cloud-assisted BANs along with the main challenges that need to be addressed for their development and management. The current state-of-the-art is overviewed and framed according to the main requirements for effective Cloud-assisted BAN architectures. Finally, relevant open research issues in terms of efficiency, scalability, security, interoperability, prototyping, dynamic deployment and management, are discussed.

Energy-efficient hybrid system for Wireless Body Area Network Applications

Wireless Body Area Networks (WBANs) consist of a number of miniaturized wearable or implanted sensor nodes that are employed to monitor vital parameters of a patient over long duration of time. These sensors capture physiological data and wirelessly transfer the collected data to a local base station in order to be further processed. Almost all of these body sensors are expected to have low data-rate and to run on a battery. Since recharging or replacing the battery is not a simple task specifically in the case of implanted devices such as pacemakers, extending the lifetime of sensor nodes in WBANs is one of the greatest challenges. To achieve this goal, WBAN systems employ low-power communication transceivers and low duty cycle Medium Access Control (MAC) protocols. Although, currently used MAC protocols are able to reduce the energy consumption of devices for transmission and reception, yet they are still unable to offer an ultimate energy self-sustaining solution for low-power MAC protocols. This paper proposes to utilize energy harvesting technologies in low-power MAC protocols. This novel approach can further reduce energy consumption of devices in WBAN systems.

Could in-home sensors surpass human observation of people with Parkinson’s at high risk of falling? An ethnographic study

Self-report underpins our understanding of falls among people with Parkinson’s (PwP) as they largely happen unwitnessed at home. In this qualitative study, we used an ethnographic approach to investigate which in-home sensors, in which locations, could gather useful data about fall risk. Over six weeks, we observed five independently mobile PwP at high risk of falling, at home. We made field notes about falls (prior events and concerns) and recorded movement with video, Kinect, and wearable sensors. The three women and two men (aged 71 to 79 years) having moderate or severe Parkinson’s were dependent on others and highly sedentary. We most commonly noted balance protection, loss, and restoration during chair transfers, walks across open spaces and through gaps, turns, steps up and down, and tasks in standing (all evident walking between chair and stairs, e.g.). Our unobtrusive sensors were acceptable to participants: they could detect instability during everyday activity at home and potentially guide intervention. Monitoring the route between chair and stairs is likely to give information without invading the privacy of people at high risk of falling, with very limited mobility, who spend most of the day in their sitting rooms.

A survey on wireless body area networks for eHealthcare systems in residential environments

The progress in wearable and implanted health monitoring technologies has strong potential to alter the future of healthcare services by enabling ubiquitous monitoring of patients. A typical health monitoring system consists of a network of wearable or implanted sensors that constantly monitor physiological parameters. Collected data are relayed using existing wireless communication protocols to the base station for additional processing. This article provides researchers with information to compare the existing low-power communication technologies that can potentially support the rapid development and deployment of WBAN systems, and mainly focuses on remote monitoring of elderly or chronically ill patients in residential environments.

A Computer Vision Framework For Finger-Tapping Evaluation In Parkinson's Disease

Objective: To define and evaluate a Computer-Vision (CV) method for scoring Paced Finger-Tapping (PFT) in Parkinson's disease (PD) using quantitative motion analysis of index-fingers and to compare the obtained scores to the UPDRS (Unified Parkinson's Disease Rating Scale) finger-taps (FT). Background: The naked-eye evaluation of PFT in clinical practice results in coarse resolution to determine PD status. Besides, sensor mechanisms for PFT evaluation may cause patients discomfort. In order to avoid cost and effort of applying wearable sensors, a CV system for non-invasive PFT evaluation is introduced. Methods: A database of 221 PFT videos from 6 PD patients was processed. The subjects were instructed to position their hands above their shoulders besides the face and tap the index-finger against the thumb consistently with speed. They were facing towards a pivoted camera during recording. The videos were rated by two clinicians between symptom levels 0-to-3 using UPDRS-FT. The CV method incorporates a motion analyzer and a face detector. The method detects the face of testee in each video-frame. The frame is split into two images from face-rectangle center. Two regions of interest are located in each image to detect index-finger motion of left and right hands respectively. The tracking of opening and closing phases of dominant hand index-finger produces a tapping time-series. This time-series is normalized by the face height. The normalization calibrates the amplitude in tapping signal which is affected by the varying distance between camera and subject (farther the camera, lesser the amplitude). A total of 15 features were classified using K-nearest neighbor (KNN) classifier to characterize the symptoms levels in UPDRS-FT. The target ratings provided by the raters were averaged. Results: A 10-fold cross validation in KNN classified 221 videos between 3 symptom levels with 75% accuracy. An area under the receiver operating characteristic curves of 82.6% supports feasibility of the obtained features to replicate clinical assessments. Conclusions: The system is able to track index-finger motion to estimate tapping symptoms in PD. It has certain advantages compared to other technologies (e.g. magnetic sensors, accelerometers etc.) for PFT evaluation to improve and automate the ratings

Motion Cues Analysis for Parkinson Gait Recognition

Background: Previous assessment methods for PG recognition used sensor mechanisms for PG that may cause discomfort. In order to avoid stress of applying wearable sensors, computer vision (CV) based diagnostic systems for PG recognition have been proposed. Main constraints in these methods are the laboratory setup procedures: Novel colored dresses for the patients were specifically designed to segment the test body from a specific colored background. Objective: To develop an image processing tool for home-assessment of Parkinson Gait(PG) by analyzing motion cues extracted during the gait cycles. Methods: The system is based on the idea that a normal body attains equilibrium during the gait by aligning the body posture with the axis of gravity. Due to the rigidity in muscular tone, persons with PD fail to align their bodies with the axis of gravity. The leaned posture of PD patients appears to fall forward. Whereas a normal posture exhibits a constant erect posture throughout the gait. Patients with PD walk with shortened stride angle (less than 15 degrees on average) with high variability in the stride frequency. Whereas a normal gait exhibits a constant stride frequency with an average stride angle of 45 degrees. In order to analyze PG, levodopa-responsive patients and normal controls were videotaped with several gait cycles. First, the test body is segmented in each frame of the gait video based on the pixel contrast from the background to form a silhouette. Next, the center of gravity of this silhouette is calculated. This silhouette is further skeletonized from the video frames to extract the motion cues. Two motion cues were stride frequency based on the cyclic leg motion and the lean frequency based on the angle between the leaned torso tangent and the axis of gravity. The differences in the peaks in stride and lean frequencies between PG and normal gait are calculated using Cosine Similarity measurements. Results: High cosine dissimilarity was observed in the stride and lean frequencies between PG and normal gait. High variations are found in the stride intervals of PG whereas constant stride intervals are found in the normal gait. Conclusions: We propose an algorithm as a source to eliminate laboratory constraints and discomfort during PG analysis. Installing this tool in a home computer with a webcam allows assessment of gait in the home environment.

Introdução à interação humano-computador

Iniciada apresentando o contexto da área de nteração Humano Computador (IHC). O histórico da área é dividido em fases, sendo que a primeira fase é definida pela pouca interface, ou seja, grandes máquinas em que a interação com o usuário era mínima; a segunda fase é caracterizada pelos prompts de comando; a terceira fase é composta pela interação com janelas, interfaces, menus e ponteiros do mouse; a quarta fase compões os movimentos de realidade virtual, interfaces tangíveis, computação usável (wearable computing). A IHC é uma área multidisciplinar visto que deve trabalhar tanto com aspectos relacionados à máquina quanto ao ser humano

Social fabrics

Existing wearable computing research and indeed commercial products, have explored how to control phones and music players in pockets. They have typically relied on interaction via simple flexible button sensors. This thesis proposes, design and develops new ways of interacting which explore the potential of clothes, such as pulling or stretching. Its aim to present and demonstrate the value of embodied and intuitive inputs based on standard clothing elements such as zips, fasteners, beads, Velcro and magnets. Individual interactions for each are described and discussed before a final combination application, the MusicHoodie, which is developed to control an MP3 player. A simple usability test on this system reveals a range of interesting and promising results about which were the most acceptable and understandable inputs. This thesis closes with a discussion of the implications and contributions of the work it presents.

WalkNRide: contextualising feedback in physical activity trackers

Increasing levels of sedentarism and obesity, along with advances in sensor technologies have instigated a market for wearable activity trackers, electronic devices that sense users’ physical activity levels with the goals of self-monitoring and behaviour change. Nowadays, activity trackers are one of the most desirable technologies, making up for a market of over $230 million in 2013. However, despite the spike of users’ interest, activity trackers have been shown to lose their appeal over time, with a recent survey suggesting that one out of three users discard the tracker in the course of the first six months of use. The question we pose is: how can we design activity tracker so that users’ interests is sustained over the long term? Our design approach focuses on contextualising physical activity. We do this through sensing users’ locations and activities (such as being still, walking or commuting through a car, bus or other means) and thus providing innovative ways of presenting feedback on users. This thesis presents the design and evaluation of WalkNRide, a physical activity tracker for Google Android. Through a longitudinal field study of WalkNRide, we attempt to inquire into the factors that drive the adoption (or non-adoption) of the tool as well as the ways in which the use of the tool contributes towards habit formation.

The correlation between thermal comfort in buildings and fashion products

This article is about thermal comfort in the wearable product. The research correlates fashion and architecture, in so far as it elects the brise soleil - an architectural element capable of regulating temperature and ventilation inside buildings - as a study referential, in trying to transpose and adapt its mechanisms to the wearable apparel.

Novel wireless-communicating textiles made from multi-material and minimally-invasive fibers

The ability to integrate multiple materials into miniaturized fiber structures enables the realization of novel biomedical textile devices with higher-level functionalities and minimally-invasive attributes. In this work, we present novel textile fabrics integrating unobtrusive multi-material fibers that communicate through 2.4 GHz wireless networks with excellent signal quality. The conductor elements of the textiles are embedded within the fibers themselves, providing electrical and chemical shielding against the environment, while preserving the mechanical and cosmetic properties of the garments. These multi-material fibers combine insulating and conducting materials into a well-defined geometry, and represent a cost-effective and minimally-invasive approach to sensor fabrics and bio-sensing textiles connected in real time to mobile communications infrastructures, suitable for a variety of health and life science applications.

Ergonomia e design de vestimentas ocupacionais no Brasil: foco em equipamentos de proteção individual no setor de petróleo e gás

Pós-graduação em Design - FAAC

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.

Context detection and abstraction in smart environments

Context-aware computing is currently considered the most promising approach to overcome information overload and to speed up access to relevant information and services. Context-awareness may be derived from many sources, including user profile and preferences, network information, sensor analysis; usually context-awareness relies on the ability of computing devices to interact with the physical world, i.e. with the natural and artificial objects hosted within the "environment”. Ideally, context-aware applications should not be intrusive and should be able to react according to user’s context, with minimum user effort. Context is an application dependent multidimensional space and the location is an important part of it since the very beginning. Location can be used to guide applications, in providing information or functions that are most appropriate for a specific position. Hence location systems play a crucial role. There are several technologies and systems for computing location to a vary degree of accuracy and tailored for specific space model, i.e. indoors or outdoors, structured spaces or unstructured spaces. The research challenge faced by this thesis is related to pedestrian positioning in heterogeneous environments. Particularly, the focus will be on pedestrian identification, localization, orientation and activity recognition. This research was mainly carried out within the “mobile and ambient systems” workgroup of EPOCH, a 6FP NoE on the application of ICT to Cultural Heritage. Therefore applications in Cultural Heritage sites were the main target of the context-aware services discussed. Cultural Heritage sites are considered significant test-beds in Context-aware computing for many reasons. For example building a smart environment in museums or in protected sites is a challenging task, because localization and tracking are usually based on technologies that are difficult to hide or harmonize within the environment. Therefore it is expected that the experience made with this research may be useful also in domains other than Cultural Heritage. This work presents three different approaches to the pedestrian identification, positioning and tracking: Pedestrian navigation by means of a wearable inertial sensing platform assisted by the vision based tracking system for initial settings an real-time calibration; Pedestrian navigation by means of a wearable inertial sensing platform augmented with GPS measurements; Pedestrian identification and tracking, combining the vision based tracking system with WiFi localization. The proposed localization systems have been mainly used to enhance Cultural Heritage applications in providing information and services depending on the user’s actual context, in particular depending on the user’s location.