WiMorse: a contactless Morse code text input system using ambient WiFi signals

International audienceRecent years have witnessed advances of Internet of Things (IoT) technologies and their applications to enable contactless sensing and human-computer interaction in smart homes. For people with Motor Neurone Disease (MND), their motion capabilities are severely impaired and they have difficulties interacting with IoT devices and even communicating with other people. As the disease progresses, most patients lose their speech function eventually which makes the widely adopted voice-based solutions fail. In contrast, most patients can still move their fingers slightly even after they have lost the control of their arms and hands. Thus we propose to develop a Morse code based text input system, called WiMorse, which allows patients with minimal single-finger control to input and communicate with other people without attaching any sensor to their fingers. WiMorse leverages ubiquitous commodity WiFi devices to track subtle finger movements contactlessly and encode them as Morse code input. In order to sense the very subtle finger movements, we propose to employ the ratio of the Channel State Information (CSI) between two antennas to enhance the Signal to Noise Ratio. To address the severe location dependency issue in wireless sensing with accurate theoretical underpinning and experiments, we propose a signal transformation mechanism to automatically convert signals based on the input position, achieving stable sensing performance. Comprehensive experiments demonstrate that WiMorse can achieve higher than 95% recognition accuracy for finger generated Morse code, and is robust against input position, environment changes, and user diversity

Building and evaluating an inconspicuous smartphone authentication method

Tese de mestrado em Engenharia Informática, apresentada à Universidade de Lisboa, através da Faculdade de Ciências, 2013Os smartphones que trazemos connosco estão cada vez mais entranhados nas nossas vidas intimas. Estes dispositivos possibilitam novas formas de trabalhar, de socializar, e ate de nos divertirmos. No entanto, também criaram novos riscos a nossa privacidade. Uma forma comum de mitigar estes riscos e configurar o dispositivo para bloquear apos um período de inatividade. Para voltar a utiliza-lo, e então necessário superar uma barreira de autenticação. Desta forma, se o aparelho cair das mãos de outra pessoa, esta não poderá utiliza-lo de forma a que tal constitua uma ameaça. O desbloqueio com autenticação e, assim, o mecanismo que comummente guarda a privacidade dos utilizadores de smartphones. Porem, os métodos de autenticação atualmente utilizados são maioritariamente um legado dos computadores de mesa. As palavras-passe e códigos de identificação pessoal são tornados menos seguros pelo facto de as pessoas criarem mecanismos para os memorizarem mais facilmente. Alem disso, introduzir estes códigos e inconveniente, especialmente no contexto móvel, em que as interações tendem a ser curtas e a necessidade de autenticação atrapalha a prossecução de outras tarefas. Recentemente, os smartphones Android passaram a oferecer outro método de autenticação, que ganhou um grau de adoção assinalável. Neste método, o código secreto do utilizador e uma sucessão de traços desenhados sobre uma grelha de 3 por 3 pontos apresentada no ecrã táctil. Contudo, quer os códigos textuais/numéricos, quer os padrões Android, são suscetíveis a ataques rudimentares. Em ambos os casos, o canal de entrada e o toque no ecrã táctil; e o canal de saída e o visual. Tal permite que outras pessoas possam observar diretamente a introdução da chave; ou que mais tarde consigam distinguir as marcas deixadas pelos dedos na superfície de toque. Alem disso, estes métodos não são acessíveis a algumas classes de utilizadores, nomeadamente os cegos. Nesta dissertação propõe-se que os métodos de autenticação em smartphones podem ser melhor adaptados ao contexto móvel. Nomeadamente, que a possibilidade de interagir com o dispositivo de forma inconspícua poderá oferecer aos utilizadores um maior grau de controlo e a capacidade de se auto-protegerem contra a observação do seu código secreto. Nesse sentido, foi identificada uma modalidade de entrada que não requer o canal visual: sucessões de toques independentes de localização no ecrã táctil. Estes padrões podem assemelhar-se (mas não estão limitados) a ritmos ou código Morse. A primeira contribuição deste trabalho e uma técnica algorítmica para a deteção destas sucessões de toques, ou frases de toque, como chaves de autenticação. Este reconhecedor requer apenas uma demonstração para configuração, o que o distingue de outras abordagens que necessitam de vários exemplos para treinar o algoritmo. O reconhecedor foi avaliado e demonstrou ser preciso e computacionalmente eficiente. Esta contribuição foi enriquecida com o desenvolvimento de uma aplicação Android que demonstra o conceito. A segunda contribuição e uma exploração de fatores humanos envolvidos no uso de frases de toque para autenticação. E consubstanciada em três estudos com utilizadores, em que o método de autenticação proposto e comparado com as alternativas mais comuns: PIN e o padrão Android. O primeiro estudo (N=30) compara os três métodos no que que diz respeito a resistência a observação e à usabilidade, entendida num sentido lato, que inclui a experiencia de utilização (UX). Os resultados sugerem que a usabilidade das três abordagens e comparável, e que em condições de observação perfeitas, nos três casos existe grande viabilidade de sucesso para um atacante. O segundo estudo (N=19) compara novamente os três métodos mas, desta feita, num cenário de autenticação inconspícua. Com efeito, os participantes tentaram introduzir os códigos com o dispositivo situado por baixo de uma mesa, fora do alcance visual. Neste caso, demonstra-se que a autenticação com frases de toque continua a ser usável. Já com as restantes alternativas existe uma diminuição substancial das medidas de usabilidade. Tal sugere que a autenticação por frases de toque suporta a capacidade de interação inconspícua, criando assim a possibilidade de os utilizadores se protegerem contra possíveis atacantes. O terceiro estudo (N=16) e uma avaliação de usabilidade e aceitação do método de autenticação com utilizadores cegos. Neste estudo, são também elicitadas estratégias de ocultação suportadas pela autenticação por frases de toque. Os resultados sugerem que a técnica e também adequada a estes utilizadores.As our intimate lives become more tangled with the smartphones we carry, privacy has become an increasing concern. A widely available option to mitigate security risks is to set a device so that it locks after a period of inactivity, requiring users to authenticate for subsequent use. Current methods for establishing one's identity are known to be susceptible to even rudimentary observation attacks. The mobile context in which interactions with smartphones are prone to occur further facilitates shoulder-surfing. We submit that smartphone authentication methods can be better adapted to the mobile context. Namely, the ability to interact with the device in an inconspicuous manner could offer users more control and the ability to self-protect against observation. Tapping is a communication modality between a user and a device that can be appropriated for that purpose. This work presents a technique for employing sequences of taps, or tap phrases, as authentication codes. An efficient and accurate tap phrase recognizer, that does not require training, is presented. Three user studies were conducted to compare this approach to the current leading methods. Results indicate that the tapping method remains usable even under inconspicuous authentications scenarios. Furthermore, we found that it is appropriate for blind users, to whom usability barriers and security risks are of special concern

Morse Code Datasets for Machine Learning

We present an algorithm to generate synthetic datasets of tunable difficulty on classification of Morse code symbols for supervised machine learning problems, in particular, neural networks. The datasets are spatially one-dimensional and have a small number of input features, leading to high density of input information content. This makes them particularly challenging when implementing network complexity reduction methods. We explore how network performance is affected by deliberately adding various forms of noise and expanding the feature set and dataset size. Finally, we establish several metrics to indicate the difficulty of a dataset, and evaluate their merits. The algorithm and datasets are open-source.Comment: Presented at the 9th International Conference on Computing, Communication and Networking Technologies (ICCCNT

Fuzzy Mouse Cursor Control System for Computer Users with Spinal Cord Injuries

People with severe motor-impairments due to Spinal Cord Injury (SCI) or Spinal Cord Dysfunction (SCD), often experience difficulty with accurate and efficient control of pointing devices (Keates et al., 02). Usually this leads to their limited integration to society as well as limited unassisted control over the environment. The questions “How can someone with severe motor-impairments perform mouse pointer control as accurately and efficiently as an able-bodied person?” and “How can these interactions be advanced through use of Computational Intelligence (CI)?” are the driving forces behind the research described in this paper. Through this research, a novel fuzzy mouse cursor control system (FMCCS) is developed. The goal of this system is to simplify and improve efficiency of cursor control and its interactions on the computer screen by applying fuzzy logic in its decision-making to make disabled Internet users use the networked computer conveniently and easily. The FMCCS core consists of several fuzzy control functions, which define different user interactions with the system. The development of novel cursor control system is based on utilization of motor functions that are still available to most complete paraplegics, having capability of limited vision and breathing control. One of the biggest obstacles of developing human computer interfaces for disabled people focusing primarily on eyesight and breath control is user’s limited strength, stamina, and reaction time. Within the FMCCS developed in this research, these limitations are minimized through the use of a novel pneumatic input device and intelligent control algorithms for soft data analysis, fuzzy logic and user feedback assistance during operation. The new system is developed using a reliable and cheap sensory system and available computing techniques. Initial experiments with healthy and SCI subjects have clearly demonstrated benefits and promising performance of the new system: the FMCCS is accessible for people with severe SCI; it is adaptable to user specific capabilities and wishes; it is easy to learn and operate; point-to-point movement is responsive, precise and fast. The integrated sophisticated interaction features, good movement control without strain and clinical risks, as well the fact that quadriplegics, whose breathing is assisted by a respirator machine, still possess enough control to use the new system with ease, provide a promising framework for future FMCCS applications. The most motivating leverage for further FMCCS development is however, the positive feedback from persons who tested the first system prototype

Body swarm interface (BOSI) : controlling robotic swarms using human bio-signals

Traditionally robots are controlled using devices like joysticks, keyboards, mice and other similar human computer interface (HCI) devices. Although this approach is effective and practical for some cases, it is restrictive only to healthy individuals without disabilities, and it also requires the user to master the device before its usage. It becomes complicated and non-intuitive when multiple robots need to be controlled simultaneously with these traditional devices, as in the case of Human Swarm Interfaces (HSI). This work presents a novel concept of using human bio-signals to control swarms of robots. With this concept there are two major advantages: Firstly, it gives amputees and people with certain disabilities the ability to control robotic swarms, which has previously not been possible. Secondly, it also gives the user a more intuitive interface to control swarms of robots by using gestures, thoughts, and eye movement. We measure different bio-signals from the human body including Electroencephalography (EEG), Electromyography (EMG), Electrooculography (EOG), using off the shelf products. After minimal signal processing, we then decode the intended control action using machine learning techniques like Hidden Markov Models (HMM) and K-Nearest Neighbors (K-NN). We employ formation controllers based on distance and displacement to control the shape and motion of the robotic swarm. Comparison for ground truth for thoughts and gesture classifications are done, and the resulting pipelines are evaluated with both simulations and hardware experiments with swarms of ground robots and aerial vehicles

Evaluating the Effects of Utilizing a Mobile Device by Transitioning High School Students with Intellectual Disability to Locate Items from a Grocery List and Improve their Independence

Individuals with Intellectual Disability (ID) struggle to learn daily living skills (DLS) required for independent living. One specific skill set that is challenging for individuals with ID is grocery shopping. The current study is one of two investigations that have been undertaken entirely in the community and without the use of booster session simulations in a classroom. This study investigated the effects of using least-to-most prompting and mobile technology as a tool to assist 18 to 22-year-old adult students with ID to find six items from a grocery-shopping list. Dependent measures included the number of task steps completed correctly, selecting the correct items from the shopping list, and the duration of shopping. Sessions were conducted twice a week in a community grocery store. A single subject, multiple probe design across participants was employed. There were three phases in this study. The phases included: (a) teaching an initial grocery list, (b) teaching a re-sequenced grocery list, and (c) teaching a replacement grocery list. Overall, the participants demonstrated improvements in their ability to complete the task steps and locate grocery items during the intervention condition in phase one. Two of the three participants’ duration of shopping also improved over the course of the intervention in phase one. However, only one participant advanced to phases two and three of the study as the others did not meet the criterion of achieving 85% or better on the task analysis, which was needed to advance to the subsequent phases of the study. The results of this study suggest that the use of mobile devices used with least-to-most prompting can have a degree of positive effect on the acquisition of functional skills such as locating grocery items by 18 to 22-year-old students with ID. However, for some students either additional weekly sessions in the community setting or classroom simulations are needed. Alternatively, researchers and practitioners might consider pairing mobile technology with different prompting and prompt fading systems (e.g., most-to-least prompting) for students struggling to acquire this skill set in a community setting

Dwell-free input methods for people with motor impairments

Millions of individuals affected by disorders or injuries that cause severe motor impairments have difficulty performing compound manipulations using traditional input devices. This thesis first explores how effective various assistive technologies are for people with motor impairments. The following questions are studied: (1) What activities are performed? (2) What tools are used to support these activities? (3) What are the advantages and limitations of these tools? (4) How do users learn about and choose assistive technologies? (5) Why do users adopt or abandon certain tools? A qualitative study of fifteen people with motor impairments indicates that users have strong needs for efficient text entry and communication tools that are not met by existing technologies. To address these needs, this thesis proposes three dwell-free input methods, designed to improve the efficacy of target selection and text entry based on eye-tracking and head-tracking systems. They yield: (1) the Target Reverse Crossing selection mechanism, (2) the EyeSwipe eye-typing interface, and (3) the HGaze Typing interface. With Target Reverse Crossing, a user moves the cursor into a target and reverses over a goal to select it. This mechanism is significantly more efficient than dwell-time selection. Target Reverse Crossing is then adapted in EyeSwipe to delineate the start and end of a word that is eye-typed with a gaze path connecting the intermediate characters (as with traditional gesture typing). When compared with a dwell-based virtual keyboard, EyeSwipe affords higher text entry rates and a more comfortable interaction. Finally, HGaze Typing adds head gestures to gaze-path-based text entry to enable simple and explicit command activations. Results from a user study demonstrate that HGaze Typing has better performance and user satisfaction than a dwell-time method