An Epiduroscopy Simulator Based on a Serious Game for Spatial Cognitive Training (EpiduroSIM): User-Centered Design Approach

Background: Performing high-level surgeries with endoscopy is challenging, and hence, an efficient surgical training method or system is required. Serious game-based simulators can provide a trainee-centered educational environment unlike traditional teacher-centered education environments since serious games provide a high level of interaction (feedback that induces learning). Objective: This study aimed to propose an epiduroscopy simulator, EpiduroSIM, based on a serious game for spatial cognitive training. Methods: EpiduroSIM was designed based on a serious game. For spatial cognitive training, the virtual environment of EpiduroSIM was modeled based on a cognitive map. Results: EpiduroSIM was developed considering user accessibility to provide various functions. The experiment for the validation of EpiduroSIM focused on psychological fidelity and repetitive training effects. The experiments were conducted by dividing 16 specialists into 2 groups of 8 surgeons. The group was divided into beginner and expert based on their epiduroscopy experience. The psychological fidelity of EpiduroSIM was confirmed through the training results of the expert group rather than the beginner group. In addition, the repetitive training effect of EpiduroSIM was confirmed by improving the training results in the beginner group. Conclusions: EpiduroSIM may be useful for training beginner surgeons in epiduroscopy.ope

Characterizing Computer Access Using a One-Channel EEG Wireless Sensor

This work studies the feasibility of using mental attention to access a computer. Brain activity was measured with an electrode placed at the Fp1 position and the reference on the left ear; seven normally developed people and three subjects with cerebral palsy (CP) took part in the experimentation. They were asked to keep their attention high and low for as long as possible during several trials. We recorded attention levels and power bands conveyed by the sensor, but only the first was used for feedback purposes. All of the information was statistically analyzed to find the most significant parameters and a classifier based on linear discriminant analysis (LDA) was also set up. In addition, 60% of the participants were potential users of this technology with an accuracy of over 70%. Including power bands in the classifier did not improve the accuracy in discriminating between the two attentional states. For most people, the best results were obtained by using only the attention indicator in classification. Tiredness was higher in the group with disabilities (2.7 in a scale of 3) than in the other (1.5 in the same scale); and modulating the attention to access a communication board requires that it does not contain many pictograms (between 4 and 7) on screen and has a scanning period of a relatively high tscan 10 s. The information transfer rate (ITR) is similar to the one obtained by other brain computer interfaces (BCI), like those based on sensorimotor rhythms (SMR) or slow cortical potentials (SCP), and makes it suitable as an eye-gaze independent BCI

An Overview of Serious Games

Serious games are growing rapidly as a gaming industry as well as a field of academic research. There are many surveys in the field of digital serious games; however, most surveys are specific to a particular area such as education or health. So far, there has been little work done to survey digital serious games in general, which is the main goal of this paper. Hence, we discuss relevant work on serious games in different application areas including education, well-being, advertisement, cultural heritage, interpersonal communication, and health care. We also propose a taxonomy for digital serious games, and we suggest a classification of reviewed serious games applications from the literature against the defined taxonomy. Finally, the paper provides guidelines, drawn from the literature, for the design and development of successful serious games, as well as discussing research perspectives in this domain

Piezoresistive Breathing Sensing System with 3D Printed Wearable Casing

Respiratory rate is an important parameter for many health, home care, work, or sport applications. In this paper, a new wearable sensing system based on a piezoresistive FlexiForce sensor has been developed. The sensor can be attached to any common chest strap. A compact 3D casing has been designed and printed with a 3D printer. This casing integrates the sensor and all auxiliary elements of the system: microcontroller, battery, Bluetooth module, connections, battery charger, and acquisition circuit. To the best of our knowledge, this is the first study presenting a FlexiForce respiration sensor that includes all system elements in a single compact casing. The source files with the design of the casing have been published as supplementary material to be reused by any interested researcher. The sensing system was tested with twenty-one subjects for different breathing rates. Two different algorithms were developed to obtain the respiratory rate from the voltage signals recorded by the sensor. Statistical tests were performed to determine the optimal computation time window and algorithm. This approach is also novel in this field. Low error values were obtained for a time window of 27¿s with an algorithm based on the calculation of time between zero-crossings (4.02%) and with an algorithm based on counting them (3.40%). To promote research transparency and reusability, the dataset with the recorded data and the source code of the algorithms and statistical tests have also been published. Therefore, an open, replicable, low-error, wearable, wireless, and compact sensing system to measure respiratory rate was developed and tested

Mimicking human player strategies in fighting games using game artificial intelligence techniques

Fighting videogames (also known as fighting games) are ever growing in popularity and accessibility. The isolated console experiences of 20th century gaming has been replaced by online gaming services that allow gamers to play from almost anywhere in the world with one another. This gives rise to competitive gaming on a global scale enabling them to experience fresh play styles and challenges by playing someone new. Fighting games can typically be played either as a single player experience, or against another human player, whether it is via a network or a traditional multiplayer experience. However, there are two issues with these approaches. First, the single player offering in many fighting games is regarded as being simplistic in design, making the moves by the computer predictable. Secondly, while playing against other human players can be more varied and challenging, this may not always be achievable due to the logistics involved in setting up such a bout. Game Artificial Intelligence could provide a solution to both of these issues, allowing a human player s strategy to be learned and then mimicked by the AI fighter. In this thesis, game AI techniques have been researched to provide a means of mimicking human player strategies in strategic fighting games with multiple parameters. Various techniques and their current usages are surveyed, informing the design of two separate solutions to this problem. The first solution relies solely on leveraging k nearest neighbour classification to identify which move should be executed based on the in-game parameters, resulting in decisions being made at the operational level and being fed from the bottom-up to the strategic level. The second solution utilises a number of existing Artificial Intelligence techniques, including data driven finite state machines, hierarchical clustering and k nearest neighbour classification, in an architecture that makes decisions at the strategic level and feeds them from the top-down to the operational level, resulting in the execution of moves. This design is underpinned by a novel algorithm to aid the mimicking process, which is used to identify patterns and strategies within data collated during bouts between two human players. Both solutions are evaluated quantitatively and qualitatively. A conclusion summarising the findings, as well as future work, is provided. The conclusions highlight the fact that both solutions are proficient in mimicking human strategies, but each has its own strengths depending on the type of strategy played out by the human. More structured, methodical strategies are better mimicked by the data driven finite state machine hybrid architecture, whereas the k nearest neighbour approach is better suited to tactical approaches, or even random button bashing that does not always conform to a pre-defined strategy

Sensing Systems for Respiration Monitoring: A Technical Systematic Review

Respiratory monitoring is essential in sleep studies, sport training, patient monitoring, or health at work, among other applications. This paper presents a comprehensive systematic review of respiration sensing systems. After several systematic searches in scientific repositories, the 198 most relevant papers in this field were analyzed in detail. Different items were examined: sensing technique and sensor, respiration parameter, sensor location and size, general system setup, communication protocol, processing station, energy autonomy and power consumption, sensor validation, processing algorithm, performance evaluation, and analysis software. As a result, several trends and the remaining research challenges of respiration sensors were identified. Long-term evaluations and usability tests should be performed. Researchers designed custom experiments to validate the sensing systems, making it difficult to compare results. Therefore, another challenge is to have a common validation framework to fairly compare sensor performance. The implementation of energy-saving strategies, the incorporation of energy harvesting techniques, the calculation of volume parameters of breathing, or the effective integration of respiration sensors into clothing are other remaining research efforts. Addressing these and other challenges outlined in the paper is a required step to obtain a feasible, robust, affordable, and unobtrusive respiration sensing system

Data- and Value-Driven Software Engineering with Deep Customer Insight : Proceedings of the Seminar No. 58314308

There is a need in many software-based companies to evolve their software development practices towards continuous integration and continuous deployment. This allows a company to frequently and rapidly integrate and deploy their work and in consequence also opens opportunities for getting feedback from customers on a regular basis. Ideally, this feedback is used to support design decisions early in the development process, e.g., to determine which features should be maintained over time and which features should be skipped. In more general terms, the entire R&D system of an organization should be in a state where it is able to respond and act quickly based in instant customer feedback and where actual deployment of software functionality is seen as a way of fast experimenting and testing what the customer needs. Experimentation refers here to fast validation of a business model or more specifically validating a value hypothesis. Reaching such a state of continuous experimentation implies a lot of challenges for organizations. Selected challenges are how to develop the "right" software while developing software "right", how to have an appropriate tool infrastructure in place, how to measure and evaluate customer value, what are appropriate feedback systems, how to improve the velocity of software development, how to increase the business hit rate with new products and features, how to integrate such experiments into the development process, how to link knowledge about value for users or customers to higher-level goals of an organization. These challenges are quite new for many software-based organizations and not sufficiently understood from a software engineering perspective. These proceedings contain selected seminar papers of the student seminar Data- and Value-Driven Software Engineering with Deep Customer Insight that was held at the Department of Computer Science of the University of Helsinki. The seminar was held during the fall semester of 2014 from September 1st to December 8th. Papers in the seminar cover a wide range of topics related to the creation of value in software engineering. An interview of startups shows that emerging companies face a number of key decision points that shape their future. Value has a different meaning in different contexts. Embedded devices can be used to gather data and provide more value to the users through analysis and adaptation to circumstances. In entertainment, metrics can provide content creators the chance to react to user behavior and provide a more meaningful user experience. Value creation needs an active approach to software development from the companies: software engineering processes need to be incorporated with proper mechanisms to find the correct stakeholders, elicit requirements that provide the highest value and successfully implement the necessary changes with short development cycles. When the right building blocks are in place, companies are able to quickly deliver new software and leverage data from their products and services to continuously improve the perceived value of software

KEER2022

Avanttítol: KEER2022. DiversitiesDescripció del recurs: 25 juliol 202

Contribución al diseño de sensores vestibles y ambientales para medir la respiración y el salto vertical en adultos mayores y frágiles.

Con el avance de la tecnología, se ha popularizado entre la población el uso de dispositivos para medir su estado de salud. Para lograr esto, se suelen utilizar dispositivos vestibles como los smartwatch y smartbands, dispositivos ambientales embebidos en los alrededores, e incluso dispositivos conectados a aplicaciones móviles. El uso de estas tecnologías también se ha popularizado entre los profesionales de la salud.Esta tesis se centra en el desarrollo de dispositivos para monitorizar la salud de adultos mayores y adultos frágiles. Se desarrollaron dos líneas de trabajo: en la primera se diseñó e implementó un sistema vestible para monitorizar en tiempo real la respiración de los usuarios; en la segunda se desarrolló un sistema ambiental capaz de medir la altura del salto vertical efectuado por los usuarios sobre él.Sistema vestible para monitorizar la respiración:- Dentro de esta línea de trabajo se investigó un nuevo sensor de respiración que venía a cubrir algunas lagunas existentes en el estado de la técnica: la integración de todos los elementos electrónicos del sistema en un encapsulado compacto, la liberación del diseño para su reutilización y mejora por parte de otros investigadores y el bajo coste de los elementos que componen el sistema, entre otros. El sistema vestible consiste en un dispositivo que se coloca alrededor del pecho mediante una cinta ajustable. Este sistema funciona mediante un sensor piezoresistivo que detecta las variaciones en el diámetro del pecho ocasionadas al inhalar y exhalar; las variaciones detectadas son enviadas de forma inalámbrica mediante Bluetooth a una estación de visualización elegida por el usuario (PC, Tablet o Smartphone). El sistema se encuentra embebido en un armazón impreso en 3D. Para validar el funcionamiento de este sistema, se realizaron pruebas con 21 voluntarios que efectuaron diferentes ritmos de respiración. Para obtener los ritmos respiratorios de cada señal generada, se utilizaron dos algoritmos. Estos algoritmos calculan el ritmo respiratorio al segmentar la señal original en ventanas de tiempo desde 6 hasta 30 segundos. Los resultados obtenidos muestran que, con una ventana de tiempo de 27 segundos, se obtiene el menor error para cada algoritmo (4,02% y 3,40 %).Sistema ambiental para medir el salto vertical:- Dentro de esta segunda línea de trabajo se investigó en un novedoso sistema ambiental para medir la altura del salto, lo que supuso una innovación respecto a los sensores utilizados actualmente para este fin. El sistema ambiental consiste en una plataforma que detecta objetos sobre ella mediante la presión, y mide el tiempo transcurrido desde que un objeto se retira y se coloca de nuevo. El sistema detecta los objetos mediante una matriz de sensores piezoresitivos (Force Sensitive Resistors - FSR realizados con velostat). Las dimensiones de la plataforma son 30 cm x 30 cm, área sobre la cual se distribuyen un total de 256 sensores FSR. El salto vertical se calcula mediante la fórmula de tiempo de vuelo, y el resultado es enviado mediante Bluetooth a un PC o Smartphone. Se realizaron dos experimentos: en el primero participaron un total de 38 voluntarios, con el objetivo de validar el funcionamiento del sistema con una cámara de alta velocidad como referencia (120 fps); en el segundo experimento se capturaron los datos en crudo de 15 voluntarios, con estos datos se emularon 10 frecuencias de muestreo (desde 20 Hz hasta 200 Hz) y se analizaron los efectos de utilizar frecuencias más bajas. Del primer experimento se obtuvo un error relativo medio de 1.98% con un coeficiente de determinación r2= 0,996. Del segundo experimento se determinó que las frecuencias de muestreo de 200 Hz y 100 Hz muestran un desempeño similar al mantener un error relativo por debajo del 5% en el 95% de las mediciones.Finalmente, este trabajo de tesis concluye indicando las principales aportaciones realizadas para cada una de las dos líneas de trabajo, así como el trabajo futuro que podría desarrollarse en cada una de ellas.<br /