282 research outputs found

    Android based teleoperation for the finch robot

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    The act of creating a robot involves systems engineering and creative problem solutions. It is about using established components to create a system that works in the natural or at least in the human environment. The current project is no exception, we have used the Robot Operating System (ROS) to create an android based teleoperator application for the Finch robot. A Raspberry Pi processing platform establishes the link between the android device and the Finch robot. The most creative task, during the system design, was to translate the commands from the teleoperator application into wheel movements of the Finch robot. The translation must take into account the physical setup of the robot, including unintended negative influences, such as drag. The command translation involved a nonlinear coordinate transformation. The ROS framework enabled us to focus on that nonstandard coordinate translation task by offering a high level of abstraction and the ability to create component functionalities independently

    A Review of Atrial Fibrillation Detection Methods as a Service

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    Atrial Fibrillation (AF) is a common heart arrhythmia that often goes undetected, and even if it is detected, managing the condition may be challenging. In this paper, we review how the RR interval and Electrocardiogram (ECG) signals, incorporated into a monitoring system, can be useful to track AF events. Were such an automated system to be implemented, it could be used to help manage AF and thereby reduce patient morbidity and mortality. The main impetus behind the idea of developing a service is that a greater data volume analyzed can lead to better patient outcomes. Based on the literature review, which we present herein, we introduce the methods that can be used to detect AF efficiently and automatically via the RR interval and ECG signals. A cardiovascular disease monitoring service that incorporates one or multiple of these detection methods could extend event observation to all times, and could therefore become useful to establish any AF occurrence. The development of an automated and efficient method that monitors AF in real time would likely become a key component for meeting public health goals regarding the reduction of fatalities caused by the disease. Yet, at present, significant technological and regulatory obstacles remain, which prevent the development of any proposed system. Establishment of the scientific foundation for monitoring is important to provide effective service to patients and healthcare professionals

    Computer aided diagnosis for cardiovascular diseases based on ECG signals : a survey

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    The interpretation of Electroencephalography (ECG) signals is difficult, because even subtle changes in the waveform can indicate a serious heart disease. Furthermore, these waveform changes might not be present all the time. As a consequence, it takes years of training for a medical practitioner to become an expert in ECG-based cardiovascular disease diagnosis. That training is a major investment in a specific skill. Even with expert ability, the signal interpretation takes time. In addition, human interpretation of ECG signals causes interoperator and intraoperator variability. ECG-based Computer-Aided Diagnosis (CAD) holds the promise of improving the diagnosis accuracy and reducing the cost. The same ECG signal will result in the same diagnosis support regardless of time and place. This paper introduces both the techniques used to realize the CAD functionality and the methods used to assess the established functionality. This survey aims to instill trust in CAD of cardiovascular diseases using ECG signals by introducing both a conceptional overview of the system and the necessary assessment method

    Uncovering design topics by visualizing and interpreting keyword data

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    This paper describes a bibliometric keyword analysis from the international DESIGN conference. We combined related keywords to form DESIGN topics. After that, we visualized the connections between the topics. Our analysis shows that the web of science database does not contain the DESIGN 2012-14 proceedings. That is relevant for the conference organizers, because content visibility is important. The topic visualization benefits both contributors to and organizers of the international DESIGN conference, because it shows trending topics and indicates areas with room for improvement

    Software defined antenna testing

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    Microstrip patch directional antennas are an attractive solution for modern wireless systems due to their high gain and directivity. Being an attractive solution creates the need to design such devices for various application scenarios. We have addressed that need by designing, simulating, and testing a rectangular microstrip patch directional antenna at 5GHz. Antenna patch and ground plane were designed with the well-known guided wavelength equation. The antenna performance, in terms of return loss at -10dB, gain, bandwidth, and the radiation pattern was analyzed with a simulation model. The proposed antenna achieved an impedance bandwidth of 77.8MHz (from 4.9662GHz to 5.0440GHz) and a gain of 6.26dBi at 5GHz. The antenna performance was verified with a software defined radio platform. We found that the software radio measurements confirmed the key simulation results. Furthermore, the extensive use of simulation enabled us to develop both antenna and digital baseband algorithms in parallel

    A review of automated sleep stage scoring based on physiological signals for the new millennia

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    Background and Objective: Sleep is an important part of our life. That importance is highlighted by the multitude of health problems which result from sleep disorders. Detecting these sleep disorders requires an accurate interpretation of physiological signals. Prerequisite for this interpretation is an understanding of the way in which sleep stage changes manifest themselves in the signal waveform. With that understanding it is possible to build automated sleep stage scoring systems. Apart from their practical relevance for automating sleep disorder diagnosis, these systems provide a good indication of the amount of sleep stage related information communicated by a specific physiological signal. Methods: This article provides a comprehensive review of automated sleep stage scoring systems, which were created since the year 2000. The systems were developed for Electrocardiogram (ECG), Electroencephalogram (EEG), Electrooculogram (EOG), and a combination of signals. Results: Our review shows that all of these signals contain information for sleep stage scoring. Conclusions: The result is important, because it allows us to shift our research focus away from information extraction methods to systemic improvements, such as patient comfort, redundancy, safety and cost

    A Smart Service Platform for Cost Efficient Cardiac Health Monitoring

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    Aim: In this study we have investigated the problem of cost effective wireless heart health monitoring from a service design perspective. Subject and Methods: There is a great medical and economic need to support the diagnosis of a wide range of debilitating and indeed fatal non-communicable diseases, like Cardiovascular Disease (CVD), Atrial Fibrillation (AF), diabetes, and sleep disorders. To address this need, we put forward the idea that the combination of Heart Rate (HR) measurements, Internet of Things (IoT), and advanced Artificial Intelligence (AI), forms a Heart Health Monitoring Service Platform (HHMSP). This service platform can be used for multi-disease monitoring, where a distinct service meets the needs of patients having a specific disease. The service functionality is realized by combining common and distinct modules. This forms the technological basis which facilitates a hybrid diagnosis process where machines and practitioners work cooperatively to improve outcomes for patients. Results: Human checks and balances on independent machine decisions maintain safety and reliability of the diagnosis. Cost efficiency comes from efficient signal processing and replacing manual analysis with AI based machine classification. To show the practicality of the proposed service platform, we have implemented an AF monitoring service. Conclusion: Having common modules allows us to harvest the economies of scale. That is an advantage, because the fixed cost for the infrastructure is shared among a large group of customers. Distinct modules define which AI models are used and how the communication with practitioners, caregivers and patients is handled. That makes the proposed HHMSP agile enough to address safety, reliability and functionality needs from healthcare providers

    Atrial fibrillation detection service validation tool

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    We developed a software tool to validate a deep learning algorithm for an atrial fibrillation detection service with heart rate data from a clinical study. The deep learning algorithm analyses the measurement data and establishes an estimated atrial fibrillation probability for each heartbeat. The software tool displays both data and deep learning analysis results. Furthermore, the graphical user interface can be used by medical experts to detect atrial fibrillation periods in the data and establish a reference result which will be treated as ground truth in subsequent result analysis steps. Once both deep learning and expert results are available, a confusion matrix is produced and the algorithm performance is validated by establishing accuracy, sensitivity, specificity, and f1-score. The software tool was created in Python and the software incorporated a graphical user interface as well as functional elements for data display and deep learning. To establish the required functionality, we used three different parallel processing methods for: (1) user interface processing, (2) data handling, and (3) deep learning. This highlights the need for parallel processing methods even for projects with a low or mid-range complexity. We have learned that the functionality of individual components can be expressed elegantly in Python. However, the lack of parallel debugging support makes it rather difficult to integrate functional components to establish a working solution
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