An Early Drowning Detection System for Internet of Things (IoT) Applications

Drowning is the leading cause of injury or death for children and teenagers. Designing a drowning detection device by implementing an Internet of Thing (IoT) is needed. An Early Drowning Detection System (EDDS) is a system that gives an early alarm to the guardians (parents and lifeguard) if the detector triggered an abnormal heartbeat and the victims are submerged under the water for a long time. A microcontroller was used to control the signal received from a pulse sensor and time for the signal lost under the water before it is transmitted to the access point. The access point acts as a data forwarding to the database via an internet connection. Universal Asynchronous Receiver/Transmitter (UART) 433MHz radio frequency transceiver has been used to create the wireless communication between drowning detection device and monitoring hub. A triggered warning signal will be transmitted to the guardians via Android apps and web page

Trypophobia: Heart rate, heart rate variability and cortical haemodynamic response

Background: Trypophobia is a common condition in which sufferers are averse to images of small holes arranged in clusters. Methods: We used photo-plethysmography to examine cardiovascular correlates and near infrared spectroscopy to examine cortical correlates of the phenomenon in order to validate the Trypophobia Questionnaire and explore the several interlinked explanations of the disorder. Results: Trypophobic images were found to increase heart rate and heart rate variability, but only in individuals with high scores on the Trypophobia Questionnaire. Trypophobic images were also found to elicit larger haemodynamic responses in posterior cortical areas, but again only in individuals with high scores. Limitations: The results are consistent with a contribution from both parasympathetic and sympathetic systems. Conclusion: The data demonstrate the validity of the Trypophobia Questionnaire and show an involvement not only ofthe autonomic system but cortical mechanisms including cortical hyperexcitability

Android Application to Detect and Alert Tachycardia and Bradycardia using Pulse Rate Sensor

Heart rate monitoring is most vital in preventing disorders related to heart. Failure to detect heart disorder in early stage may lead to death. The lacking of devices to immediately detect the abnormalities in heart and alert the patients emergency contact lead to this problem. In this report the author propose a system to detect two heart disorders called Tachycardia and Bradycardia which are caused by abnormalities in heart rate. The proposed system will consist of a pulse sensor which will be connected to a smartphone via Bluetooth. The signal information which is processed by the microcontroller will be sent to the mobile phone. An app created will send an alert to the emergency contacts of the patients when Tachycardia or Bradycardia condition has been detected by the sensor. This will increase the possibilities of giving immediate treatment to the patient, and hope to reduce the death rate caused by heart disorder

Android Application to Detect and Alert Tachycardia and Bradycardia using Pulse Rate Sensor

Heart rate monitoring is most vital in preventing disorders related to heart. Failure to detect heart disorder in early stage may lead to death. The lacking of devices to immediately detect the abnormalities in heart and alert the patients emergency contact lead to this problem. In this report the author propose a system to detect two heart disorders called Tachycardia and Bradycardia which are caused by abnormalities in heart rate. The proposed system will consist of a pulse sensor which will be connected to a smartphone via Bluetooth. The signal information which is processed by the microcontroller will be sent to the mobile phone. An app created will send an alert to the emergency contacts of the patients when Tachycardia or Bradycardia condition has been detected by the sensor. This will increase the possibilities of giving immediate treatment to the patient, and hope to reduce the death rate caused by heart disorder

Desarrollo de un filtro digital para señales foto pletismográficas obtenidas de una tarjeta de adquisición de datos en un entorno de laboratorio

En la presente investigación se hizo un estudio de diversos filtros digitales que puedan cumplir con la tarea de filtrar, en tiempo real, y usando una tarjeta de adquisición de datos (TAD), señales PPG obtenidas para calcular la hemoglobina en la sangre de una persona. Es por esto que, la tarea de filtrar estas señales fotopletismográficas (PPG), es crucial, ya que un mal filtrado puede terminar en un mal cálculo de hemoglobina. El primer paso fue estudiar el estado del arte alrededor del filtrado de señales PPG y así determinar cuáles pueden ser las opciones para hacer el filtrado. Posteriormente, se obtuvieron señales PPG sin filtrar de pacientes para su estudio, lo que permitió determinar los parámetros para los filtros elegidos. Luego de ello se determinaron las ecuaciones y los algoritmos para poder hacer la comparación necesaria para la determinación del filtro. Una vez determinadas las ecuaciones y algoritmos, se procedió a hacer su implementación en PyCharm, usando el lenguaje de programación Python, lo que permitió determinar los indicadores para la comparación de los filtros y la determinación del más eficiente, es decir, que optimice los recursos computacionales disponibles sin consumo excesivo. Una vez realizada la comparación, se determinó, según las necesidades del proyecto, cuál es el filtro que cumplía los requerimientos, lo que resultó en el filtro Butterworth de orden 6. Con la determinación del filtro, se procedió a desarrollarlo en lenguaje C para luego implementarse en el microcontrolador del proyecto, validando que el filtro, funciona según los requerimientos previamente establecidos.In the present investigation a study of many digital filters was made that may accomplish the task of filtering, in real time, and using a data acquisition board (DAQ), PPG signals obtained to calculate hemoglobin in a person’s blood. This is why, the task of filtering these PPG signals, is crucial, because, a bad filtering, may result in a bad hemoglobin calculation. The first step was studying the state of art surrounding photoplethysmographic signal (PPG) filtering, that way, determining which options may do the filtering task. After that, unfiltered PPG signals were obtained from patients, for its study, that way, the parameters needed, could be determined for the study of the chosen filters. After that, the equations and algorithms needed were determined for making the comparison for the filter determination. Once the equations and algorithms needed were determined, the implementation in PyCharm was done, using Python programming language, which allowed us to determine the indicators for the filter’s comparison and the determination of the most efficient one, that it optimizes the available computational resources without excessive consumption. When the comparative table was done, it was determined that, following the project needs, the most adequate filter, turned to be order 6 Butterworth filter. With this result, it was developed the filter in C language so it could be implemented in the microprocessor of the project, validating that this filter, works according to the previously established requirements.Tesi

An exploration of trypophobia

Images comprising clusters of objects can induce aversion and certain symptoms of anxiety, fear and disgust (so-called “trypophobia”) in about 13% of the population. This thesis is an investigation of the stimulus and response characteristics of the condition. First, a symptom questionnaire (Trypophobia Questionnaire) was developed and validated based on reports of different categories of symptoms. The questionnaire demonstrated a single construct that predicted discomfort from trypophobic images, but not neutral or unpleasant images, and did not correlate with anxiety. Second, filtering images reduced the excess energy at mid-range spatial frequencies (previously associated with both trypophobic and uncomfortable images). Relative to unfiltered trypophobic images, the discomfort from filtered images experienced by observers with high TQ scores was less than that experienced with neutral images, and by observers with low TQ scores. Clusters of concave objects (holes) did not induce significantly more discomfort than clusters of convex objects (bumps), suggesting that trypophobia (previously referred to as “fear of holes”) involves clusters not of holes but of objects with particular spectral profile involving excess energy at mid-range spatial frequencies. These visual characteristics have been previously shown to induce discomfort and a strong cortical oxygenation. The same abnormal oxygenation occurred for trypophobic images, but only for individuals with high TQ scores. Three lines of evidence suggest that trypophobia is a response of disgust rather than fear: (1) trypophobia was associated with an aversion to spiders, and not snakes; (2) trypophobic stimuli did not produce a bias in the subjective estimation of stimulus duration but (3) increased the heart rate and its variability. Fear inducing stimuli generally give effects opposite to those listed as 2 and 3. In conclusion, trypophobia is a reaction of disgust to clusters of objects with particular spectral profile that may resemble contamination sources (e.g., skin lesions)

A business model framework for the Internet of Things

The Internet of Things (IoT) is an emerging technology with research interests transcending disciplines of computer sciences and computer engineering to agriculture, business management, civil engineering, architecture, medical sciences, social science etc. This is because of the potential expanding range of its application areas of wind mill operation and irrigation control, supply chain and logistics, manufacturing, home and office environment, healthcare, social care, etc. As it is usually the case with emerging technologies, IoT is faced with the challenge of bridging the gap between the technology development and corresponding business model design. Without a workable business model, the IoT paradigm may end up in research labs and subsequently fade away. A business model should show how lucrative it is to be in the IoT business by adding value to the customer and generating revenue for the business firm. This research is a contribution towards the goal of developing a business model for IoT, with customer/user value potential as the focal point. The comprehensive literature review carried out during this research (i) outlines the concept of business models; (ii) investigates through desk research, existing digital technology business models with focus on two (2) established digital technology firms and identified five generic components of their business models including but not limited to subscription, training, price, satisfaction, and trust, which were used for the primary investigation; (iii) investigates the IoT state-of-the-arts by elaborating on the IoT space and precursor technologies that are part of its ecosystem with the aim of describing, illustrating and developing application prototypes for three IoT scenarios of health monitoring, the use of the library and borrowing of books (a novel idea), and home environment; (iv) evaluates business model framework representation maps in current use, and specifically modified the general structure, content, and performance framework map to design an adoption framework map called a customer-focused business model framework map for IoT (CBMF4IoT). The unique approach to business model research involved conducting a user-led experiment to investigate the likelihood of IoT adoption of existing digital technology business models, as the customer value potential aspect of a business model design was the focal point of this research. Specifically, the experiment was aimed at determining if there was any significant differences in user inclinations towards the five generic components of existing digital technology business models based on smartphone context and IoT products context in a within-subjects design, with sample population drawn from University of Sussex community. The experimental design relied on participants' past experiences with smartphone for them to indicate their pre-purchase inclinations towards the five generics components. For the IoT products context, descriptions and diagrammatic illustration of the three IoT scenarios with their corresponding Just-in-Mind clickable prototypes served as educational tools to enable participants to be acquainted with IoT in order for them to indicate their potential pre-purchase inclinations towards the five generic components. A unique procedure for business model adoption likelihood was designed using the Sign test for high, low, and medium likelihood of adoption. The results of this test indicate medium likelihood of adoption for three of the generic components and low likelihood of adoption for two of the generic components. The results of this test was then fed to the CBMF4IoT. This thesis demonstrates that reusability of successful digital technology business models could potentially result in market success for an emerging digital technology in a B2C context, as users opinion formed the bases for the conclusions, instead of the conventional opinion gathering from only experts, business owners, and practitioners for a BM research