Anonimity in Health-oriented Social Networks

AbstractWeb 2.0 philosophy of content creation has spread to many domains including healthcare. A new trend in social networks is to serve specialized, niche-oriented participants, with unique interests. We study what are the advantages, disadvantages and concerns when deploying a social network in the health domain; to be used for sharing information about treatment outcomes and conditions. Our paper raises the privacy concern, namely anonymization, when different stakeholders use such a platform

AUTOMATIC RECOGNITION OF DENTAL PATHOLOGIES AS PART OF A CLINICAL DECISION SUPPORT PLATFORM

The current work is done within the context of Romanian National Program II (PNII) research project "Application for Using Image Data Mining and 3D Modeling in Dental Screening" (AIMMS). The AIMMS project aims to design a program that can detect anatomical information and possible pathological formations from a collection of digital imaging and communications in medicine (DICOM) images. The main function of the AIMMS platform is to provide the user with the opportunity to use an integrated dental support platform, using image processing techniques and 3D modeling. From the literature review, it can be found that for the detection and classification of teeth and dental pathologies existing studies are in their infancy. Therefore, the work reported in this article makes a scientific contribution in this field. In this article it is presented the relevant literature review and algorithms that were created for detection of dental pathologies in the context of research project AIMMS

i-Light - Intelligent Luminaire Based Platform for Home Monitoring and Assisted Living

[EN] We present i-Light, a cyber-physical platform that aims to help older adults to live safely within their own homes. The system is the result of an international research project funded by the European Union and is comprised of a custom developed wireless sensor network together with software services that provide continuous monitoring, reporting and real-time alerting capabilities. The principal innovation proposed within the project regards implementation of the hardware components in the form of intelligent luminaires with inbuilt sensing and communication capabilities. Custom luminaires provide indoor localisation and environment sensing, are cost-effective and are designed to replace the lighting infrastructure of the deployment location without prior mapping or fingerprinting. We evaluate the system within a home and show that it achieves localisation accuracy sufficient for room-level detection. We present the communication infrastructure, and detail how the software services can be configured and used for visualisation, reporting and real-time alerting.This work was funded by a grant of the Romanian National Authority for Scientific Research and Innovation, CCCDI-UEFISCDI, project number 46E/2015, i-Light-A pervasive home monitoring system based on intelligent luminaires.Marin, I.; Vasilateanu, A.; Molnar, A.; Bocicor, MI.; Cuesta Frau, D.; Molina Picó, A.; Goga, N. (2018). i-Light - Intelligent Luminaire Based Platform for Home Monitoring and Assisted Living. Electronics. 7(10):1-24. https://doi.org/10.3390/electronics7100220S124710World Report on Ageing and Health http://apps.who.int/iris/bitstream/10665/186463/1/9789240694811_eng.pdf?ua=1ECP Makes Switching to eMAR Easy http://extendedcarepro.com/products/Carevium Assisted Living Software http://www.carevium.com/carevium-assisted-living-software/Yardi EHR http://www.yardi.com/products/ehr-senior-care/Yardi eMAR http://www.yardi.com/products/emar/Botia, J. A., Villa, A., & Palma, J. (2012). Ambient Assisted Living system for in-home monitoring of healthy independent elders. Expert Systems with Applications, 39(9), 8136-8148. doi:10.1016/j.eswa.2012.01.153Lopez-Guede, J. M., Moreno-Fernandez-de-Leceta, A., Martinez-Garcia, A., & Graña, M. (2015). Lynx: Automatic Elderly Behavior Prediction in Home Telecare. BioMed Research International, 2015, 1-18. doi:10.1155/2015/201939Luca, S., Karsmakers, P., Cuppens, K., Croonenborghs, T., Van de Vel, A., Ceulemans, B., … Vanrumste, B. (2014). Detecting rare events using extreme value statistics applied to epileptic convulsions in children. Artificial Intelligence in Medicine, 60(2), 89-96. doi:10.1016/j.artmed.2013.11.007Better Health Assessments Every Day, for Better Everyday Living http://healthsense.com/Home Telehealth https://www.usa.philips.com/healthcare/solutions/enterprise-telehealth/home-telehealthThe Carelink Network http://www.medtronic.com/us-en/healthcare-professionals/products/cardiac-rhythm/managing-patients/information-systems/carelink-network.htmlHaigh, P. A., Bausi, F., Ghassemlooy, Z., Papakonstantinou, I., Le Minh, H., Fléchon, C., & Cacialli, F. (2014). Visible light communications: real time 10 Mb/s link with a low bandwidth polymer light-emitting diode. Optics Express, 22(3), 2830. doi:10.1364/oe.22.002830Indoor Positioning System http://www.gelighting.com/LightingWeb/na/solutions/control-systems/indoor-positioning-system.jspIndoor and Outdoor Lighting Solutions http://www.acuitybrands.com/solutions/featured-spacesHuang, C.-N., & Chan, C.-T. (2011). ZigBee-based indoor location system by k-nearest neighbor algorithm with weighted RSSI. Procedia Computer Science, 5, 58-65. doi:10.1016/j.procs.2011.07.010Charlon, Y., Fourty, N., & Campo, E. (2013). A Telemetry System Embedded in Clothes for Indoor Localization and Elderly Health Monitoring. Sensors, 13(9), 11728-11749. doi:10.3390/s130911728Patient/Elderly Activity Monitoring Using WiFi-Based Indoor Localization https://wiki.cc.gatech.edu/designcomp/images/3/3d/HHH_Report.pdfReal Time Location System http://zonith.com/products/rtls/Accurate Positioning https://www.pozyx.io/yooBee System Overview https://www.blooloc.com/over-yoobeeThe Top Indoor Location Engine for Smart Apps https://senion.com/Locating People, Way-Finding, and Attendance Tracking https://estimote.com/products/Indoor Navigation, Indoor Positioning, Indoor Analytics and Indoor Tracking https://www.infsoft.com/Lighting Reimagined https://www.lifx.com/Tabu. Lumen. Simply Brighter http://www.lumenbulb.net/Philips Hue http://www2.meethue.com/en-usElgato Avea https://www.elgato.com/en/aveaiLumi—The World’s Most Intelligent Light Bulbs hhttps://www.indiegogo.com/projects/ilumi-the-world-s-most-intelligent-light-bulbs--5#/Bluegiga BLE112 Bluetooth® Smart Module http://www.silabs.com/products/wireless/bluetooth/bluetooth-low-energy-modules/ble112-bluetooth-smart-moduleISO/IEEE 11073 https://www.iso.org/standard/67821.htmlDescription https://www.diodes.com/assets/Datasheets/ZXLD1366.pdfDigital Humidity Sensor SHT2x https://www.sensirion.com/en/environmental-sensors/humidity-sensors/humidity-temperature-sensor-sht2x-digital-i2c-accurate/Photo IC Type High Sensitive Light Sensor https://industrial.panasonic.com/cdbs/www-data/pdf/ADD8000/ADD8000CE2.pdfWSP2110 VOC Gas Sensor http://www.winsen-sensor.com/products/flat-surfaced-gas-sensor/wsp2110.htmlLow Power-Consumption CO2 Sensor http://www.winsen-sensor.com/d/files/PDF/Solid%20Electrolyte%20CO2%20Sensor/MG812%20CO2%20Manual%20V1.1.pdfGP2Y1010AU0F Compact Optical Dust Sensor http://www.sharp-world.com/products/device/lineup/data/pdf/datasheet/gp2y1010au_e.pdfEKMC (VZ) Series http://www3.panasonic.biz/ac/e/control/sensor/human/vz/index.jspSensors for Automotive & Industrial Applications: Grid-EYE Infrared Array Sensor https://na.industrial.panasonic.com/products/sensors/sensors-automotive-industrial-applications/grid-eye-infrared-array-sensorGeneric Attributes https://www.bluetooth.com/specifications/gattDeveloping NFC Applications. (2011). Near Field Communication, 151-239. doi:10.1002/9781119965794.ch5Matsuoka, H., Wang, J., Jing, L., Zhou, Y., Wu, Y., & Cheng, Z. (2014). Development of a control system for home appliances based on BLE technique. 2014 IEEE International Symposium on Independent Computing (ISIC). doi:10.1109/indcomp.2014.7011751Standard ECMA-404. The JSON Data Interchange Format http://www.ecma-international.org/publications/files/ECMA-ST/ECMA-404.pdfThe EU General Data Protection Regulation http://www.eugdpr.org/Tews, E., & Beck, M. (2009). Practical attacks against WEP and WPA. Proceedings of the second ACM conference on Wireless network security - WiSec ’09. doi:10.1145/1514274.1514286Farooq, U., & Aslam, M. F. (2017). Comparative analysis of different AES implementation techniques for efficient resource usage and better performance of an FPGA. Journal of King Saud University - Computer and Information Sciences, 29(3), 295-302. doi:10.1016/j.jksuci.2016.01.004Luo, X.-L., Liao, L.-Z., & Wah Tam, H. (2007). Convergence analysis of the Levenberg–Marquardt method. Optimization Methods and Software, 22(4), 659-678. doi:10.1080/10556780601079233Wammu https://wammu.eu/gammu

Model checking the properties of ISO/IEEE 11073-20601: 2016 standard-based communication protocol for personal health device

Engineering of medical informatics systems is a complex work because it is at the intersection of several critical domains, among which medicine, computer science, electrical engineering to mention just a few. One critical aspect of such systems is the interoperability of the different components. One key solution for the interoperability is the creation of good standards that will assure the interchange of data between products of several vendors and domains - medical devices, medical information systems, medical data, etc. In this paper a formal analysis of the ISO/IEEE 11073 -20601: 2016 Draft Standard for Health informatics - Personal health device communication - Application profile - Optimized exchange protocol is described. This family of standards specifies the communication between devices that can be agents (weighing scales, spirometers) which measure health related data and managers (laptop, smartphone etc.) that collect the information and can display or forward it. First the protocol was modeled in Promela and then the model was checked manually and also using the Spin tool that performed an automated check. The results revealed issues which can cause deadlocks. However, these issues appeared in exceptional workflows, the normal flow being designed well. This highlights the methodology of developing such protocols: concentration on normal, intended behaviors without dealing with exceptional behaviors. Using formal models can reveal problems with exceptional behaviors. The results and proposed solutions were reported to the IEEE 1073 working group and will be integrated in the standard

AUTOMATIC RECOGNITION OF DENTAL PATHOLOGIES AS PART OF A CLINICAL DECISION SUPPORT PLATFORM

The current work is done within the context of Romanian National Program II (PNII) research project "Application for Using Image Data Mining and 3D Modeling in Dental Screening" (AIMMS). The AIMMS project aims to design a program that can detect anatomical information and possible pathological formations from a collection of digital imaging and communications in medicine (DICOM) images. The main function of the AIMMS platform is to provide the user with the opportunity to use an integrated dental support platform, using image processing techniques and 3D modeling. From the literature review, it can be found that for the detection and classification of teeth and dental pathologies existing studies are in their infancy. Therefore, the work reported in this article makes a scientific contribution in this field. In this article it is presented the relevant literature review and algorithms that were created for detection of dental pathologies in the context of research project AIMMS

Ontologies applied in medicine: A digital library creation framework for health literacy

International audienceThe objective of this work is to extend the existing work for raising the medical literacy of empowered patients by creating a digital library that contains relevant articles from different medical domain. It should be noted that a large number of persons are interested in finding relevant information about their condition. We have chosen to discuss in this research the automated generation of ontologies for the medical domain. By the use of ontologies that gives key terms from a domain, the creation of the digital library can be done by crawling from the Internet articles which are related to the profile of the user and that are based on the key terms of the ontologies