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ROBO M.D. and other subprojects implemented in Innovation 4 Welfare pro gram

ROBO M.D. and other subprojects implemented in Innovation 4 Welfare pro gram Dr. Petr Bartoš, Ph.D. University of South Bohemia IFA2012 Faculty of Pedagogy May 30th 2012 Department of Applied Physics and Technology Prague. Introduction.

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ROBO M.D. and other subprojects implemented in Innovation 4 Welfare pro gram

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  1. ROBO M.D. and other subprojects implemented in Innovation 4 Welfare program Dr. Petr Bartoš, Ph.D. University of South Bohemia IFA2012 Faculty of Pedagogy May 30th 2012 Department of Applied Physics and Technology Prague

  2. Introduction • Program Innovation 4 Welfare is financed by the European Union. • - 8 projects, duration 1.5 year: • FITHERHAB • FOBOS • HAS PASSPORT • MNEMOSYNE • MRH • PICKFIBER • ROBO M.D. • TIAM Video presentation

  3. ROBO M.D. • ROBO M.D. (Monitor & Detect) • monitor bio-signals • detect critical situations and possibly predict them, before they occur. • focusedon elderly persons living at home • Specifications/requirements on the system: • to developlow-cost equipment • system based on modular structure • wireless communication of all the components • easy to use • non-invasive system

  4. Participants University of Tartu University of Applied Sciences University of South Bohemia Johannes Kepler University Italian National Research Council

  5. System architecture Software  data processing  decision Medical service, nurse, guardian, …

  6. Signals and detection • What we would like to monitor • ECG • EEG • Skin Temperature • Acceleration • Blood Pressure (continuously) • Respiration • O2 Saturation • Glucose concentration • What we can monitor easily • ECG (single lead) • Skin Temperature • Acceleration cost: 1.000 £

  7. Signals and detection Software running on a PC Data processing Decision / Alert

  8. Signals and detection • What we would like to detect (predict) • Heart attack • Stroke • a fall • Apnea • Hyper-, Hypotension • Hyper-, Hypoglycemia • … • To be able to detect one special case, we need the right information from the user (monitor signals) • The combination of some signals might give additional information  Cross analysis, 1 + 1 ≠ 2

  9. Questionaire, robot • Daily questions were created • „Would you like to answer some questions today?“no answer: -- repeat questionno: -- do not ask anything more yes: start to ask…e.g., • „Are you feeling ok today?“ • … • Questions in the case of an alert were created • Example: Algorithm detects a fall • “Did you fall down?“ • no answer: confirm the alarm • no: wrong detection by the algorithm • yes: confirm the alarm • “Do you need help?” • yes: organize help (out of scope of this project) • no: -- • no answer: organize help Video: fall simulation

  10. Thank you for your attention! bartos-petr@seznam.cz

  11. Problems to solve... • Limited range of the wireless connections (Bluetooth – 10m) • No connection through walls, i.e. the PC has to be located in the same room as the patient • Quality of the recorded signals is partially bad • The electrode of the ECG sensor has to be replaced every day • The robot can only operate in a room without obstacles

  12. Project idea • Target group: elderly people, living (alone) at home or almost autonomous in home for old people • Automatic detection of critical situations (e.g., a fall) as well as automatic initialization of rescue procedure, if needed • Use of measurement devices which do not increase the burden of the patient • Use of rather cheap equipment, wireless devices, simplest possible interaction with the user • Collection of sensor data to predict critical situations (e.g., general dangerous long-term variation in the heart activity) • If required, forward the data to a professional (medical doctor) for analysis • development until series-production readiness (we are far from it!) • Connections of the system with medical personnel, or any other external organizations No goals of the project

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