BEGIN:VCALENDAR VERSION:2.0 PRODID:IEEE vTools.Events//EN CALSCALE:GREGORIAN BEGIN:VTIMEZONE TZID:Europe/Zurich BEGIN:DAYLIGHT DTSTART:20230326T030000 TZOFFSETFROM:+0100 TZOFFSETTO:+0200 RRULE:FREQ=YEARLY;BYDAY=-1SU;BYMONTH=3 TZNAME:CEST END:DAYLIGHT BEGIN:STANDARD DTSTART:20231029T020000 TZOFFSETFROM:+0200 TZOFFSETTO:+0100 RRULE:FREQ=YEARLY;BYDAY=-1SU;BYMONTH=10 TZNAME:CET END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTAMP:20230429T003403Z UID:E21A728A-ABEB-40BA-B2EA-19C92ED95053 DTSTART;TZID=Europe/Zurich:20230427T170000 DTEND;TZID=Europe/Zurich:20230427T180000 DESCRIPTION:11:00am New Jersey Time 17:00 Geneva Time\n\nProfessor Dr Katar zyna Wac Distinguished Speaker IEEE Computer Society with PACE SIGHT Group and Women in Engineering\n\nBiosensors for Telemonitoring of the Patients \n\nThe availability of miniaturized\, wearable\, personalized sensors and powerful mobile phones (smartphones) enable the development of a magnitud e of services for ubiquitous monitoring of behavioral markers of individua ls in daily life environments\, i.e.\, outside strict clinical settings. A behavioral marker is defined as a specific behavior in any of the three d omains—physical\, psychological or social\, leveraged to indicate/measur e the change in individual’s condition (e.g.\, for a purpose of diagnosi s)\, the effects of preventive\, treatment or rehabilitation activities\, or a progress of disease.\n\nThe technologies for behavioral marker assess ment are ready—hardware and software technologies are available at affor dable prices and research on advanced algorithms for state assessment is o ngoing. In this presentation\, we give an example of ubiquitous technologi es for the ambulatory assessment of an individual’s behavioral markers r elated to his/her\n\n- physical state (heart rate\, body temperature\, blo od pressure\, respiration\, etc.)\, physical activity\, medication intake\ , fatigue and pain\, sleep quality\n- psychological state in terms of mood s\, feelings\, memory and concentration\,\n- social state in terms of rela tionships and social interactions\, including social relationships with fe llow patients suffering from the same disease.\n\nWe will also give an exa mple of environmental state assessment technologies for noise\, pollution\ , or transportation usage\, influencing the individual’s state and behav iors in all three above-mentioned domains. We discuss these technologies i n terms of their design space and provided features\, and their strengths and barriers for user adoption and scaling.\n\nThe challenge lies in the m ethodological aspects of the approach\, where the data collected in the in dividual’s daily life environments must be of a particular quality to in form the clinical decisions taken. The questions are raised about where\, when and what to measure\, how to make sense of data\, how to extract and fuse relevant features\, how to use the data in individual cases (“perso nalized analytics”)\, what to consider as constituting the evidence on e ffectiveness of a given treatment or rehabilitation activity\, and how to link that to clinical outcomes for a given patient.\n\nCo-sponsored by: Co mputer Chapter\, PACE SIGHT\, WIE\n\nSpeaker(s): Professor Dr Katarzyna Wa c\, \n\nAgenda: \nIntroductions\n\nPresentation\n\nQuestions and Discussio n\n\nVirtual: https://events.vtools.ieee.org/m/349801 LOCATION:Virtual: https://events.vtools.ieee.org/m/349801 ORGANIZER:kit.august@gmail.com SEQUENCE:5 SUMMARY:Professor Dr Katarzyna Wac Distinguished Speaker Biosensors for Tel emonitoring of the Patients URL;VALUE=URI:https://events.vtools.ieee.org/m/349801 X-ALT-DESC:Description: <br /><h4>11:00am New Jersey Time 17:00 Geneva Time </h4>\n<h4>Professor Dr Katarzyna Wac Distinguished Speaker IEEE Computer Society with PACE SIGHT Group and Women in Engineering</h4>\n<h4>Biosensor s for Telemonitoring of the Patients</h4>\n<p>The availability of miniatur ized\, wearable\, personalized sensors and powerful mobile phones (smartph ones) enable the development of a magnitude of services for ubiquitous mon itoring of behavioral markers of individuals in daily life environments\, i.e.\, outside strict clinical settings. A behavioral marker is defined as a specific behavior in any of the three domains&mdash\;physical\, psychol ogical or social\, leveraged to indicate/measure the change in individual& rsquo\;s condition (e.g.\, for a purpose of diagnosis)\, the effects of pr eventive\, treatment or rehabilitation activities\, or a progress of disea se.</p>\n<p>The technologies for behavioral marker assessment are ready&md ash\;hardware and software technologies are available at affordable prices and research on advanced algorithms for state assessment is ongoing. In t his presentation\, we give an example of ubiquitous technologies for the a mbulatory assessment of an individual&rsquo\;s behavioral markers related to his/her</p>\n<ul>\n<li>physical state (heart rate\, body temperature\, blood pressure\, respiration\, etc.)\, physical activity\, medication inta ke\, fatigue and pain\, sleep quality</li>\n<li>psychological state in ter ms of moods\, feelings\, memory and concentration\,</li>\n<li>social state in terms of relationships and social interactions\, including social rela tionships with fellow patients suffering from the same disease.</li>\n</ul >\n<p>&nbsp\;</p>\n<p>We will also give an example of environmental state assessment technologies for noise\, pollution\, or transportation usage\, influencing the individual&rsquo\;s state and behaviors in all three above -mentioned domains. We discuss these technologies in terms of their design space and provided features\, and their strengths and barriers for user a doption and scaling.</p>\n<p>The challenge lies in the methodological aspe cts of the approach\, where the data collected in the individual&rsquo\;s daily life environments must be of a particular quality to inform the clin ical decisions taken. The questions are raised about where\, when and what to measure\, how to make sense of data\, how to extract and fuse relevant features\, how to use the data in individual cases (&ldquo\;personalized analytics&rdquo\;)\, what to consider as constituting the evidence on effe ctiveness of a given treatment or rehabilitation activity\, and how to lin k that to clinical outcomes for a given patient.</p><br /><br />Agenda: <b r /><p>Introductions</p>\n<p>Presentation</p>\n<p>Questions and Discussion </p> END:VEVENT END:VCALENDAR