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PRODID:IEEE vTools.Events//EN
CALSCALE:GREGORIAN
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TZID:Australia/Brisbane
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DTSTART:19920301T020000
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TZOFFSETTO:+1000
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BEGIN:VEVENT
DTSTAMP:20260820T100530Z
UID:FD6E8343-488B-47D0-B4C0-FE1F72DC9DEC
DTSTART;TZID=Australia/Brisbane:20260820T150000
DTEND;TZID=Australia/Brisbane:20260820T160000
DESCRIPTION:Digital technologies are creating new opportunities to assess a
 nd monitor neurodegenerative disorders beyond traditional clinic-based vis
 its. This talk will explore how smartphones\, wearable sensors\, mobile ap
 plications\, and machine learning can be used to capture clinically releva
 nt information about symptoms in everyday environments.\n\nUsing Parkinson
 ’s disease as the main case study\, I will discuss examples of smartphon
 e-based assessments of tremor and finger dexterity\, the validation of sen
 sor-derived measures against clinical assessments and wearable devices\, a
 nd the use of machine learning to estimate symptom severity. The talk will
  also address an equally important question: whether these technologies ar
 e usable\, meaningful\, and acceptable to the people expected to use them.
 \n\nFinally\, I will discuss some of the opportunities and challenges invo
 lved in translating digital biomarkers and remote monitoring technologies 
 into clinically useful and patient-centred tools for neurodegenerative dis
 orders.\n\nSpeaker(s): Dr Gent Ymeri\, \n\nVirtual: https://events.vtools.
 ieee.org/m/572254
LOCATION:Virtual: https://events.vtools.ieee.org/m/572254
ORGANIZER:moid.sandhu@csiro.au
SEQUENCE:22
SUMMARY:Digital Technologies for Neurodegenerative Disorders: From Smartpho
 nes and Wearables to Digital Biomarkers
URL;VALUE=URI:https://events.vtools.ieee.org/m/572254
X-ALT-DESC:Description: <br /><div data-olk-copy-source="MessageBody">Digit
 al technologies are creating new opportunities to assess and monitor neuro
 degenerative disorders beyond traditional clinic-based visits. This talk w
 ill explore how smartphones\, wearable sensors\, mobile applications\, and
  machine learning can be used to capture clinically relevant information a
 bout symptoms in everyday environments.</div>\n<div>&nbsp\;</div>\n<div>Us
 ing Parkinson&rsquo\;s disease as the main case study\, I will discuss exa
 mples of smartphone-based assessments of tremor and finger dexterity\, the
  validation of sensor-derived measures against clinical assessments and we
 arable devices\, and the use of machine learning to estimate symptom sever
 ity. The talk will also address an equally important question: whether the
 se technologies are usable\, meaningful\, and acceptable to the people exp
 ected to use them.</div>\n<div>&nbsp\;</div>\n<div>Finally\, I will discus
 s some of the opportunities and challenges involved in translating digital
  biomarkers and remote monitoring technologies into clinically useful and 
 patient-centred tools for neurodegenerative disorders.</div>
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