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DTSTART:20220313T030000
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BEGIN:VEVENT
DTSTAMP:20220925T032119Z
UID:1F7F95FE-7F2E-483F-89A1-08AC7CCB9D28
DTSTART;TZID=Canada/Eastern:20211122T113000
DTEND;TZID=Canada/Eastern:20211122T123000
DESCRIPTION:Wearable measurement systems have been currently spreading as p
 ersonal devices for monitoring physiological parameters. In last years\, s
 uch systems are going to be integrated in Internet of Things (IoT) systems
  where several acquisition nodes are simultaneously connected and managed.
  The acquisition nodes must comply the size and energy consumption require
 ments of wearable devices\, while allowing the streaming of sampled signal
 s such as the Electrocardiogram and the respiration wave and providing eno
 ugh accuracy to guarantee the biosignal integrity. This is even harder whe
 n the device is connected to Wide Area Network IoT systems\, characterized
  by a lower bandwidth and a higher power consumption.\n\nTo face these pro
 blems\, efficient sampling strategies can be adopted aiming to reduce the 
 data rate to be transmitted and as a consequence the energy consumption.\n
 \nThe seminar will present the state of art of sampling methods for physio
 logical signals and will in particular deal with methods based on compress
 ed sensing. Compared with the others\, such methods offer a lower computat
 ional load on the acquisition node\, by moving it to the reception side\, 
 which in the case of IoT systems\, is usually realized in the cloud. The S
 eminar will also present the activity carried out in this field by the Lab
 oratory of Signal Processing and Measurement Information of the University
  of Sannio\, mainly in the framework of the ATTICUS (Ambient-intelligent T
 ele-monitoring and Telemetry for Incepting & Catering over Human Sustainab
 ility) project.\n\nSpeaker(s): Dr. Luca De Vito \, \n\nOttawa\, Ontario\, 
 Canada\, Virtual: https://events.vtools.ieee.org/m/290606
LOCATION:Ottawa\, Ontario\, Canada\, Virtual: https://events.vtools.ieee.or
 g/m/290606
ORGANIZER:sreeramanr@sce.carleton.ca
SEQUENCE:1
SUMMARY:Sampling methods for physiological signals in Internet of Medical T
 hings systems
URL;VALUE=URI:https://events.vtools.ieee.org/m/290606
X-ALT-DESC:Description: <br /><p>Wearable measurement systems have been cur
 rently spreading as personal devices for monitoring physiological paramete
 rs. In last years\, such systems are going to be integrated in Internet of
  Things (IoT) systems where several acquisition nodes are simultaneously c
 onnected and managed. The acquisition nodes must comply the size and energ
 y consumption requirements of wearable devices\, while allowing the stream
 ing of sampled signals such as the Electrocardiogram and the respiration w
 ave and providing enough accuracy to guarantee the biosignal integrity. Th
 is is even harder when the device is connected to Wide Area Network IoT sy
 stems\, characterized by a lower bandwidth and a higher power consumption.
 </p>\n<p>To face these problems\, efficient sampling strategies can be ado
 pted aiming to reduce the data rate to be transmitted and as a consequence
  the energy consumption.</p>\n<p>The seminar will present the state of art
  of sampling methods for physiological signals and will in particular deal
  with methods based on compressed sensing. Compared with the others\, such
  methods offer a lower computational load on the acquisition node\, by mov
 ing it to the reception side\, which in the case of IoT systems\, is usual
 ly realized in the cloud. The Seminar will also present the activity carri
 ed out in this field by the Laboratory of Signal Processing and Measuremen
 t Information of the University of Sannio\, mainly in the framework of the
  ATTICUS (Ambient-intelligent Tele-monitoring and Telemetry for Incepting 
 &amp\; Catering over Human Sustainability) project.</p>
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