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DTSTART:20231105T010000
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DTSTAMP:20230412T210827Z
UID:5A8BA269-8B64-4B45-9574-377D4B3CB9D7
DTSTART;TZID=America/New_York:20230412T153000
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DESCRIPTION:Many investigators are interested in improving the control stra
 tegies of hand prosthesis to make it functional and more convenient to use
 . The most used control approach is based on the forearm muscles activitie
 s\, named ‘ElectroMyoGraphic’ (EMG) signal. However\, these biological
  signals are very sensitive to many disturbances and are generally unpredi
 ctable in time\, type\, and level. This leads to inaccurate identification
  of user intent and threatens the prosthesis control reliability.\n\nIn a 
 first analysis\, this presentation will focus on smart sensor solution for
  estimation of simple and fine hand movements based on multi-model structu
 re. In a second analysis\, we will present fault detection approach consid
 ering several types and combinations of faults in one or two inputs signal
 s and in the same or different instants. The proposed approach is consider
 ed as a model-independent abrupt or intermittent fault detection method an
 d as an alternative solution to the unpredictable input observer-based tec
 hniques\, without any observability requirements. The proposed solution is
  appropriate for many rapidly expanding fields and practices\, including b
 iomedical engineering\, robotics\, and biofeedback therapy or even militar
 y applications.\n\nCo-sponsored by: School of Electrical Engineering and C
 omputer Science\, University of Ottawa\n\nSpeaker(s): Dr. Inès Chihi\, \n
 \nRoom: STE 5084\, Bldg: SITE\, University of Ottawa\, 800 King Edward Ave
 .\, Ottawa\, Ontario\, Canada\, K1N 6N5\, Virtual: https://events.vtools.i
 eee.org/m/355751
LOCATION:Room: STE 5084\, Bldg: SITE\, University of Ottawa\, 800 King Edwa
 rd Ave.\, Ottawa\, Ontario\, Canada\, K1N 6N5\, Virtual: https://events.vt
 ools.ieee.org/m/355751
ORGANIZER:VGroza@ieee.org
SEQUENCE:14
SUMMARY:Smart sensor for recognition of simple and complex hand movements: 
 from estimation to fault detection
URL;VALUE=URI:https://events.vtools.ieee.org/m/355751
X-ALT-DESC:Description: <br /><p>Many investigators are interested in impro
 ving the control strategies of hand prosthesis to make it functional and m
 ore convenient to use. The most used control approach is based on the fore
 arm muscles activities\, named &lsquo\;ElectroMyoGraphic&rsquo\; (EMG) sig
 nal. However\, these biological signals are very sensitive to many disturb
 ances and are generally unpredictable in time\, type\, and level. This lea
 ds to inaccurate identification of user intent and threatens the prosthesi
 s control reliability.</p>\n<p>In a first analysis\, this presentation wil
 l focus on smart sensor solution for estimation of simple and fine hand mo
 vements based on multi-model structure. In a second analysis\, we will pre
 sent fault detection approach considering several types and combinations o
 f faults in one or two inputs signals and in the same or different instant
 s. The proposed approach is considered as a model-independent abrupt or in
 termittent fault detection method and as an alternative solution to the un
 predictable input observer-based techniques\, without any observability re
 quirements. The proposed solution is appropriate for many rapidly expandin
 g fields and practices\, including biomedical engineering\, robotics\, and
  biofeedback therapy or even military applications.</p>
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