000 03184nam a22004935i 4500
001 978-3-642-24902-0
003 DE-He213
005 20140220083304.0
007 cr nn 008mamaa
008 120216s2012 gw | s |||| 0|eng d
020 _a9783642249020
_9978-3-642-24902-0
024 7 _a10.1007/978-3-642-24902-0
_2doi
050 4 _aQ342
072 7 _aUYQ
_2bicssc
072 7 _aCOM004000
_2bisacsh
082 0 4 _a006.3
_223
100 1 _aUrdiales, Cristina.
_eauthor.
245 1 0 _aCollaborative Assistive Robot for Mobility Enhancement (CARMEN)
_h[electronic resource] :
_bThe bare necessities: assisted wheelchair navigation and beyond /
_cby Cristina Urdiales.
264 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg,
_c2012.
300 _aXVI, 236p. 140 illus., 64 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aIntelligent Systems Reference Library,
_x1868-4394 ;
_v27
505 0 _aFrom the content: On the why of robotic assistive devices -- A Dummy’s Guide to Assistive Navigation Devices -- From shared control to collaborative navigation -- Bigger, faster, better, more! -- If I only had a brain -- Once more, with feeling.
520 _aIn nowadays aging society, many people require mobility assistance. Sometimes, assistive devices need a certain degree of autonomy when users' disabilities difficult manual control. However, clinicians report that excessive assistance may lead to loss of residual skills and frustration. Shared control focuses on deciding when users need help and providing it. Collaborative control aims at giving just the right amount of help in a transparent, seamless way. This book presents the collaborative control paradigm. User performance may be indicative of physical/cognitive condition, so it is used to decide how much help is needed. Besides, collaborative control integrates machine and user commands so that people contribute to self-motion at all times. Collaborative control was extensively tested for 3 years using a robotized wheelchair at a rehabilitation hospital in Rome with volunteer inpatients presenting different disabilities, ranging from mild to severe. We also present a taxonomy of common metrics for wheelchair navigation and tests are evaluated accordingly. Obtained results are coherent both from a quantitative and qualitative point of view.
650 0 _aEngineering.
650 0 _aMedical records
_xData processing.
650 0 _aArtificial intelligence.
650 0 _aBiomedical engineering.
650 1 4 _aEngineering.
650 2 4 _aComputational Intelligence.
650 2 4 _aArtificial Intelligence (incl. Robotics).
650 2 4 _aHealth Informatics.
650 2 4 _aBiomedical Engineering.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783642249013
830 0 _aIntelligent Systems Reference Library,
_x1868-4394 ;
_v27
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-642-24902-0
912 _aZDB-2-ENG
999 _c102356
_d102356