000 08609nam a2201273 i 4500
001 7437541
003 IEEE
005 20200413152920.0
006 m eo d
007 cr cn |||m|||a
008 160320s2016 caua foab 000 0 eng d
020 _a9781627059503
_qebook
020 _z9781627054560
_qprint
024 7 _a10.2200/S00702ED1V01Y201602ARH009
_2doi
035 _a(CaBNVSL)swl00406314
035 _a(OCoLC)945166265
040 _aCaBNVSL
_beng
_erda
_cCaBNVSL
_dCaBNVSL
050 4 _aRC376.5
_b.O322 2016
060 4 _aWL 390
_bO322b 2016
082 0 4 _a616.83
_223
100 1 _aO'Hara, Kenton.,
_eauthor.
245 1 0 _aBody tracking in healthcare /
_cKenton O'Hara, Cecily Morrison, Abigail Sellen, Nadia Bianchi-Berthouze, Cathy Craig.
264 1 _aSan Rafael, California (1537 Fourth Street, San Rafael, CA 94901 USA) :
_bMorgan & Claypool,
_c2016.
300 _a1 PDF (xv, 135 pages) :
_billustrations.
336 _atext
_2rdacontent
337 _aelectronic
_2isbdmedia
338 _aonline resource
_2rdacarrier
490 1 _aSynthesis lectures on assistive, rehabilitative, and health-preserving technologies,
_x2162-7266 ;
_v# 9
538 _aMode of access: World Wide Web.
538 _aSystem requirements: Adobe Acrobat Reader.
500 _aPart of: Synthesis digital library of engineering and computer science.
504 _aIncludes bibliographical references (pages 107-131).
505 0 _a1. Introduction -- 1.1 Enabling technologies -- 1.1.1 Camera-based systems -- 1.1.2 Body worn sensors -- 1.1.3 Force and pressure-based systems -- 1.2 Body tracking in context -- 1.3 Overview --
505 8 _a2. Clinical assessment of motor disability -- 2.1 Introduction -- 2.2 Tracking disease progression in multiple sclerosis assessment -- 2.2.1 Contexts and practices in MS assessment with the EDSS -- 2.2.2 Challenges and characteristics of assessment room -- 2.2.3 Doctor-patient relationship in assessment -- 2.2.4 Summary -- 2.3 Understanding concerns in system design: assess MS system -- 2.3.1 System overview -- 2.3.2 Algorithms -- 2.3.3 Movement exercise protocol -- 2.3.4 Ensuring standardized movement performance -- 2.3.5 Framing and standardization, seeing how the machine sees -- 2.3.6 Representing the movement measure and classification -- 2.4 Conclusions --
505 8 _a3. Self-directed rehabilitation and care -- 3.1 Introduction -- 3.2 Facilitating physical activity in chronic musculoskeletal pain -- 3.3 Technology for chronic pain rehabilitation -- 3.3.1 Go-with-the-flow: sonification in movement rehabilitation -- 3.3.2 Transferring to everyday functioning: kinect vs. wearable smartphone as a body-tracking device -- 3.3.3 Self-directed rehabilitation as process: from clinical facilitation to self-management -- 3.3.4 Tracking affective states and pain levels -- 3.4 Exergaming and balance rehabilitation in older adults -- 3.4.1 Balance and fall risk in older adults -- 3.4.2 Body-tracking technology for balance training -- 3.4.3 Designing a balance training game -- 3.4.4 Understanding rehabilitative game use -- 3.5 Conclusion --
505 8 _a4. Interactions for clinicians -- 4.1 Introduction -- 4.2 Sterility and constraints on imaging practices -- 4.3 Tracking the body of the clinician for enabling touchless interaction with images -- 4.4 Clinical considerations in gesture design -- 4.4.1 Clinical constraints on movement in gesture design -- 4.4.2 Supporting collaboration and control -- 4.4.3 What actions and body parts to track for the purposes of system control -- 4.4.4 Engaging and disengaging the system -- 4.4.5 Feedback and making oneself sensed -- 4.4.6 Coarse vs. fine-grained control -- 4.5 Body tracking, gesture, and robotics -- 4.6 Increasing interaction bandwidth through input modality -- 4.7 Conclusions --
505 8 _a5. Conclusions -- 5.1 Introduction -- 5.2 Contextual design -- 5.2.1 Sensor technology -- 5.2.2 Data and algorithms -- 5.2.3 Designing movements -- 5.2.4 Interface and interaction design -- 5.2.5 Physical set-up and form factor -- 5.2.6 Social set-up and practices -- 5.3 The future -- Bibliography -- Author biographies.
506 1 _aAbstract freely available; full-text restricted to subscribers or individual document purchasers.
510 0 _aCompendex
510 0 _aINSPEC
510 0 _aGoogle scholar
510 0 _aGoogle book search
520 3 _aWithin the context of healthcare, there has been a long-standing interest in understanding the posture and movement of the human body. Gait analysis work over the years has looked to articulate the patterns and parameters of this movement both for a normal healthy body and in a range of movement-based disorders. In recent years, these efforts to understand the moving body have been transformed by significant advances in sensing technologies and computational analysis techniques all offering new ways for the moving body to be tracked, measured, and interpreted. While much of this work has been largely research focused, as the field matures, we are seeing more shifts into clinical practice. As a consequence, there is an increasing need to understand these sensing technologies over and above the specific capabilities to track, measure, and infer patterns of movement in themselves. Rather, there is an imperative to understand how the material form of these technologies enables them also to be situated in everyday healthcare contexts and practices. There are significant mutually interdependent ties between the fundamental characteristics and assumptions of these technologies and the configurations of everyday collaborative practices that are possible them. Our attention then must look to social, clinical, and technical relations pertaining to these various body technologies that may play out in particular ways across a range of different healthcare contexts and stakeholders. Our aim in this book is to explore these issues with key examples illustrating how social contexts of use relate to the properties and assumptions bound up in particular choices of body-tracking technology. We do this through a focus on three core application areas in healthcare--assessment, rehabilitation, and surgical interaction--and recent efforts to apply body-tracking technologies to them.
530 _aAlso available in print.
588 _aTitle from PDF title page (viewed on March 20, 2016).
650 0 _aGait disorders
_xDiagnosis.
650 0 _aMedical informatics.
650 0 _aPatient monitoring.
650 2 _aGait.
650 2 _aMedical Informatics.
650 2 _aMonitoring, Physiologic.
653 _abody tracking
653 _ahealthcare
653 _arehabilitation
653 _aassessment
653 _amotion tracking
653 _atechnology
653 _acomputer vision
653 _acomputing
653 _ahuman-computer interaction
653 _atouchless interaction
653 _adata
653 _aalgorithms
653 _ahealth
653 _asensors
653 _agait analysis
653 _amobile
653 _agesture
653 _amedical imaging
653 _aaccelerometer
653 _adepth sensor
653 _aforce sensors
653 _ainertial measurement unit
653 _abalance board
653 _abody-worn sensors
653 _ainteractive technology
653 _aphysiotherapy
653 _adoctor
653 _apatient
653 _amultiple sclerosis
653 _achronic pain
653 _astroke
653 _afall risk
653 _aParkinson's disease
653 _acameras
653 _aactivity monitoring
653 _acollaboration
653 _ateamwork
653 _akinematics
653 _akinetics
653 _arobotics
653 _awearable computing
653 _aexergames
653 _asurgery
653 _anatural user interfaces
653 _aexercise
653 _aolder adults
653 _anatural user interface
653 _aspeech
653 _amovement disorder
700 1 _aMorrison, Cecily.,
_eauthor.
700 1 _aSellen, Abigail J.,
_eauthor.
700 1 _aBianchi-Berthouze, Nadia,
_d1964-,
_eauthor.
700 1 _aCraig, Cathy.,
_eauthor.
776 0 8 _iPrint version:
_z9781627054560
830 0 _aSynthesis digital library of engineering and computer science.
830 0 _aSynthesis lectures on assistive, rehabilitative, and health-preserving technologies ;
_v# 9.
_x2162-7266
856 4 2 _3Abstract with links to resource
_uhttp://ieeexplore.ieee.org/servlet/opac?bknumber=7437541
999 _c562196
_d562196