Recent Advances in Motion Analysis
The advances in the technology and methodology for human movement capture and analysis over the last decade have been remarkable. Besides acknowledged approaches for kinematic, dynamic, and electromyographic (EMG) analysis carried out in the laboratory, more recently developed devices, such as weara...
Saved in:
HerausgeberIn: | |
---|---|
Sonstige: | |
Year of Publication: | 2021 |
Language: | English |
Physical Description: | 1 electronic resource (192 p.) |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
id |
993546122704498 |
---|---|
ctrlnum |
(CKB)5400000000046280 (oapen)https://directory.doabooks.org/handle/20.500.12854/76283 (EXLCZ)995400000000046280 |
collection |
bib_alma |
record_format |
marc |
spelling |
Di Nardo, Francesco edt Recent Advances in Motion Analysis Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute 2021 1 electronic resource (192 p.) text txt rdacontent computer c rdamedia online resource cr rdacarrier The advances in the technology and methodology for human movement capture and analysis over the last decade have been remarkable. Besides acknowledged approaches for kinematic, dynamic, and electromyographic (EMG) analysis carried out in the laboratory, more recently developed devices, such as wearables, inertial measurement units, ambient sensors, and cameras or depth sensors, have been adopted on a wide scale. Furthermore, computational intelligence (CI) methods, such as artificial neural networks, have recently emerged as promising tools for the development and application of intelligent systems in motion analysis. Thus, the synergy of classic instrumentation and novel smart devices and techniques has created unique capabilities in the continuous monitoring of motor behaviors in different fields, such as clinics, sports, and ergonomics. However, real-time sensing, signal processing, human activity recognition, and characterization and interpretation of motion metrics and behaviors from sensor data still representing a challenging problem not only in laboratories but also at home and in the community. This book addresses open research issues related to the improvement of classic approaches and the development of novel technologies and techniques in the domain of motion analysis in all the various fields of application. English Technology: general issues bicssc falls slips trips postural perturbations wearables stretch-sensors ankle kinematics rowing technology inertial sensor accelerometer performance signal processing sEMG knee random forest principal component analysis back propagation estimation model knee angle deep learning neural networks gait-phase classification electrogoniometer EMG sensors walking gait-event detection automotive radar machine learning walking analysis seated posture cognitive engagement stress level load cells embedded systems sensorized seat flexion-relaxation phenomenon surface electromyography wearable device WBSN automatic detection of the FRP Internet of Things (IoT) human activity recognition (HAR) motion analysis wearable sensors cerebral palsy hemiplegia motor disorders gait variability coefficient of variation surface EMG statistical gait analysis activation patterns co-activation Parkinson’s disease activity recognition rate invariance Lie group 3-0365-0438-9 3-0365-0439-7 Fioretti, Sandro edt Di Nardo, Francesco oth Fioretti, Sandro oth |
language |
English |
format |
eBook |
author2 |
Fioretti, Sandro Di Nardo, Francesco Fioretti, Sandro |
author_facet |
Fioretti, Sandro Di Nardo, Francesco Fioretti, Sandro |
author2_variant |
n f d nf nfd s f sf |
author2_role |
HerausgeberIn Sonstige Sonstige |
title |
Recent Advances in Motion Analysis |
spellingShingle |
Recent Advances in Motion Analysis |
title_full |
Recent Advances in Motion Analysis |
title_fullStr |
Recent Advances in Motion Analysis |
title_full_unstemmed |
Recent Advances in Motion Analysis |
title_auth |
Recent Advances in Motion Analysis |
title_new |
Recent Advances in Motion Analysis |
title_sort |
recent advances in motion analysis |
publisher |
MDPI - Multidisciplinary Digital Publishing Institute |
publishDate |
2021 |
physical |
1 electronic resource (192 p.) |
isbn |
3-0365-0438-9 3-0365-0439-7 |
illustrated |
Not Illustrated |
work_keys_str_mv |
AT dinardofrancesco recentadvancesinmotionanalysis AT fiorettisandro recentadvancesinmotionanalysis |
status_str |
n |
ids_txt_mv |
(CKB)5400000000046280 (oapen)https://directory.doabooks.org/handle/20.500.12854/76283 (EXLCZ)995400000000046280 |
carrierType_str_mv |
cr |
is_hierarchy_title |
Recent Advances in Motion Analysis |
author2_original_writing_str_mv |
noLinkedField noLinkedField noLinkedField |
_version_ |
1787548726833709057 |
fullrecord |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>04201nam-a2201009z--4500</leader><controlfield tag="001">993546122704498</controlfield><controlfield tag="005">20231214132858.0</controlfield><controlfield tag="006">m o d </controlfield><controlfield tag="007">cr|mn|---annan</controlfield><controlfield tag="008">202201s2021 xx |||||o ||| 0|eng d</controlfield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(CKB)5400000000046280</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(oapen)https://directory.doabooks.org/handle/20.500.12854/76283</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(EXLCZ)995400000000046280</subfield></datafield><datafield tag="041" ind1="0" ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Di Nardo, Francesco</subfield><subfield code="4">edt</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Recent Advances in Motion Analysis</subfield></datafield><datafield tag="260" ind1=" " ind2=" "><subfield code="a">Basel, Switzerland</subfield><subfield code="b">MDPI - Multidisciplinary Digital Publishing Institute</subfield><subfield code="c">2021</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 electronic resource (192 p.)</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">computer</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">online resource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">The advances in the technology and methodology for human movement capture and analysis over the last decade have been remarkable. Besides acknowledged approaches for kinematic, dynamic, and electromyographic (EMG) analysis carried out in the laboratory, more recently developed devices, such as wearables, inertial measurement units, ambient sensors, and cameras or depth sensors, have been adopted on a wide scale. Furthermore, computational intelligence (CI) methods, such as artificial neural networks, have recently emerged as promising tools for the development and application of intelligent systems in motion analysis. Thus, the synergy of classic instrumentation and novel smart devices and techniques has created unique capabilities in the continuous monitoring of motor behaviors in different fields, such as clinics, sports, and ergonomics. However, real-time sensing, signal processing, human activity recognition, and characterization and interpretation of motion metrics and behaviors from sensor data still representing a challenging problem not only in laboratories but also at home and in the community. This book addresses open research issues related to the improvement of classic approaches and the development of novel technologies and techniques in the domain of motion analysis in all the various fields of application.</subfield></datafield><datafield tag="546" ind1=" " ind2=" "><subfield code="a">English</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Technology: general issues</subfield><subfield code="2">bicssc</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">falls</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">slips</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">trips</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">postural perturbations</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">wearables</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">stretch-sensors</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">ankle kinematics</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">rowing</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">technology</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">inertial sensor</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">accelerometer</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">performance</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">signal processing</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">sEMG</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">knee</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">random forest</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">principal component analysis</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">back propagation</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">estimation model</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">knee angle</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">deep learning</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">neural networks</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">gait-phase classification</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">electrogoniometer</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">EMG sensors</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">walking</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">gait-event detection</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">automotive radar</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">machine learning</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">walking analysis</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">seated posture</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">cognitive engagement</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">stress level</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">load cells</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">embedded systems</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">sensorized seat</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">flexion-relaxation phenomenon</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">surface electromyography</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">wearable device</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">WBSN</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">automatic detection of the FRP</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Internet of Things (IoT)</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">human activity recognition (HAR)</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">motion analysis</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">wearable sensors</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">cerebral palsy</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">hemiplegia</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">motor disorders</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">gait variability</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">coefficient of variation</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">surface EMG</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">statistical gait analysis</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">activation patterns</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">co-activation</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Parkinson’s disease</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">activity recognition</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">rate invariance</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Lie group</subfield></datafield><datafield tag="776" ind1=" " ind2=" "><subfield code="z">3-0365-0438-9</subfield></datafield><datafield tag="776" ind1=" " ind2=" "><subfield code="z">3-0365-0439-7</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Fioretti, Sandro</subfield><subfield code="4">edt</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Di Nardo, Francesco</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Fioretti, Sandro</subfield><subfield code="4">oth</subfield></datafield><datafield tag="906" ind1=" " ind2=" "><subfield code="a">BOOK</subfield></datafield><datafield tag="ADM" ind1=" " ind2=" "><subfield code="b">2023-12-15 05:35:23 Europe/Vienna</subfield><subfield code="f">system</subfield><subfield code="c">marc21</subfield><subfield code="a">2022-04-04 09:22:53 Europe/Vienna</subfield><subfield code="g">false</subfield></datafield><datafield tag="AVE" ind1=" " ind2=" "><subfield code="i">DOAB Directory of Open Access Books</subfield><subfield code="P">DOAB Directory of Open Access Books</subfield><subfield code="x">https://eu02.alma.exlibrisgroup.com/view/uresolver/43ACC_OEAW/openurl?u.ignore_date_coverage=true&portfolio_pid=5338179330004498&Force_direct=true</subfield><subfield code="Z">5338179330004498</subfield><subfield code="b">Available</subfield><subfield code="8">5338179330004498</subfield></datafield></record></collection> |