Comput Methods Programs Biomed - Vision-based motion detection, analysis and recognition of epileptic seizures--a systematic review.

Tópicos

{ motion(1329) object(1292) video(1091) }
{ method(1969) cluster(1462) data(1082) }
{ research(1085) discuss(1038) issu(1018) }
{ howev(809) still(633) remain(590) }
{ patient(2315) diseas(1263) diabet(1191) }
{ extract(1171) text(1153) clinic(932) }
{ data(2317) use(1299) case(1017) }
{ studi(1410) differ(1259) use(1210) }
{ spatial(1525) area(1432) region(1030) }
{ can(981) present(881) function(850) }
{ implement(1333) system(1263) develop(1122) }
{ detect(2391) sensit(1101) algorithm(908) }
{ featur(3375) classif(2383) classifi(1994) }
{ concept(1167) ontolog(924) domain(897) }
{ method(1557) propos(1049) approach(1037) }
{ case(1353) use(1143) diagnosi(1136) }
{ perform(1367) use(1326) method(1137) }
{ data(1737) use(1416) pattern(1282) }
{ imag(2675) segment(2577) method(1081) }
{ treatment(1704) effect(941) patient(846) }
{ data(1714) softwar(1251) tool(1186) }
{ care(1570) inform(1187) nurs(1089) }
{ general(901) number(790) one(736) }
{ studi(1119) effect(1106) posit(819) }
{ record(1888) medic(1808) patient(1693) }
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{ activ(1138) subject(705) human(624) }
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{ patient(2837) hospit(1953) medic(668) }
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{ signal(2180) analysi(812) frequenc(800) }
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{ gene(2352) biolog(1181) express(1162) }
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{ first(2504) two(1366) second(1323) }
{ time(1939) patient(1703) rate(768) }
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{ method(2212) result(1239) propos(1039) }

Resumo

The analysis of human motion from video has been the object of interest for many application areas, these including surveillance, control, biomedical analysis, video annotation etc. This paper addresses the advances within this topic in relation to epilepsy, a domain where human motion is with no doubt one of the most important elements of a patient's clinical image. It describes recent achievements in vision-based detection, analysis and recognition of human motion in epilepsy for marker-based and marker-free systems. An overview of motion-characterizing features extracted so far is presented separately. The objective is to gain existing knowledge in this field and set the route marks for the future development of an integrated decision support system for epilepsy diagnosis and disease management based on automated video analysis. This review revealed that the quantification of motion patterns of selected epileptic seizures has been studied thoroughly while the recognition of seizures is currently in its beginnings, but however feasible. Moreover, only a limited set of seizure types have been analyzed so far, indicating that a holistic approach addressing all epileptic syndromes is still missing.

Resumo Limpo

analysi human motion video object interest mani applic area includ surveil control biomed analysi video annot etc paper address advanc within topic relat epilepsi domain human motion doubt one import element patient clinic imag describ recent achiev visionbas detect analysi recognit human motion epilepsi markerbas markerfre system overview motioncharacter featur extract far present separ object gain exist knowledg field set rout mark futur develop integr decis support system epilepsi diagnosi diseas manag base autom video analysi review reveal quantif motion pattern select epilept seizur studi thorough recognit seizur current begin howev feasibl moreov limit set seizur type analyz far indic holist approach address epilept syndrom still miss

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