AMIA Annu Symp Proc - ReadySteady: app for accelerometer-based activity monitoring and wellness-motivation feedback system for older adults.

Tópicos

{ activ(1452) weight(1219) physic(1104) }
{ age(1611) year(1155) adult(843) }
{ monitor(1329) mobil(1314) devic(1160) }
{ design(1359) user(1324) use(1319) }
{ state(1844) use(1261) util(961) }
{ survey(1388) particip(1329) question(1065) }
{ data(3963) clinic(1234) research(1004) }
{ measur(2081) correl(1212) valu(896) }
{ assess(1506) score(1403) qualiti(1306) }
{ learn(2355) train(1041) set(1003) }
{ perform(999) metric(946) measur(919) }
{ visual(1396) interact(850) tool(830) }
{ implement(1333) system(1263) develop(1122) }
{ detect(2391) sensit(1101) algorithm(908) }
{ motion(1329) object(1292) video(1091) }
{ surgeri(1148) surgic(1085) robot(1054) }
{ algorithm(1844) comput(1787) effici(935) }
{ data(1714) softwar(1251) tool(1186) }
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{ imag(2675) segment(2577) method(1081) }
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{ model(2341) predict(2261) use(1141) }
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{ blood(1257) pressur(1144) flow(957) }
{ spatial(1525) area(1432) region(1030) }
{ record(1888) medic(1808) patient(1693) }
{ model(3480) simul(1196) paramet(876) }
{ research(1218) medic(880) student(794) }
{ patient(2837) hospit(1953) medic(668) }
{ model(2656) set(1616) predict(1553) }
{ data(2317) use(1299) case(1017) }
{ medic(1828) order(1363) alert(1069) }
{ signal(2180) analysi(812) frequenc(800) }
{ group(2977) signific(1463) compar(1072) }
{ sampl(1606) size(1419) use(1276) }
{ gene(2352) biolog(1181) express(1162) }
{ first(2504) two(1366) second(1323) }
{ activ(1138) subject(705) human(624) }
{ time(1939) patient(1703) rate(768) }
{ patient(1821) servic(1111) care(1106) }
{ use(2086) technolog(871) perceiv(783) }
{ can(981) present(881) function(850) }
{ analysi(2126) use(1163) compon(1037) }
{ structur(1116) can(940) graph(676) }
{ cancer(2502) breast(956) screen(824) }
{ use(976) code(926) identifi(902) }
{ use(1733) differ(960) four(931) }
{ result(1111) use(1088) new(759) }
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{ decis(3086) make(1611) patient(1517) }
{ method(1969) cluster(1462) data(1082) }

Resumo

Increased physical activity and exercise have been found to reduce falls and decrease mortality and age-related morbidity in older adults. However, a large percentage of this population fail to achieve the necessary levels of activity needed to support health living. In this work, we present a mobile app developed on the iOS platform that monitors activity levels using accelerometry. The data captured by the sensor is utilized to provide real-time motivational feedback to enable reinforcement of positive behaviors in older adults. Pilot experiments (conducted with younger adults) performed to assess validity of activity measurement showed that system accurately measures sedentary, light, moderate and vigorous activities in a controlled lab setting. Pilot tests (conducted with older adults) in the user setting showed that while the app is adept at capturing gross body activity (such as sitting, walking and jogging), additional sensors may be required to capture activities involving the extremities.

Resumo Limpo

increas physic activ exercis found reduc fall decreas mortal agerel morbid older adult howev larg percentag popul fail achiev necessari level activ need support health live work present mobil app develop io platform monitor activ level use accelerometri data captur sensor util provid realtim motiv feedback enabl reinforc posit behavior older adult pilot experi conduct younger adult perform assess valid activ measur show system accur measur sedentari light moder vigor activ control lab set pilot test conduct older adult user set show app adept captur gross bodi activ sit walk jog addit sensor may requir captur activ involv extrem

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