Wearable Sensor-Based In-Home Assessment of Gait, Balance, and Physical Activity for Discrimination of Frailty Status: Baseline Results of the Arizona Frailty Cohort Study

Background: Frailty is a geriatric syndrome resulting from age-related cumulative decline across multiple physiologic systems, impaired homeostatic reserve, and reduced capacity to resist stress. Based on recent estimates, 10% of community-dwelling older individuals are frail and another 41.6% are p...

Full description

Saved in:
Bibliographic Details
Published inGerontology (Basel) Vol. 61; no. 3; pp. 258 - 267
Main Authors Schwenk, Michael, Mohler, Jane, Wendel, Christopher, D''Huyvetter, Karen, Fain, Mindy, Taylor-Piliae, Ruth, Najafi, Bijan
Format Journal Article
LanguageEnglish
Published Basel, Switzerland S. Karger AG 01.04.2015
Subjects
Activity trackers
Aged
Aged, 80 and over
Aging - physiology
Arizona
Biosensors
Cohort Studies
Cross-Sectional Studies
Female
Frail Elderly
Frailty
Gait
Geriatric assessment
Geriatric Assessment - methods
Geriatric Assessment - statistics & numerical data
Geriatrics
Health aspects
Humans
Male
Medical examination
Methods
Motor Activity
Older people
Physiological aspects
Postural Balance
Posture
Regenerative and Technological Section / Original Paper
Sensors
Technology application
Walking
Arizona
United States
Frailty
Physical activity
Monitoring
Physical function
Wearable sensors
Online AccessGet full text

Cover

Abstract Background: Frailty is a geriatric syndrome resulting from age-related cumulative decline across multiple physiologic systems, impaired homeostatic reserve, and reduced capacity to resist stress. Based on recent estimates, 10% of community-dwelling older individuals are frail and another 41.6% are prefrail. Frail elders account for the highest health care costs in industrialized nations. Impaired physical function is a major indicator of frailty, and functional performance tests are useful for the identification of frailty. Objective instrumented assessments of physical functioning that are feasible for home frailty screening have not been adequately developed. Objective: To examine the ability of wearable sensor-based in-home assessment of gait, balance, and physical activity (PA) to discriminate between frailty levels (nonfrail, prefrail, and frail). Methods: In an observational cross-sectional study, in-home visits were completed in 125 older adults (nonfrail: n = 44, prefrail: n = 60, frail: n = 21) living in Tucson, Ariz., USA, between September 2012 and November 2013. Temporal-spatial gait parameters (speed, stride length, stride time, double support, and variability of stride velocity), postural balance (sway of hip, ankle, and center of mass), and PA (percentage of walking, standing, sitting, and lying; mean duration and variability of single walking, standing, sitting, and lying bouts) were measured in the participant's home using validated wearable sensor technology. Logistic regression was used to assess the most sensitive gait, balance, and PA variables for identifying prefrail participants (vs. nonfrail). Multinomial logistic regression was used to identify variables sensitive to discriminate between three frailty levels. Results: Gait speed (area under the curve, AUC = 0.802), hip sway (AUC = 0.734), and steps/day (AUC = 0.736) were the most sensitive parameters for the identification of prefrailty. Multinomial regression revealed that stride length (AUC = 0.857) and double support (AUC = 0.841) were the most sensitive gait parameters for discriminating between three frailty levels. Interestingly, walking bout duration variability was the most sensitive PA parameter for discriminating between three frailty levels (AUC = 0.818). No balance parameter discriminated between three frailty levels. Conclusion: Our results indicate that unique parameters derived from objective assessment of gait, balance, and PA are sensitive for the identification of prefrailty and the classification of a subject's frailty level. The present findings highlight the potential of wearable sensor technology for in-home assessment of frailty status.
AbstractList Background: Frailty is a geriatric syndrome resulting from age-related cumulative decline across multiple physiologic systems, impaired homeostatic reserve, and reduced capacity to resist stress. Based on recent estimates, 10% of community-dwelling older individuals are frail and another 41.6% are prefrail. Frail elders account for the highest health care costs in industrialized nations. Impaired physical function is a major indicator of frailty, and functional performance tests are useful for the identification of frailty. Objective instrumented assessments of physical functioning that are feasible for home frailty screening have not been adequately developed. Objective: To examine the ability of wearable sensor-based in-home assessment of gait, balance, and physical activity (PA) to discriminate between frailty levels (nonfrail, prefrail, and frail). Methods: In an observational cross-sectional study, in-home visits were completed in 125 older adults (nonfrail: n = 44, prefrail: n = 60, frail: n = 21) living in Tucson, Ariz., USA, between September 2012 and November 2013. Temporal-spatial gait parameters (speed, stride length, stride time, double support, and variability of stride velocity), postural balance (sway of hip, ankle, and center of mass), and PA (percentage of walking, standing, sitting, and lying; mean duration and variability of single walking, standing, sitting, and lying bouts) were measured in the participant's home using validated wearable sensor technology. Logistic regression was used to assess the most sensitive gait, balance, and PA variables for identifying prefrail participants (vs. nonfrail). Multinomial logistic regression was used to identify variables sensitive to discriminate between three frailty levels. Results: Gait speed (area under the curve, AUC = 0.802), hip sway (AUC = 0.734), and steps/day (AUC = 0.736) were the most sensitive parameters for the identification of prefrailty. Multinomial regression revealed that stride length (AUC = 0.857) and double support (AUC = 0.841) were the most sensitive gait parameters for discriminating between three frailty levels. Interestingly, walking bout duration variability was the most sensitive PA parameter for discriminating between three frailty levels (AUC = 0.818). No balance parameter discriminated between three frailty levels. Conclusion: Our results indicate that unique parameters derived from objective assessment of gait, balance, and PA are sensitive for the identification of prefrailty and the classification of a subject's frailty level. The present findings highlight the potential of wearable sensor technology for in-home assessment of frailty status. © 2014 S. Karger AG, Basel
Background: Frailty is a geriatric syndrome resulting from age-related cumulative decline across multiple physiologic systems, impaired homeostatic reserve, and reduced capacity to resist stress. Based on recent estimates, 10% of community-dwelling older individuals are frail and another 41.6% are prefrail. Frail elders account for the highest health care costs in industrialized nations. Impaired physical function is a major indicator of frailty, and functional performance tests are useful for the identification of frailty. Objective instrumented assessments of physical functioning that are feasible for home frailty screening have not been adequately developed. Objective: To examine the ability of wearable sensor-based in-home assessment of gait, balance, and physical activity (PA) to discriminate between frailty levels (nonfrail, prefrail, and frail). Methods: In an observational cross-sectional study, in-home visits were completed in 125 older adults (nonfrail: n = 44, prefrail: n = 60, frail: n = 21) living in Tucson, Ariz., USA, between September 2012 and November 2013. Temporal-spatial gait parameters (speed, stride length, stride time, double support, and variability of stride velocity), postural balance (sway of hip, ankle, and center of mass), and PA (percentage of walking, standing, sitting, and lying; mean duration and variability of single walking, standing, sitting, and lying bouts) were measured in the participant's home using validated wearable sensor technology. Logistic regression was used to assess the most sensitive gait, balance, and PA variables for identifying prefrail participants (vs. nonfrail). Multinomial logistic regression was used to identify variables sensitive to discriminate between three frailty levels. Results: Gait speed (area under the curve, AUC = 0.802), hip sway (AUC = 0.734), and steps/day (AUC = 0.736) were the most sensitive parameters for the identification of prefrailty. Multinomial regression revealed that stride length (AUC = 0.857) and double support (AUC = 0.841) were the most sensitive gait parameters for discriminating between three frailty levels. Interestingly, walking bout duration variability was the most sensitive PA parameter for discriminating between three frailty levels (AUC = 0.818). No balance parameter discriminated between three frailty levels. Conclusion: Our results indicate that unique parameters derived from objective assessment of gait, balance, and PA are sensitive for the identification of prefrailty and the classification of a subject's frailty level. The present findings highlight the potential of wearable sensor technology for in-home assessment of frailty status.
Background: Frailty is a geriatric syndrome resulting from age-related cumulative decline across multiple physiologic systems, impaired homeostatic reserve, and reduced capacity to resist stress. Based on recent estimates, 10% of community-dwelling older individuals are frail and another 41.6% are prefrail. Frail elders account for the highest health care costs in industrialized nations. Impaired physical function is a major indicator of frailty, and functional performance tests are useful for the identification of frailty. Objective instrumented assessments of physical functioning that are feasible for home frailty screening have not been adequately developed. Objective: To examine the ability of wearable sensor-based in-home assessment of gait, balance, and physical activity (PA) to discriminate between frailty levels (nonfrail, prefrail, and frail). Methods: In an observational cross-sectional study, in-home visits were completed in 125 older adults (nonfrail: n = 44, prefrail: n = 60, frail: n = 21) living in Tucson, Ariz., USA, between September 2012 and November 2013. Temporal-spatial gait parameters (speed, stride length, stride time, double support, and variability of stride velocity), postural balance (sway of hip, ankle, and center of mass), and PA (percentage of walking, standing, sitting, and lying; mean duration and variability of single walking, standing, sitting, and lying bouts) were measured in the participant's home using validated wearable sensor technology. Logistic regression was used to assess the most sensitive gait, balance, and PA variables for identifying prefrail participants (vs. nonfrail). Multinomial logistic regression was used to identify variables sensitive to discriminate between three frailty levels. Results: Gait speed (area under the curve, AUC = 0.802), hip sway (AUC = 0.734), and steps/day (AUC = 0.736) were the most sensitive parameters for the identification of prefrailty. Multinomial regression revealed that stride length (AUC = 0.857) and double support (AUC = 0.841) were the most sensitive gait parameters for discriminating between three frailty levels. Interestingly, walking bout duration variability was the most sensitive PA parameter for discriminating between three frailty levels (AUC = 0.818). No balance parameter discriminated between three frailty levels. Conclusion: Our results indicate that unique parameters derived from objective assessment of gait, balance, and PA are sensitive for the identification of prefrailty and the classification of a subject's frailty level. The present findings highlight the potential of wearable sensor technology for in-home assessment of frailty status. Keywords: Monitoring, Physical function, Physical activity, Wearable sensors, Frailty
Background: Frailty is a geriatric syndrome resulting from age-related cumulative decline across multiple physiologic systems, impaired homeostatic reserve, and reduced capacity to resist stress. Based on recent estimates, 10% of community-dwelling older individuals are frail and another 41.6% are prefrail. Frail elders account for the highest health care costs in industrialized nations. Impaired physical function is a major indicator of frailty, and functional performance tests are useful for the identification of frailty. Objective instrumented assessments of physical functioning that are feasible for home frailty screening have not been adequately developed. Objective: To examine the ability of wearable sensor-based in-home assessment of gait, balance, and physical activity (PA) to discriminate between frailty levels (nonfrail, prefrail, and frail). Methods: In an observational cross-sectional study, in-home visits were completed in 125 older adults (nonfrail: n = 44, prefrail: n = 60, frail: n = 21) living in Tucson, Ariz., USA, between September 2012 and November 2013. Temporal-spatial gait parameters (speed, stride length, stride time, double support, and variability of stride velocity), postural balance (sway of hip, ankle, and center of mass), and PA (percentage of walking, standing, sitting, and lying; mean duration and variability of single walking, standing, sitting, and lying bouts) were measured in the participant's home using validated wearable sensor technology. Logistic regression was used to assess the most sensitive gait, balance, and PA variables for identifying prefrail participants (vs. nonfrail). Multinomial logistic regression was used to identify variables sensitive to discriminate between three frailty levels. Results: Gait speed (area under the curve, AUC = 0.802), hip sway (AUC = 0.734), and steps/day (AUC = 0.736) were the most sensitive parameters for the identification of prefrailty. Multinomial regression revealed that stride length (AUC = 0.857) and double support (AUC = 0.841) were the most sensitive gait parameters for discriminating between three frailty levels. Interestingly, walking bout duration variability was the most sensitive PA parameter for discriminating between three frailty levels (AUC = 0.818). No balance parameter discriminated between three frailty levels. Conclusion: Our results indicate that unique parameters derived from objective assessment of gait, balance, and PA are sensitive for the identification of prefrailty and the classification of a subject's frailty level. The present findings highlight the potential of wearable sensor technology for in-home assessment of frailty status. copyright 2014 S. Karger AG, Basel
BACKGROUNDFrailty is a geriatric syndrome resulting from age-related cumulative decline across multiple physiologic systems, impaired homeostatic reserve, and reduced capacity to resist stress. Based on recent estimates, 10% of community-dwelling older individuals are frail and another 41.6% are prefrail. Frail elders account for the highest health care costs in industrialized nations. Impaired physical function is a major indicator of frailty, and functional performance tests are useful for the identification of frailty. Objective instrumented assessments of physical functioning that are feasible for home frailty screening have not been adequately developed.OBJECTIVETo examine the ability of wearable sensor-based in-home assessment of gait, balance, and physical activity (PA) to discriminate between frailty levels (nonfrail, prefrail, and frail).METHODSIn an observational cross-sectional study, in-home visits were completed in 125 older adults (nonfrail: n=44, prefrail: n=60, frail: n=21) living in Tucson, Ariz., USA, between September 2012 and November 2013. Temporal-spatial gait parameters (speed, stride length, stride time, double support, and variability of stride velocity), postural balance (sway of hip, ankle, and center of mass), and PA (percentage of walking, standing, sitting, and lying; mean duration and variability of single walking, standing, sitting, and lying bouts) were measured in the participant's home using validated wearable sensor technology. Logistic regression was used to assess the most sensitive gait, balance, and PA variables for identifying prefrail participants (vs. nonfrail). Multinomial logistic regression was used to identify variables sensitive to discriminate between three frailty levels.RESULTSGait speed (area under the curve, AUC=0.802), hip sway (AUC=0.734), and steps/day (AUC=0.736) were the most sensitive parameters for the identification of prefrailty. Multinomial regression revealed that stride length (AUC=0.857) and double support (AUC=0.841) were the most sensitive gait parameters for discriminating between three frailty levels. Interestingly, walking bout duration variability was the most sensitive PA parameter for discriminating between three frailty levels (AUC=0.818). No balance parameter discriminated between three frailty levels.CONCLUSIONOur results indicate that unique parameters derived from objective assessment of gait, balance, and PA are sensitive for the identification of prefrailty and the classification of a subject's frailty level. The present findings highlight the potential of wearable sensor technology for in-home assessment of frailty status.
Frailty is a geriatric syndrome resulting from age-related cumulative decline across multiple physiologic systems, impaired homeostatic reserve, and reduced capacity to resist stress. Based on recent estimates, 10% of community-dwelling older individuals are frail and another 41.6% are prefrail. Frail elders account for the highest health care costs in industrialized nations. Impaired physical function is a major indicator of frailty, and functional performance tests are useful for the identification of frailty. Objective instrumented assessments of physical functioning that are feasible for home frailty screening have not been adequately developed. To examine the ability of wearable sensor-based in-home assessment of gait, balance, and physical activity (PA) to discriminate between frailty levels (nonfrail, prefrail, and frail). In an observational cross-sectional study, in-home visits were completed in 125 older adults (nonfrail: n=44, prefrail: n=60, frail: n=21) living in Tucson, Ariz., USA, between September 2012 and November 2013. Temporal-spatial gait parameters (speed, stride length, stride time, double support, and variability of stride velocity), postural balance (sway of hip, ankle, and center of mass), and PA (percentage of walking, standing, sitting, and lying; mean duration and variability of single walking, standing, sitting, and lying bouts) were measured in the participant's home using validated wearable sensor technology. Logistic regression was used to assess the most sensitive gait, balance, and PA variables for identifying prefrail participants (vs. nonfrail). Multinomial logistic regression was used to identify variables sensitive to discriminate between three frailty levels. Gait speed (area under the curve, AUC=0.802), hip sway (AUC=0.734), and steps/day (AUC=0.736) were the most sensitive parameters for the identification of prefrailty. Multinomial regression revealed that stride length (AUC=0.857) and double support (AUC=0.841) were the most sensitive gait parameters for discriminating between three frailty levels. Interestingly, walking bout duration variability was the most sensitive PA parameter for discriminating between three frailty levels (AUC=0.818). No balance parameter discriminated between three frailty levels. Our results indicate that unique parameters derived from objective assessment of gait, balance, and PA are sensitive for the identification of prefrailty and the classification of a subject's frailty level. The present findings highlight the potential of wearable sensor technology for in-home assessment of frailty status.
Audience Academic
Author Mohler, Jane
Wendel, Christopher
Fain, Mindy
Taylor-Piliae, Ruth
Schwenk, Michael
D''Huyvetter, Karen
Najafi, Bijan
AuthorAffiliation a Arizona Center on Aging, College of Medicine, University of Arizona, Tucson, AZ
d College of Nursing, University of Arizona, Tucson, AZ
b Division of Geriatrics, General Internal Medicine, and Palliative Medicine, Department of Medicine, College of Medicine, University of Arizona, Tucson, AZ
c Interdisciplinary Consortium on Advanced Motion Performance (iCAMP), Department of Surgery, College of Medicine, University of Arizona, Tucson, AZ
AuthorAffiliation_xml – name: b Division of Geriatrics, General Internal Medicine, and Palliative Medicine, Department of Medicine, College of Medicine, University of Arizona, Tucson, AZ
– name: c Interdisciplinary Consortium on Advanced Motion Performance (iCAMP), Department of Surgery, College of Medicine, University of Arizona, Tucson, AZ
– name: a Arizona Center on Aging, College of Medicine, University of Arizona, Tucson, AZ
– name: d College of Nursing, University of Arizona, Tucson, AZ
Author_xml – sequence: 1
  givenname: Michael
  surname: Schwenk
  fullname: Schwenk, Michael
– sequence: 2
  givenname: Jane
  surname: Mohler
  fullname: Mohler, Jane
  email: jmohler@aging.arizona.edu
– sequence: 3
  givenname: Christopher
  surname: Wendel
  fullname: Wendel, Christopher
– sequence: 4
  givenname: Karen
  surname: D''Huyvetter
  fullname: D''Huyvetter, Karen
– sequence: 5
  givenname: Mindy
  surname: Fain
  fullname: Fain, Mindy
– sequence: 6
  givenname: Ruth
  surname: Taylor-Piliae
  fullname: Taylor-Piliae, Ruth
– sequence: 7
  givenname: Bijan
  surname: Najafi
  fullname: Najafi, Bijan
BackLink https://www.ncbi.nlm.nih.gov/pubmed/25547185$$D View this record in MEDLINE/PubMed
BookMark eNqFkl1rFDEUhgep2G31wnuRgCAKHc3HZDLjhbBd7QcUFKvo3XBm5kw3bTapSaaw_iX_pBl2XdQbrwLnPO97OG_OQbZnncUse8zoK8Zk_ZpSKsqa1vJeNmMFF_lU2MtmVNAiF7z4tp8dhHCdipQz-iDb51IWilVylv38iuChNUgu0Qbn82MI2JNzm5-5FZJ5CBjCCm0kbiCnoOMROQYDtsMjArYnH5froDswZN5FfafjmgzOk3c6dF6vtIWonZ2kJx60Sd3LCHEMb8g0xmiL5BOG0cQwMXGZBnr9w1nY8Qu3dD4m2divH2b3BzABH23fw-zLyfvPi7P84sPp-WJ-kXclL2LOgEKJHceqrpSCthy6XrGCgcBSqpZxIaVSAlqEUtG2rytZgBAD5xV0smXiMHu78b0d2xX2Xdreg2lu00bg140D3fzdsXrZXLm7pigkZ6xKBi-2Bt59HzHEZpUCQZNyQzeGhlW1EqpQJf0_WipVVZLSOqHP_kGv3ehtSiJRVV2WjKtp9vMNdQUGmyWCicvgzDh9RGjmpVCcFpSLBL7cgJ13IXgcdgsy2kxn1ezOKrFP_0xkR_6-owQ82QA34K_Q74Ct_hfnh9MS
CitedBy_id crossref_primary_10_3390_s21072258
crossref_primary_10_1136_bmjopen_2022_070507
crossref_primary_10_1177_1358863X16660626
crossref_primary_10_3390_s21165289
crossref_primary_10_3390_s21206918
crossref_primary_10_1016_j_gaitpost_2023_10_006
crossref_primary_10_1159_000535283
crossref_primary_10_1111_ggi_13492
crossref_primary_10_2196_19732
crossref_primary_10_1007_s40520_020_01686_x
crossref_primary_10_3390_app7100986
crossref_primary_10_3390_s22165940
crossref_primary_10_1186_s12877_019_1089_z
crossref_primary_10_1186_s12891_022_05211_1
crossref_primary_10_1186_s12984_023_01247_z
crossref_primary_10_3389_fnagi_2021_729060
crossref_primary_10_2139_ssrn_4095799
crossref_primary_10_3389_fpubh_2023_1169083
crossref_primary_10_3390_s22186745
crossref_primary_10_3390_nu11081770
crossref_primary_10_1007_s40520_016_0693_4
crossref_primary_10_1007_s00391_016_1129_7
crossref_primary_10_2139_ssrn_4104254
crossref_primary_10_1159_000441494
crossref_primary_10_1590_s1980_220x2017028703392
crossref_primary_10_1109_JBHI_2017_2677901
crossref_primary_10_1109_JBHI_2022_3181738
crossref_primary_10_3390_s19030452
crossref_primary_10_1177_1084822316640266
crossref_primary_10_12968_jowc_2018_27_Sup6a_S1
crossref_primary_10_1186_s12877_020_01572_1
crossref_primary_10_1159_000502288
crossref_primary_10_1038_s41598_024_53025_z
crossref_primary_10_3390_s22093555
crossref_primary_10_1093_gerona_gly170
crossref_primary_10_1109_TNSRE_2022_3186616
crossref_primary_10_1159_000515078
crossref_primary_10_3390_ijerph19138164
crossref_primary_10_3390_s20123427
crossref_primary_10_3390_s20020505
crossref_primary_10_1016_j_jalz_2018_05_003
crossref_primary_10_1186_s12889_019_7062_0
crossref_primary_10_1016_j_regg_2017_10_006
crossref_primary_10_1016_j_clinbiomech_2019_12_019
crossref_primary_10_3390_s20082218
crossref_primary_10_1007_s40520_023_02525_5
crossref_primary_10_3390_electronics9050728
crossref_primary_10_3390_s22103893
crossref_primary_10_1371_journal_pone_0264013
crossref_primary_10_3390_s21092983
crossref_primary_10_1007_s12603_016_0764_4
crossref_primary_10_2196_48270
crossref_primary_10_1186_s12877_023_04106_7
crossref_primary_10_1186_s12877_021_02252_4
crossref_primary_10_3390_s18061763
crossref_primary_10_1159_000530900
crossref_primary_10_3390_s21124017
crossref_primary_10_3390_std13020011
crossref_primary_10_3390_s22093532
crossref_primary_10_1123_jmpb_2019_0029
crossref_primary_10_1016_j_jclinepi_2021_04_009
crossref_primary_10_1186_s11556_019_0223_4
crossref_primary_10_1007_s40520_020_01626_9
crossref_primary_10_1007_s12603_018_1057_x
crossref_primary_10_2196_14090
crossref_primary_10_1016_j_bbr_2020_113061
crossref_primary_10_1109_JBHI_2021_3100979
crossref_primary_10_1159_000520401
crossref_primary_10_1186_s12877_019_1048_8
crossref_primary_10_3389_fpubh_2022_861621
crossref_primary_10_1123_japa_2016_0287
crossref_primary_10_1371_journal_pone_0286707
crossref_primary_10_3390_s18051613
crossref_primary_10_1016_j_jos_2024_01_001
crossref_primary_10_3390_app10238451
crossref_primary_10_3390_s18051336
crossref_primary_10_1590_0034_7167_2019_0601
crossref_primary_10_1080_01616412_2016_1187829
crossref_primary_10_14336_AD_2020_1114
crossref_primary_10_1177_1932296819839703
crossref_primary_10_1186_s42490_019_0007_y
crossref_primary_10_1007_s00256_015_2313_3
crossref_primary_10_7547_15_186
crossref_primary_10_2196_20834
crossref_primary_10_1038_s41746_019_0204_z
crossref_primary_10_3390_s23125446
crossref_primary_10_1080_01621424_2016_1264340
crossref_primary_10_1177_1932296820904947
crossref_primary_10_1097_MRR_0000000000000453
crossref_primary_10_3310_hta21730
crossref_primary_10_1038_s41746_022_00657_y
crossref_primary_10_1186_s12984_021_00909_0
crossref_primary_10_1186_s12877_022_03711_2
crossref_primary_10_1159_000445889
crossref_primary_10_1007_s12652_019_01593_8
crossref_primary_10_3390_brainsci13071018
crossref_primary_10_1016_j_clinbiomech_2016_10_007
crossref_primary_10_3389_fneur_2018_00257
crossref_primary_10_3390_s22239278
crossref_primary_10_3390_ijerph18010203
Cites_doi 10.1159/000363136
10.1046/j.1532-5415.2001.49281.x
10.1016/0197-4580(89)90010-9
10.1016/j.critrevonc.2009.12.002
10.1093/gerona/gls119
10.1177/193229681300700507
10.1016/j.exger.2014.01.024
10.1093/gerona/glr007
10.1159/000081435
10.1016/j.gaitpost.2007.02.005
10.1177/193229681000400403
10.1016/S0021-9290(02)00008-8
10.1016/j.jbiomech.2011.06.007
10.1016/0021-9681(78)90058-9
10.1126/sageke.2004.16.pe16
10.1016/j.gaitpost.2008.09.002
10.1093/gerona/56.3.M146
10.1159/000354211
10.1111/jgs.12122
10.1016/j.archger.2011.12.005
10.2340/16501977-0791
10.1109/TBME.2002.800763
10.1093/gerona/gln001
10.1109/IEMBS.2011.6091605
10.1111/j.1532-5415.2009.02394.x
10.1016/j.jpainsymman.2009.04.007
10.1093/ageing/afi196
10.1093/ageing/afp226
10.1111/j.1532-5415.2008.02008.x
10.1016/j.archger.2010.06.013
10.2165/00007256-200131020-00002
10.1093/gerona/51A.6.M303
10.1016/S0966-6362(03)00089-4
10.1111/j.1447-0594.2012.00920.x
10.1016/j.exger.2006.08.011
10.1093/gerona/62.7.722
10.1093/gerona/59.12.1295
10.1016/0022-3956(75)90026-6
10.1111/j.1532-5415.2012.04145.x
10.1109/TBME.2003.812189
ContentType Journal Article
Copyright 2014 S. Karger AG, Basel
COPYRIGHT 2015 S. Karger AG
Copyright (c) 2015 S. Karger AG, Basel
Copyright_xml – notice: 2014 S. Karger AG, Basel
– notice: COPYRIGHT 2015 S. Karger AG
– notice: Copyright (c) 2015 S. Karger AG, Basel
DBID CGR
CUY
CVF
ECM
EIF
NPM
AAYXX
CITATION
0-V
3V.
7RV
7TK
7X7
7XB
88E
88G
88I
88J
8AF
8AO
8C1
8FI
8FJ
8FK
ABUWG
AFKRA
ALSLI
AZQEC
BENPR
CCPQU
DWQXO
FYUFA
GHDGH
GNUQQ
HCIFZ
K9.
KB0
M0S
M1P
M2M
M2P
M2R
NAPCQ
PQEST
PQQKQ
PQUKI
PRINS
PSYQQ
Q9U
S0X
7X8
7TS
5PM
DOI 10.1159/000369095
DatabaseName Medline
MEDLINE
MEDLINE (Ovid)
MEDLINE
MEDLINE
PubMed
CrossRef
ProQuest Social Sciences Premium Collection
ProQuest Central (Corporate)
Nursing & Allied Health Database
Neurosciences Abstracts
Health & Medical Collection
ProQuest Central (purchase pre-March 2016)
Medical Database (Alumni Edition)
Psychology Database (Alumni)
Science Database (Alumni Edition)
Social Science Database (Alumni Edition)
STEM Database
ProQuest Pharma Collection
Public Health Database
Hospital Premium Collection
Hospital Premium Collection (Alumni Edition)
ProQuest Central (Alumni) (purchase pre-March 2016)
ProQuest Central (Alumni)
ProQuest Central
Social Science Premium Collection
ProQuest Central Essentials
ProQuest Databases
ProQuest One Community College
ProQuest Central Korea
Health Research Premium Collection
Health Research Premium Collection (Alumni)
ProQuest Central Student
SciTech Premium Collection
ProQuest Health & Medical Complete (Alumni)
Nursing & Allied Health Database (Alumni Edition)
Health & Medical Collection (Alumni Edition)
PML(ProQuest Medical Library)
Psychology Database
Science Database (ProQuest)
Social Science Database
Nursing & Allied Health Premium
ProQuest One Academic Eastern Edition (DO NOT USE)
ProQuest One Academic
ProQuest One Academic UKI Edition
ProQuest Central China
ProQuest One Psychology
ProQuest Central Basic
SIRS Editorial
MEDLINE - Academic
Physical Education Index
PubMed Central (Full Participant titles)
DatabaseTitle MEDLINE
Medline Complete
MEDLINE with Full Text
PubMed
MEDLINE (Ovid)
CrossRef
ProQuest One Psychology
ProQuest Central Student
ProQuest Central Essentials
SIRS Editorial
ProQuest Social Science Journals (Alumni Edition)
ProQuest Health & Medical Complete (Alumni)
ProQuest AP Science
ProQuest Central (Alumni Edition)
SciTech Premium Collection
ProQuest One Community College
ProQuest Pharma Collection
ProQuest Central China
ProQuest Central
Health Research Premium Collection
Health and Medicine Complete (Alumni Edition)
ProQuest Central Korea
ProQuest Medical Library (Alumni)
Social Science Premium Collection
ProQuest Public Health
ProQuest Science Journals (Alumni Edition)
ProQuest Central Basic
ProQuest Science Journals
ProQuest One Academic Eastern Edition
ProQuest Nursing & Allied Health Source
ProQuest Hospital Collection
Health Research Premium Collection (Alumni)
ProQuest Psychology Journals (Alumni)
Neurosciences Abstracts
ProQuest Hospital Collection (Alumni)
Nursing & Allied Health Premium
ProQuest Health & Medical Complete
ProQuest Social Science Journals
ProQuest Medical Library
ProQuest Psychology Journals
ProQuest Social Sciences Premium Collection
ProQuest One Academic UKI Edition
ProQuest Nursing & Allied Health Source (Alumni)
ProQuest One Academic
ProQuest Central (Alumni)
MEDLINE - Academic
Physical Education Index
DatabaseTitleList ProQuest One Psychology


CrossRef
Physical Education Index
MEDLINE - Academic
MEDLINE
Database_xml – sequence: 1
  dbid: NPM
  name: PubMed
  url: https://proxy.k.utb.cz/login?url=http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed
  sourceTypes: Index Database
– sequence: 2
  dbid: EIF
  name: MEDLINE
  url: https://proxy.k.utb.cz/login?url=https://www.webofscience.com/wos/medline/basic-search
  sourceTypes: Index Database
– sequence: 3
  dbid: BENPR
  name: ProQuest Central
  url: https://www.proquest.com/central
  sourceTypes: Aggregation Database
DeliveryMethod fulltext_linktorsrc
Discipline Medicine
Social Welfare & Social Work
Anatomy & Physiology
EISSN 1423-0003
EndPage 267
ExternalDocumentID 3719156581
A637204023
10_1159_000369095
25547185
369095
Genre Journal Article
Observational Study
Research Support, N.I.H., Extramural
GeographicLocations Arizona
United States
GeographicLocations_xml – name: Arizona
– name: United States
GrantInformation_xml – fundername: NIA NIH HHS
  grantid: R42 AG032748
– fundername: NIA NIH HHS
  grantid: 2R42AG032748
GroupedDBID ---
-~X
.GJ
0-V
0R~
0~5
0~B
29H
30W
328
34G
36B
39C
3O.
3V.
4.4
53G
5GY
5RE
7RV
7X7
88E
88I
8AF
8AO
8C1
8FI
8FJ
8UI
AAWTL
AAYIC
ABDNZ
ABIVO
ABJNI
ABPAZ
ABUWG
ACGFS
ACGOD
ACNCT
ACPRK
ACPSR
ACYGS
ADAGL
ADBBV
AENEX
AEYAO
AFDXO
AFFNX
AFJJK
AFKRA
AHMBA
ALDHI
ALIPV
ALMA_UNASSIGNED_HOLDINGS
ALSLI
ARALO
AZPMC
AZQEC
BENPR
BKEYQ
BPHCQ
BVXVI
CAG
CCPQU
COF
CS3
CYUIP
DWQXO
E0A
EBS
EJD
EMB
EMOBN
EX3
F5P
FB.
FYUFA
GNUQQ
HCIFZ
HMCUK
HZ~
H~9
IAO
IHR
IHW
INH
IY7
KUZGX
L7B
LPU
M1P
M2M
M2P
M2R
N9A
NAPCQ
O1H
O9-
PQQKQ
PROAC
PSQYO
PSYQQ
RIG
RKO
RXVBD
S0X
SV3
TWZ
UJ6
UKHRP
UPT
WH7
WOW
X7L
YCJ
ZGI
ZXP
AEILP
CGR
CUY
CVF
ECM
EIF
ITC
NPM
AAYXX
CITATION
7TK
7XB
8FK
K9.
PQEST
PQUKI
PRINS
Q9U
7X8
7TS
5PM
ID FETCH-LOGICAL-c624t-1a0a6ec2e89877ab6fcd7141a3e657b12355773abea670bd9854a33f228ac5b13
IEDL.DBID 8C1
ISSN 0304-324X
IngestDate Tue Sep 17 21:19:48 EDT 2024
Thu Oct 24 23:56:21 EDT 2024
Fri Oct 25 02:27:29 EDT 2024
Thu Oct 10 20:19:56 EDT 2024
Tue Aug 20 22:10:32 EDT 2024
Fri Dec 06 08:16:03 EST 2024
Sat Sep 28 07:56:47 EDT 2024
Thu Aug 29 12:04:35 EDT 2024
IsDoiOpenAccess false
IsOpenAccess true
IsPeerReviewed true
IsScholarly true
Issue 3
Keywords Frailty
Physical activity
Monitoring
Physical function
Wearable sensors
Language English
License Copyright: All rights reserved. No part of this publication may be translated into other languages, reproduced or utilized in any form or by any means, electronic or mechanical, including photocopying, recording, microcopying, or by any information storage and retrieval system, without permission in writing from the publisher.
2014 S. Karger AG, Basel
https://www.karger.com/Services/SiteLicenses
LinkModel DirectLink
MergedId FETCHMERGED-LOGICAL-c624t-1a0a6ec2e89877ab6fcd7141a3e657b12355773abea670bd9854a33f228ac5b13
Notes ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Undefined-1
ObjectType-Feature-3
content type line 23
ObjectType-Article-1
ObjectType-Feature-2
ORCID 0000-0002-0320-8101
OpenAccessLink https://karger.com/ger/article-pdf/61/3/258/2837376/000369095.pdf
PMID 25547185
PQID 1689661278
PQPubID 33168
PageCount 10
ParticipantIDs pubmedcentral_primary_oai_pubmedcentral_nih_gov_4452118
gale_healthsolutions_A637204023
proquest_journals_1689661278
karger_primary_369095
pubmed_primary_25547185
proquest_miscellaneous_1897374760
proquest_miscellaneous_1677885009
crossref_primary_10_1159_000369095
PublicationCentury 2000
PublicationDate 20150401
PublicationDateYYYYMMDD 2015-04-01
PublicationDate_xml – month: 04
  year: 2015
  text: 20150401
  day: 01
PublicationDecade 2010
PublicationPlace Basel, Switzerland
PublicationPlace_xml – name: Basel, Switzerland
– name: Switzerland
– name: Basel
PublicationTitle Gerontology (Basel)
PublicationTitleAlternate Gerontology
PublicationYear 2015
Publisher S. Karger AG
Publisher_xml – name: S. Karger AG
References Fieo RA, Mortensen EL, Rantanen T, Avlund K: Improving a measure of mobility-related fatigue (the mobility-tiredness scale) by establishing item intensity. J Am Geriatr Soc 2013;61:429-433.2345200110.1111/jgs.12122
Mohler MJ, Fain MJ, Wertheimer AM, Najafi B, Nikolich-Žugich J: The frailty syndrome: clinical measurements and basic underpinnings in humans and animals. Exp Gerontol 2014;54C:6-13.2450305910.1016/j.exger.2014.01.024
Kiely DK, Cupples LA, Lipsitz LA: Validation and comparison of two frailty indexes: The MOBILIZE Boston Study. J Am Geriatr Soc 2009;57:1532-1539.1968211210.1111/j.1532-5415.2009.02394.x
Peterson LE: Mlogitroc: Stata module to calculate multiclass ROC curves and AUC from multinomial logistic regression. Statistical Software Components S457181, Boston College Department of Economics, Boston, 2010.
Theou O, Jakobi JM, Vandervoort AA, Jones GR: A comparison of physical activity (PA) assessment tools across levels of frailty. Arch Gerontol Geriatr 2012;54:307-314.2220945410.1016/j.archger.2011.12.005
Najafi B, Helbostad JL, Moe-Nilssen R, Zijlstra W, Aminian K: Does walking strategy in older people change as a function of walking distance? Gait Posture 2009;29:261-266.1895243510.1016/j.gaitpost.2008.09.002
Rockwood K, Mitnitski A: Frailty in relation to the accumulation of deficits. J Gerontol A Biol Sci Med Sci 2007;62:722-727.1763431810.1093/gerona/62.7.722
Najafi B, Khan T, Wrobel J: Laboratory in a box: wearable sensors and its advantages for gait analysis. Conf Proc IEEE Eng Med Biol Soc 2011;2011:6507-6510.2225582910.1109/IEMBS.2011.6091605
Marzetti E, Leeuwenburgh C: Skeletal muscle apoptosis, sarcopenia and frailty at old age. Exp Gerontol 2006;41:1234-1238.1705287910.1016/j.exger.2006.08.011
Verghese J, Holtzer R, Lipton RB, Wang C: Mobility stress test approach to predicting frailty, disability, and mortality in high-functioning older adults. J Am Geriatr Soc 2012;60:1901-1905.2300271410.1111/j.1532-5415.2012.04145.x
Fried LP, Tangen CM, Walston J, Newman AB, Hirsch C, Gottdiener J, Seeman T, Tracy R, Kop WJ, Burke G, McBurnie MA; Cardiovascular Health Study Collaborative Research Group: Frailty in older adults: evidence for a phenotype. J Gerontol A Biol Sci Med Sci 2001;56:M146-M156.1125315610.1093/gerona/56.3.M146
Najafi B, Armstrong DG, Mohler J: Novel wearable technology for assessing spontaneous daily physical activity and risk of falling in older adults with diabetes. J Diabetes Sci Technol 2013;7:1147-1160.2412494010.1177/193229681300700507
Taylor HL, Jacobs DR Jr, Schucker B, Knudsen J, Leon AS, Debacker G: A questionnaire for the assessment of leisure time physical activities. J Chron Dis 1978;31:741-755.74837010.1016/0021-9681(78)90058-9
Kressig RW, Gregor RJ, Oliver A, Waddell D, Smith W, O'Grady M, Curns AT, Kutner M, Wolf SL: Temporal and spatial features of gait in older adults transitioning to frailty. Gait Posture 2004;20:30-35.1519651710.1016/S0966-6362(03)00089-4
Woollacott MH: Changes in postural control and the integration of postural responses into voluntary movements with aging; in Brand T, Paulus W, Bles W, Deiterich M, Krafezyk S, Strabue A (eds): Disorders of Posture and Gait. Stuttgart, Georg Thieme Verlag, 1990, pp 221-228.
Woollacott MH, Tang P-F: Balance control during walking in the older adult: research and its implications. Phys Ther 1997;77:646-660.9184689
Lindemann U, Najafi B, Zijlstra W, Hauer K, Muche R, Becker C, Aminian K: Distance to achieve steady state walking speed in frail elderly persons. Gait Posture 2008;27:91-96.1738318510.1016/j.gaitpost.2007.02.005
Montero-Odasso M, Muir SW, Hall M, Doherty TJ, Kloseck M, Beauchet O, Speechley M: Gait variability is associated with frailty in community-dwelling older adults. J Gerontol A Biol Sci Med Sci 2011;66:568-576.2135719010.1093/gerona/glr007
Kellen E, Bulens P, Deckx L, Schouten H, Van Dijk M, Verdonck I, Buntinx F: Identifying an accurate pre-screening tool in geriatric oncology. Crit Rev Oncol Hematol 2010;75:243-248.2006031310.1016/j.critrevonc.2009.12.002
Davis DH, Rockwood MR, Mitnitski AB, Rockwood K: Impairments in mobility and balance in relation to frailty. Arch Gerontol Geriatr 2011;53:79-83.2067881610.1016/j.archger.2010.06.013
Schwenk M, Hauer K, Zieschang T, Englert S, Mohler J, Najafi B: Sensor-derived physical activity parameters can predict future falls in people with dementia. Gerontology 2014;60:483-492.2517130010.1159/000363136
Hosmer DW Jr, Lemeshow S: Applied Logistic Regression. New York, John Wiley & Sons, 2004.
Rodríguez-Mañas L, Féart C, Mann G, Viña J, Chatterji S, Chodzko-Zajko W, Harmand MG-C, Bergman H, Carcaillon L, Nicholson C: Searching for an operational definition of frailty: a Delphi method based consensus statement: the frailty operative definition-consensus conference project. J Gerontol A Biol Sci Med Sci 2013;68:62-67.2251128910.1093/gerona/gls119
Verghese J, Xue X: Identifying frailty in high functioning older adults with normal mobility. Age Ageing 2010;39:382-385.2005160710.1093/ageing/afp226
Schwenk M, Schmidt M, Pfisterer M, Oster P, Hauer K: Rollator use adversely impacts on assessment of gait and mobility during geriatric rehabilitation. J Rehabil Med 2011;43:424-429.2144855710.2340/16501977-0791
Judge JO, Davis RB 3rd, Õunpuu S: Step length reductions in advanced age: the role of ankle and hip kinetics. J Gerontol A Biol Sci Med Sci 1996;51:M303-M312.891450310.1093/gerona/51A.6.M303
Schwenk M, Howe C, Saleh A, Mohler J, Grewal G, Armstrong D, Najafi B: Frailty and technology: a systematic review of gait analysis in those with frailty. Gerontology 2013;60:79-89.2394944110.1159/000354211
Tudor-Locke C, Myers A: Challenges and opportunities for measuring physical activity in sedentary adults. Sports Med 2001;31:91-100.1122798110.2165/00007256-200131020-00002
Dayhoff NE, Suhrheinrich J, Wigglesworth J, Topp R, Moore S: Balance and muscle strength as predictors of frailty among older adults. J Gerontol Nurs 1998;24:18-27.9801527
Najafi B, Horn D, Marclay S, Crews RT, Wu S, Wrobel JS: Assessing postural control and postural control strategy in diabetes patients using innovative and wearable technology. J Diabetes Sci Technol 2010;4:780-791.2066343810.1177/193229681000400403
Aminian K, Najafi B, Büla C, Leyvraz PF, Robert P: Spatio-temporal parameters of gait measured by an ambulatory system using miniature gyroscopes. J Biomech 2002;35:689-699.1195550910.1016/S0021-9290(02)00008-8
Beauchet O, Dubost V, Gonthier R, Kressig RW: Dual-task-related gait changes in transitionally frail older adults: the type of the walking-associated cognitive task matters. Gerontology 2005;51:48-52.1559175610.1159/000081435
Najafi B, Aminian K, Loew F, Blanc Y, Robert PA: Measurement of stand-sit and sit-stand transitions using a miniature gyroscope and its application in fall risk evaluation in the elderly. IEEE Trans Biomed Eng 2002;49:843-851.1214882310.1109/TBME.2002.800763
Lipsitz LA: Physiological complexity, aging, and the path to frailty. Sci Aging Knowledge Environ 2004:pe16.1510305510.1126/sageke.2004.16.pe16
Saliba D, Elliott M, Rubenstein LZ, Solomon DH, Young RT, Kamberg CJ, Roth C, MacLean CH, Shekelle PG, Sloss EM: The vulnerable elders survey: a tool for identifying vulnerable older people in the community. J Am Geriatr Soc 2001;49:1691-1699.1184400510.1046/j.1532-5415.2001.49281.x
Hauer K, Lord SR, Lindemann U, Lamb SE, Aminian K, Schwenk M: Assessment of physical activity in older people with and without cognitive impairment. J Aging Phys Act 2011;19:347-372.21911876
Mahoney FI, Barthel DW: Functional evaluation: the Barthel index. Md State Med J 1965;14:61-65.14258950
Rowe DA, Kemble CD, Robinson TS, Mahar MT: Daily walking in older adults: day-to-day variability and criterion-referenced validity of total daily step counts. J Phys Act Health 2007;4:434-446.18209234
Yardley L, Beyer N, Hauer K, Kempen G, Piot-Ziegler C, Todd C: Development and initial validation of the Falls Efficacy Scale-International (FES-I). Age Ageing 2005;34:614-619.1626718810.1093/ageing/afi196
Eaton W, Smith C, Ybarra M, Muntaner C, Tien A: Center for Epidemiologic Studies Depression Scale: review and revision; in Maruish M (ed): The Use of Psychological Testing for Treatment Planning and Outcomes Assessment. New Jersey, Lawrence Erlbaum Associates, 2004, vol 3, pp 363-377.
Melzer D, Lan T-Y, Tom BD, Deeg DJ, Guralnik JM: Variation in thresholds for reporting mobility disability between national population subgroups and studies. J Gerontol A Biol Sci Med Sci 2004;59:1295-1303.1569952910.1093/gerona/59.12.1295
Peterson MJ, Giuliani C, Morey MC, Pieper CF, Evenson KR, Mercer V, Cohen HJ, Visser M, Brach JS, Kritchevsky SB: Physical activity as a preventative factor for frailty: the health, aging, and body composition study. J Gerontol A Biol Sci Med Sci 2009;64:61-68.1916427610.1093/gerona/gln001
Rothman MD, Leo-Summers L, Gill TM: Prognostic significance of potential frailty criteria. J Am Geriatr Soc 2008;56:2211-2216.1909392010.1111/j.1532-5415.2008.02008.x
Horak FB, Shupert CL, Mirka A: Components of postural dyscontrol in the elderly: a review. Neurobiol Aging 1989;10:727-738.269780810.1016/0197-4580(89)90010-9
Fassbender K, Fainsinger RL, Carson M, Finegan BA: Cost trajectories at the end of life: the Canadian experience. J Pain Symptom Manage 2009;38:75-80.1961563010.1016/j.jpainsymman.2009.04.007
Martínez-Ramírez A, Lecumberri P, Gómez M, Rodriguez-Mañas L, García F, Izquierdo M: Frailty assessment based on wavelet analysis during quiet standing balance test. J Biomech 2011;44:2213-2220.2171901610.1016/j.jbiomech.2011.06.007
Jorstad-Stein EC, Hauer K, Becker C, Bonnefoy M, Nakash RA, Skelton DA, Lamb SE: Suitability of physical activity questionnaires for older adults in fall-prevention trials: a systematic review. J Aging Phys Act 2005;13:461-481.16301756
Folstein MF, Folstein SE, McHugh PR: ‘Mini-mental state'. A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res 1975;12
24503059 - Exp Gerontol. 2014 Jun;54:6-13
19164276 - J Gerontol A Biol Sci Med Sci. 2009 Jan;64(1):61-8
20060313 - Crit Rev Oncol Hematol. 2010 Sep;75(3):243-8
21719016 - J Biomech. 2011 Aug 11;44(12):2213-20
20663438 - J Diabetes Sci Technol. 2010 Jul;4(4):780-91
11253156 - J Gerontol A Biol Sci Med Sci. 2001 Mar;56(3):M146-56
19615630 - J Pain Symptom Manage. 2009 Jul;38(1):75-80
9801527 - J Gerontol Nurs. 1998 Jul;24(7):18-27; quiz 54-5
21911876 - J Aging Phys Act. 2011 Oct;19(4):347-72
25171300 - Gerontology. 2014;60(6):483-92
20678816 - Arch Gerontol Geriatr. 2011 Jul-Aug;53(1):79-83
12148823 - IEEE Trans Biomed Eng. 2002 Aug;49(8):843-51
16301756 - J Aging Phys Act. 2005 Oct;13(4):461-81
2697808 - Neurobiol Aging. 1989 Nov-Dec;10(6):727-38
19682112 - J Am Geriatr Soc. 2009 Sep;57(9):1532-9
21357190 - J Gerontol A Biol Sci Med Sci. 2011 May;66(5):568-76
15699529 - J Gerontol A Biol Sci Med Sci. 2004 Dec;59(12):1295-303
1202204 - J Psychiatr Res. 1975 Nov;12(3):189-98
15103055 - Sci Aging Knowledge Environ. 2004 Apr 21;2004(16):pe16
15196517 - Gait Posture. 2004 Aug;20(1):30-5
16267188 - Age Ageing. 2005 Nov;34(6):614-9
17052879 - Exp Gerontol. 2006 Dec;41(12):1234-8
11955509 - J Biomech. 2002 May;35(5):689-99
22255829 - Conf Proc IEEE Eng Med Biol Soc. 2011;2011:6507-10
17383185 - Gait Posture. 2008 Jan;27(1):91-6
23949441 - Gerontology. 2014;60(1):79-89
24124940 - J Diabetes Sci Technol. 2013 Sep;7(5):1147-60
22882512 - Geriatr Gerontol Int. 2013 Apr;13(2):421-8
8914503 - J Gerontol A Biol Sci Med Sci. 1996 Nov;51(6):M303-12
748370 - J Chronic Dis. 1978;31(12):741-55
11844005 - J Am Geriatr Soc. 2001 Dec;49(12):1691-9
22209454 - Arch Gerontol Geriatr. 2012 May-Jun;54(3):e307-14
11227981 - Sports Med. 2001 Feb;31(2):91-100
9184689 - Phys Ther. 1997 Jun;77(6):646-60
17634318 - J Gerontol A Biol Sci Med Sci. 2007 Jul;62(7):722-7
22511289 - J Gerontol A Biol Sci Med Sci. 2013 Jan;68(1):62-7
23452001 - J Am Geriatr Soc. 2013 Mar;61(3):429-33
23002714 - J Am Geriatr Soc. 2012 Oct;60(10):1901-5
19093920 - J Am Geriatr Soc. 2008 Dec;56(12):2211-16
15591756 - Gerontology. 2005 Jan-Feb;51(1):48-52
20467494 - Cardiopulm Phys Ther J. 2008 Mar;19(1):17-22
12814238 - IEEE Trans Biomed Eng. 2003 Jun;50(6):711-23
20051607 - Age Ageing. 2010 May;39(3):382-5
21448557 - J Rehabil Med. 2011 Apr;43(5):424-9
14258950 - Md State Med J. 1965 Feb;14:61-5
18209234 - J Phys Act Health. 2007 Oct;4(4):434-46
18952435 - Gait Posture. 2009 Feb;29(2):261-6
ref13
ref35
ref12
ref34
ref15
ref37
ref14
ref36
ref31
ref30
ref11
ref33
ref10
ref32
ref2
ref1
ref17
ref39
ref16
ref38
ref19
ref18
ref24
ref23
ref26
ref25
ref20
ref22
ref21
ref28
ref27
ref29
ref8
ref7
ref9
ref4
ref3
ref6
ref5
ref40
References_xml – ident: ref22
  doi: 10.1159/000363136
– ident: ref10
  doi: 10.1046/j.1532-5415.2001.49281.x
– ident: ref37
  doi: 10.1016/0197-4580(89)90010-9
– ident: ref13
  doi: 10.1016/j.critrevonc.2009.12.002
– ident: ref39
  doi: 10.1093/gerona/gls119
– ident: ref31
  doi: 10.1177/193229681300700507
– ident: ref8
  doi: 10.1016/j.exger.2014.01.024
– ident: ref9
  doi: 10.1093/gerona/glr007
– ident: ref16
  doi: 10.1159/000081435
– ident: ref34
  doi: 10.1016/j.gaitpost.2007.02.005
– ident: ref14
  doi: 10.1177/193229681000400403
– ident: ref24
  doi: 10.1016/S0021-9290(02)00008-8
– ident: ref36
  doi: 10.1016/j.jbiomech.2011.06.007
– ident: ref29
  doi: 10.1016/0021-9681(78)90058-9
– ident: ref23
  doi: 10.1126/sageke.2004.16.pe16
– ident: ref35
  doi: 10.1016/j.gaitpost.2008.09.002
– ident: ref1
  doi: 10.1093/gerona/56.3.M146
– ident: ref11
  doi: 10.1159/000354211
– ident: ref27
  doi: 10.1111/jgs.12122
– ident: ref20
  doi: 10.1016/j.archger.2011.12.005
– ident: ref38
  doi: 10.2340/16501977-0791
– ident: ref30
  doi: 10.1109/TBME.2002.800763
– ident: ref19
  doi: 10.1093/gerona/gln001
– ident: ref25
  doi: 10.1109/IEMBS.2011.6091605
– ident: ref4
  doi: 10.1111/j.1532-5415.2009.02394.x
– ident: ref2
  doi: 10.1016/j.jpainsymman.2009.04.007
– ident: ref28
  doi: 10.1093/ageing/afi196
– ident: ref12
  doi: 10.1093/ageing/afp226
– ident: ref15
  doi: 10.1111/j.1532-5415.2008.02008.x
– ident: ref7
  doi: 10.1016/j.archger.2010.06.013
– ident: ref6
  doi: 10.2165/00007256-200131020-00002
– ident: ref32
  doi: 10.1093/gerona/51A.6.M303
– ident: ref17
  doi: 10.1016/S0966-6362(03)00089-4
– ident: ref3
  doi: 10.1111/j.1447-0594.2012.00920.x
– ident: ref33
  doi: 10.1016/j.exger.2006.08.011
– ident: ref40
  doi: 10.1093/gerona/62.7.722
– ident: ref5
  doi: 10.1093/gerona/59.12.1295
– ident: ref26
  doi: 10.1016/0022-3956(75)90026-6
– ident: ref18
  doi: 10.1111/j.1532-5415.2012.04145.x
– ident: ref21
  doi: 10.1109/TBME.2003.812189
SSID ssj0030210
Score 2.5133195
Snippet Background: Frailty is a geriatric syndrome resulting from age-related cumulative decline across multiple physiologic systems, impaired homeostatic reserve,...
Frailty is a geriatric syndrome resulting from age-related cumulative decline across multiple physiologic systems, impaired homeostatic reserve, and reduced...
BACKGROUNDFrailty is a geriatric syndrome resulting from age-related cumulative decline across multiple physiologic systems, impaired homeostatic reserve, and...
SourceID pubmedcentral
proquest
gale
crossref
pubmed
karger
SourceType Open Access Repository
Aggregation Database
Index Database
Publisher
StartPage 258
SubjectTerms Activity trackers
Aged
Aged, 80 and over
Aging - physiology
Arizona
Biosensors
Cohort Studies
Cross-Sectional Studies
Female
Frail Elderly
Frailty
Gait
Geriatric assessment
Geriatric Assessment - methods
Geriatric Assessment - statistics & numerical data
Geriatrics
Health aspects
Humans
Male
Medical examination
Methods
Motor Activity
Older people
Physiological aspects
Postural Balance
Posture
Regenerative and Technological Section / Original Paper
Sensors
Technology application
Walking
Title Wearable Sensor-Based In-Home Assessment of Gait, Balance, and Physical Activity for Discrimination of Frailty Status: Baseline Results of the Arizona Frailty Cohort Study
URI https://karger.com/doi/10.1159/000369095
https://www.ncbi.nlm.nih.gov/pubmed/25547185
https://www.proquest.com/docview/1689661278
https://search.proquest.com/docview/1677885009
https://search.proquest.com/docview/1897374760
https://pubmed.ncbi.nlm.nih.gov/PMC4452118
Volume 61
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
link http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwfV3Nb9MwFLfYhhAXBN0YhVIMQpxmLYljO-GC2rIxkDahwbTeIjtxtWglGU16GP8S_yTvxUnYEJp6i19qR34fv2e_D0LeWhgItLJMgjVmIWhAZrLYMk-YmIciUEFTSPv4RB6dhV_mYt4euFVtWGWnExtFnZUpnpHv-zICZO4HKvpw9ZNh1yi8XW1baGyQLR8NHWaKz_oQD47-jLtFCBkAh3lbWQgs-H5TiCX2sK3EDXvUauX7lxiFvfof6Pw3dvKGMTp8TB61KJJO3LY_IfdsMSDbkwI86B_X9B1t4jqbA_MBeXDcXp8PyMgl49Jzu1zolQXC7kG5utwmv8-B7TGVin4D57ZcsSmYuIx-Lhg2U6eTvognLRf0k87rPTrFyMjU7lFdZG7WFNeVup4UFBAx_ZijZsKIG-QBfBXAcr6EUQS66-o9xWkQ7dJTW62XdYU0gEvh8_Jf4Cj09LPyApwFiqGP1zvk7PDg--yItc0cWCqDsGa-9rS0aWCjOFJKY45RpvzQ19xKoQym7AqluDZWS-UBv0Qi1JwvgiDSqTA-f0o2i7KwzwiNBc9EqDw_MkGYag4_Y3yrA86NtJk3JG-6LU2uXM2OpPF1RJz0-z4kr3CzE5du2st5MpFN3x6AMkOy4_ig_5PuzVHHFkkr8FXylz2H5HU_DKKK9y-6sOUaaZSKIgGo9g6aKFYcXDwJX7HrOK2fHrw_hBKwAHWLB3sCLBV-e6TIL5qS4SGIHbiSz-9e-gvyEPCgcIFJI7JZr9b2JWCu2ozJhpqrcSNeY7I1PTj5evoHI08tMg
link.rule.ids 230,314,780,784,885,12056,12223,21388,27924,27925,31719,31720,33266,33267,33744,33745,43310,43579,43805,73745,74014,74302
linkProvider ProQuest
linkToHtml http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwfV1bb9MwFLagQ8ALgm5AoTCDEE-zlsR2nPCC2rHRwVqhsWl9i-zE1aKVZKTpw_hL_EnOyY0Noalv8UntyOfyHftcCHlnYcDTyjIfrDEToAGZSULLHGlCLqSnvKqQ9nTmT07Fl7mcNwduqyasstWJlaJO8hjPyHddPwBk7noq-Hj5k2HXKLxdbVpo3CUbWDld9sjGeH_27bjVxRw9mvoeQTCADvOmthDY8N2qFEvoYGOJaxap0cv3LjAOu_gf7Pw3evKaOTp4TB41OJKO6o1_Qu7YrE82Rxn40D-u6HtaRXZWR-Z9cn_aXKD3ybBOx6VndrnQhQXC9kFeXGyS32fA-JhMRb-De5sXbAxGLqGHGcN26nTUlfGk-YJ-1mm5Q8cYGxnbHaqzpJ41xnXFdVcKCpiYfkpRN2HMDXIBvgpwOV3CKELd9eoDxWkQ79Jju1ovyxXSADKFz0t_gavQ0e_l5-AuUAx-vNoipwf7J3sT1rRzYLHviZK52tG-jT0bhIFSGrOMEuUKV3PrS2UwaVcqxbWx2lcOcEwgheZ84XmBjqVx-VPSy_LMPic0lDyRQjluYDwRaw4_Y1yrPc6NbxNnQN62Wxpd1lU7osrbkWHU7fuAbONmR3XCaSfp0civOvcAmBmQrZoPuj9p3xy2bBE1Ir-K_jLogLzphkFY8QZGZzZfI41SQSAB195CE4SKg5Pnw1c8qzmtmx78PwQTsAB1gwc7AiwWfnMkS8-rouECBA-cyRe3L32bPJicTI-io8PZ15fkIaBDWYcpDUmvLNb2FSCw0rxuxOwPZNQvPw
linkToPdf http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwfV3Nb9MwFLegQxMXBN2AQmEGIU6zmthxnHBB7bayAaumwbTeIidxtWglGUl7GP8S_yTvJU7YEJpyi19iR34fvxe_D0LeGRjgWhnmgzVmHmhAFqehYY6MQ-FJrnhdSPt45h-eeZ_ncm7jnyobVtnqxFpRp0WC_8hHrh8AMne5CkYLGxZxsj_9ePWTYQcpPGm17TTukw2wig7vkY3JwezktNXLAr2b5kzBYwAj5rbOENjzUV2WJXSwycQN62R19INLjMku_wdB_42kvGGapo_JI4sp6bhhgifknsn7ZGucgz_945q-p3WUZ_37vE82j-1hep8Mm9Rcem6WC10aIGxvFOXlFvl9DkKAiVX0G7i6RckmYPBSepQzbK1Ox11JT1os6CedrXbpBOMkE7NLdZ42sya4rqTpUEEBH9P9DPUUxt8gR-CjAJ2zJYwi7F1XHyhOg9iXnppqvVxVSAMoFT4v-wVuQ0e_V1yA60AxEPJ6m5xND77vHTLb2oElPvdWzNWO9k3CTRAGSmnMOEqV67laGF-qGBN4pVJCx0b7ygHuCaSnhVhwHuhExq54Snp5kZvnhIZSpNJTjhvE3Eu0gCuOXaO5ELFvUmdA3rZbGl01FTyi2vORYdTt-4Ds4GZHTfJpJ_XR2K-7-ACwGZDthg-6l7RPDlu2iKz4V9FfZh2QN90wCC6exujcFGukUSoIJGDcO2iCUAlw-Hz4imcNp3XTgy-IwAIWoG7xYEeAhcNvj-TZRV1A3AMhBMfyxd1L3yGbIGHR16PZl5fkIQBF2UQsDUlvVa7NKwBjq_i1lbI_nsUzbA
openUrl ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Wearable+sensor-based+in-home+assessment+of+gait%2C+balance%2C+and+physical+activity+for+discrimination+of+frailty+status%3A+baseline+results+of+the+Arizona+frailty+cohort+study&rft.jtitle=Gerontology+%28Basel%29&rft.au=Schwenk%2C+Michael&rft.au=Mohler%2C+Jane&rft.au=Wendel%2C+Christopher&rft.au=D%27Huyvetter%2C+Karen&rft.date=2015-04-01&rft.eissn=1423-0003&rft.volume=61&rft.issue=3&rft.spage=258&rft.epage=267&rft_id=info:doi/10.1159%2F000369095&rft.externalDBID=NO_FULL_TEXT
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0304-324X&client=summon
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0304-324X&client=summon
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0304-324X&client=summon