Inertial Sensor Algorithm to Estimate Walk Distance
The “total distance walked” obtained during a standardized walking test is an integral component of physical fitness and health status tracking in a range of consumer and clinical applications. Wearable inertial sensors offer the advantages of providing accurate, objective, and reliable measures of...
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| Abstract | The “total distance walked” obtained during a standardized walking test is an integral component of physical fitness and health status tracking in a range of consumer and clinical applications. Wearable inertial sensors offer the advantages of providing accurate, objective, and reliable measures of gait while streamlining walk test administration. The aim of this study was to develop an inertial sensor-based algorithm to estimate the total distance walked using older subjects with impaired fasting glucose (Study I), and to test the generalizability of the proposed algorithm in patients with Multiple Sclerosis (Study II). All subjects wore two inertial sensors (Opals by Clario-APDM Wearable Technologies) on their feet. The walking distance algorithm was developed based on 108 older adults in Study I performing a 400 m walk test along a 20 m straight walkway. The validity of the algorithm was tested using a 6-minute walk test (6MWT) in two sub-studies of Study II with different lengths of a walkway, 15 m (Study II-A, n = 24) and 20 m (Study II-B, n = 22), respectively. The start and turn around points were marked with lines on the floor while smaller horizontal lines placed every 1 m served to calculate the manual distance walked (ground truth). The proposed algorithm calculates the forward distance traveled during each step as the change in the horizontal position from each foot-flat period to the subsequent foot-flat period. The total distance walked is then computed as the sum of walk distances for each stride, including turns. The proposed algorithm achieved an average absolute error rate of 1.92% with respect to a fixed 400 m distance for Study I. The same algorithm achieved an absolute error rate of 4.17% and 3.21% with respect to an averaged manual distance for 6MWT in Study II-A and Study II-B, respectively. These results demonstrate the potential of an inertial sensor-based algorithm to estimate a total distance walked with good accuracy with respect to the manual, clinical standard. Further work is needed to test the generalizability of the proposed algorithm with different administrators and populations, as well as larger diverse cohorts. |
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| AbstractList | The "total distance walked" obtained during a standardized walking test is an integral component of physical fitness and health status tracking in a range of consumer and clinical applications. Wearable inertial sensors offer the advantages of providing accurate, objective, and reliable measures of gait while streamlining walk test administration. The aim of this study was to develop an inertial sensor-based algorithm to estimate the total distance walked using older subjects with impaired fasting glucose (Study I), and to test the generalizability of the proposed algorithm in patients with Multiple Sclerosis (Study II). All subjects wore two inertial sensors (Opals by Clario-APDM Wearable Technologies) on their feet. The walking distance algorithm was developed based on 108 older adults in Study I performing a 400 m walk test along a 20 m straight walkway. The validity of the algorithm was tested using a 6-minute walk test (6MWT) in two sub-studies of Study II with different lengths of a walkway, 15 m (Study II-A,
= 24) and 20 m (Study II-B,
= 22), respectively. The start and turn around points were marked with lines on the floor while smaller horizontal lines placed every 1 m served to calculate the manual distance walked (ground truth). The proposed algorithm calculates the forward distance traveled during each step as the change in the horizontal position from each foot-flat period to the subsequent foot-flat period. The total distance walked is then computed as the sum of walk distances for each stride, including turns. The proposed algorithm achieved an average absolute error rate of 1.92% with respect to a fixed 400 m distance for Study I. The same algorithm achieved an absolute error rate of 4.17% and 3.21% with respect to an averaged manual distance for 6MWT in Study II-A and Study II-B, respectively. These results demonstrate the potential of an inertial sensor-based algorithm to estimate a total distance walked with good accuracy with respect to the manual, clinical standard. Further work is needed to test the generalizability of the proposed algorithm with different administrators and populations, as well as larger diverse cohorts. The “total distance walked” obtained during a standardized walking test is an integral component of physical fitness and health status tracking in a range of consumer and clinical applications. Wearable inertial sensors offer the advantages of providing accurate, objective, and reliable measures of gait while streamlining walk test administration. The aim of this study was to develop an inertial sensor-based algorithm to estimate the total distance walked using older subjects with impaired fasting glucose (Study I), and to test the generalizability of the proposed algorithm in patients with Multiple Sclerosis (Study II). All subjects wore two inertial sensors (Opals by Clario-APDM Wearable Technologies) on their feet. The walking distance algorithm was developed based on 108 older adults in Study I performing a 400 m walk test along a 20 m straight walkway. The validity of the algorithm was tested using a 6-minute walk test (6MWT) in two sub-studies of Study II with different lengths of a walkway, 15 m (Study II-A, n = 24) and 20 m (Study II-B, n = 22), respectively. The start and turn around points were marked with lines on the floor while smaller horizontal lines placed every 1 m served to calculate the manual distance walked (ground truth). The proposed algorithm calculates the forward distance traveled during each step as the change in the horizontal position from each foot-flat period to the subsequent foot-flat period. The total distance walked is then computed as the sum of walk distances for each stride, including turns. The proposed algorithm achieved an average absolute error rate of 1.92% with respect to a fixed 400 m distance for Study I. The same algorithm achieved an absolute error rate of 4.17% and 3.21% with respect to an averaged manual distance for 6MWT in Study II-A and Study II-B, respectively. These results demonstrate the potential of an inertial sensor-based algorithm to estimate a total distance walked with good accuracy with respect to the manual, clinical standard. Further work is needed to test the generalizability of the proposed algorithm with different administrators and populations, as well as larger diverse cohorts. The "total distance walked" obtained during a standardized walking test is an integral component of physical fitness and health status tracking in a range of consumer and clinical applications. Wearable inertial sensors offer the advantages of providing accurate, objective, and reliable measures of gait while streamlining walk test administration. The aim of this study was to develop an inertial sensor-based algorithm to estimate the total distance walked using older subjects with impaired fasting glucose (Study I), and to test the generalizability of the proposed algorithm in patients with Multiple Sclerosis (Study II). All subjects wore two inertial sensors (Opals by Clario-APDM Wearable Technologies) on their feet. The walking distance algorithm was developed based on 108 older adults in Study I performing a 400 m walk test along a 20 m straight walkway. The validity of the algorithm was tested using a 6-minute walk test (6MWT) in two sub-studies of Study II with different lengths of a walkway, 15 m (Study II-A, n = 24) and 20 m (Study II-B, n = 22), respectively. The start and turn around points were marked with lines on the floor while smaller horizontal lines placed every 1 m served to calculate the manual distance walked (ground truth). The proposed algorithm calculates the forward distance traveled during each step as the change in the horizontal position from each foot-flat period to the subsequent foot-flat period. The total distance walked is then computed as the sum of walk distances for each stride, including turns. The proposed algorithm achieved an average absolute error rate of 1.92% with respect to a fixed 400 m distance for Study I. The same algorithm achieved an absolute error rate of 4.17% and 3.21% with respect to an averaged manual distance for 6MWT in Study II-A and Study II-B, respectively. These results demonstrate the potential of an inertial sensor-based algorithm to estimate a total distance walked with good accuracy with respect to the manual, clinical standard. Further work is needed to test the generalizability of the proposed algorithm with different administrators and populations, as well as larger diverse cohorts.The "total distance walked" obtained during a standardized walking test is an integral component of physical fitness and health status tracking in a range of consumer and clinical applications. Wearable inertial sensors offer the advantages of providing accurate, objective, and reliable measures of gait while streamlining walk test administration. The aim of this study was to develop an inertial sensor-based algorithm to estimate the total distance walked using older subjects with impaired fasting glucose (Study I), and to test the generalizability of the proposed algorithm in patients with Multiple Sclerosis (Study II). All subjects wore two inertial sensors (Opals by Clario-APDM Wearable Technologies) on their feet. The walking distance algorithm was developed based on 108 older adults in Study I performing a 400 m walk test along a 20 m straight walkway. The validity of the algorithm was tested using a 6-minute walk test (6MWT) in two sub-studies of Study II with different lengths of a walkway, 15 m (Study II-A, n = 24) and 20 m (Study II-B, n = 22), respectively. The start and turn around points were marked with lines on the floor while smaller horizontal lines placed every 1 m served to calculate the manual distance walked (ground truth). The proposed algorithm calculates the forward distance traveled during each step as the change in the horizontal position from each foot-flat period to the subsequent foot-flat period. The total distance walked is then computed as the sum of walk distances for each stride, including turns. The proposed algorithm achieved an average absolute error rate of 1.92% with respect to a fixed 400 m distance for Study I. The same algorithm achieved an absolute error rate of 4.17% and 3.21% with respect to an averaged manual distance for 6MWT in Study II-A and Study II-B, respectively. These results demonstrate the potential of an inertial sensor-based algorithm to estimate a total distance walked with good accuracy with respect to the manual, clinical standard. Further work is needed to test the generalizability of the proposed algorithm with different administrators and populations, as well as larger diverse cohorts. |
| Author | Shah, Vrutangkumar V. Curtze, Carolin Sowalsky, Kristen Mancini, Martina Carlson-Kuhta, Patricia Horak, Fay B. Arpan, Ishu El-Gohary, Mahmoud McNames, James |
| AuthorAffiliation | 2 Department of Biomechanics, University of Nebraska at Omaha, 6001 Dodge St., Omaha, NE 68182, USA; ccurtze@unomaha.edu 4 Department of Electrical and Computer Engineering, Portland State University, 1825 SW Broadway, Portland, OR 97201, USA 1 Department of Neurology, Oregon Health & Science University, 3181 SW Sam Jackson Park Road, Portland, OR 97239, USA; arpan@ohsu.edu (I.A.); mancinim@ohsu.edu (M.M.); carlsonp@ohsu.edu (P.C.-K.); horakf@ohsu.edu (F.B.H.) 3 APDM Wearable Technologie—A Clario Company, 2828 S Corbett Ave, Ste 135, Portland, OR 97201, USA; kristen.sowalsky@ert.com (K.S.); mahmoud.el-gohary@ert.com (M.E.-G.); james.mcnames@ert.com (J.M.) |
| AuthorAffiliation_xml | – name: 4 Department of Electrical and Computer Engineering, Portland State University, 1825 SW Broadway, Portland, OR 97201, USA – name: 2 Department of Biomechanics, University of Nebraska at Omaha, 6001 Dodge St., Omaha, NE 68182, USA; ccurtze@unomaha.edu – name: 3 APDM Wearable Technologie—A Clario Company, 2828 S Corbett Ave, Ste 135, Portland, OR 97201, USA; kristen.sowalsky@ert.com (K.S.); mahmoud.el-gohary@ert.com (M.E.-G.); james.mcnames@ert.com (J.M.) – name: 1 Department of Neurology, Oregon Health & Science University, 3181 SW Sam Jackson Park Road, Portland, OR 97239, USA; arpan@ohsu.edu (I.A.); mancinim@ohsu.edu (M.M.); carlsonp@ohsu.edu (P.C.-K.); horakf@ohsu.edu (F.B.H.) |
| Author_xml | – sequence: 1 givenname: Vrutangkumar V. surname: Shah fullname: Shah, Vrutangkumar V. – sequence: 2 givenname: Carolin orcidid: 0000-0001-5394-4628 surname: Curtze fullname: Curtze, Carolin – sequence: 3 givenname: Kristen surname: Sowalsky fullname: Sowalsky, Kristen – sequence: 4 givenname: Ishu surname: Arpan fullname: Arpan, Ishu – sequence: 5 givenname: Martina surname: Mancini fullname: Mancini, Martina – sequence: 6 givenname: Patricia orcidid: 0000-0002-5794-4155 surname: Carlson-Kuhta fullname: Carlson-Kuhta, Patricia – sequence: 7 givenname: Mahmoud surname: El-Gohary fullname: El-Gohary, Mahmoud – sequence: 8 givenname: Fay B. orcidid: 0000-0001-7704-5459 surname: Horak fullname: Horak, Fay B. – sequence: 9 givenname: James surname: McNames fullname: McNames, James |
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| CitedBy_id | crossref_primary_10_1016_j_gaitpost_2024_01_030 crossref_primary_10_3390_s24082632 crossref_primary_10_1016_j_jbiomech_2023_111907 crossref_primary_10_1186_s12984_024_01409_7 crossref_primary_10_1080_14796678_2025_2457881 crossref_primary_10_3390_s23084091 crossref_primary_10_3390_s24051480 crossref_primary_10_1016_j_heliyon_2023_e17854 crossref_primary_10_2196_44428 |
| Cites_doi | 10.2196/13756 10.1109/MeMeA49120.2020.9137305 10.1002/mds.26718 10.1586/17434440.2016.1153421 10.1183/09031936.00071506 10.1111/j.1532-5415.2006.00701.x 10.1016/S1474-4422(19)30397-7 10.1016/S0140-6736(86)90837-8 10.1186/s12984-015-0013-9 10.1007/s00415-020-09696-5 10.1557/s43577-021-00123-2 10.1093/eurheartj/ehi162 10.1016/j.gaitpost.2016.04.025 10.1109/TBME.2006.875664 10.3810/psm.2011.05.1904 10.1093/qjmed/hch084 10.1519/00139143-200932020-00002 10.1038/s41746-020-0299-2 10.1164/ajrccm.158.5.9710086 10.1212/WNL.43.2.268 10.1164/ajrccm.166.1.at1102 10.1038/s41746-018-0073-x 10.1109/MCG.2005.140 10.1109/MPRV.2012.16 10.1089/tmj.2014.0025 10.1088/1361-6579/ab4023 10.3390/s20092660 10.1016/S1474-4422(06)70678-0 10.2196/10527 10.1109/JBHI.2015.2427511 10.1001/jamaneurol.2018.0809 10.1249/01.MSS.0000089342.96098.C4 10.1136/thx.39.11.818 10.1177/1352458507082607 10.1037/0033-2909.86.2.420 10.1016/j.jsams.2013.10.241 10.1249/01.MSS.0000078932.61440.A2 10.1016/j.gaitpost.2017.04.013 10.1161/CIRCHEARTFAILURE.115.002062 10.1136/bmj.284.6329.1607 10.1016/j.jdiacomp.2015.10.006 10.1016/j.amjmed.2017.11.051 10.1183/09031936.00150314 |
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| References | Washabaugh (ref_38) 2017; 55 Nutt (ref_1) 1993; 43 Takacs (ref_29) 2014; 17 Burr (ref_7) 2011; 39 Sabatini (ref_41) 2006; 53 Juen (ref_34) 2015; 19 Zhan (ref_22) 2018; 75 Bland (ref_46) 1986; 327 Juen (ref_35) 2014; 20 Shrout (ref_47) 1979; 86 Maksimovic (ref_36) 2015; 30 Olsson (ref_6) 2005; 26 Casanova (ref_11) 2007; 29 Schneider (ref_30) 2003; 35 Guyatt (ref_10) 1984; 39 Godfrey (ref_18) 2016; 31 Butland (ref_14) 1982; 284 Schubert (ref_26) 2020; 3 Feehan (ref_32) 2018; 6 Crouter (ref_31) 2003; 35 Fritz (ref_4) 2009; 32 Pearson (ref_16) 2004; 97 Ata (ref_33) 2018; 1 Holland (ref_8) 2014; 44 ref_23 ref_45 ref_44 Warmerdam (ref_15) 2020; 19 Fischer (ref_42) 2013; 12 ref_43 Capela (ref_25) 2015; 12 Salvi (ref_27) 2020; 8 Huang (ref_24) 2016; 48 Snijders (ref_2) 2007; 6 Mancini (ref_17) 2016; 13 Yang (ref_20) 2021; 12 Goldman (ref_37) 2008; 14 Perera (ref_12) 2006; 54 Shah (ref_19) 2020; 267 Baker (ref_3) 2018; 131 Foxlin (ref_40) 2005; 25 Dong (ref_21) 2021; 46 ref_5 Guyatt (ref_13) 1985; 132 Brooks (ref_28) 2015; 8 Enright (ref_9) 1998; 158 Morris (ref_39) 2019; 40 |
| References_xml | – volume: 8 start-page: e13756 year: 2020 ident: ref_27 article-title: The mobile-based 6-minute walk test: Usability study and algorithm development and validation publication-title: JMIR mHealth uHealth doi: 10.2196/13756 – ident: ref_45 doi: 10.1109/MeMeA49120.2020.9137305 – volume: 31 start-page: 1293 year: 2016 ident: ref_18 article-title: Free-living monitoring of Parkinson’s disease: Lessons from the field publication-title: Mov. Disord. doi: 10.1002/mds.26718 – volume: 13 start-page: 455 year: 2016 ident: ref_17 article-title: Potential of APDM mobility lab for the monitoring of the progression of Parkinson’s disease publication-title: Expert Rev. Med. Devices doi: 10.1586/17434440.2016.1153421 – volume: 29 start-page: 535 year: 2007 ident: ref_11 article-title: The 6-min walking distance: Long term follow up in patients with COPD publication-title: Eur. Respir. J. doi: 10.1183/09031936.00071506 – volume: 54 start-page: 743 year: 2006 ident: ref_12 article-title: Meaningful change and responsiveness in common physical performance measures in older adults publication-title: J. Am. Geriatr. Soc. doi: 10.1111/j.1532-5415.2006.00701.x – volume: 19 start-page: 462 year: 2020 ident: ref_15 article-title: Long-term unsupervised mobility assessment in movement disorders publication-title: Lancet Neurol. doi: 10.1016/S1474-4422(19)30397-7 – volume: 327 start-page: 307 year: 1986 ident: ref_46 article-title: Statistical methods for assessing agreement between two methods of clinical measurement publication-title: Lancet doi: 10.1016/S0140-6736(86)90837-8 – volume: 12 start-page: 19 year: 2015 ident: ref_25 article-title: Novel algorithm for a smartphone-based 6-minute walk test application: Algorithm, application development, and evaluation publication-title: J. Neuroeng. Rehabil. doi: 10.1186/s12984-015-0013-9 – volume: 267 start-page: 1188 year: 2020 ident: ref_19 article-title: Quantity and quality of gait and turning in people with multiple sclerosis, Parkinson’s disease and matched controls during daily living publication-title: J. Neurol. doi: 10.1007/s00415-020-09696-5 – volume: 46 start-page: 512 year: 2021 ident: ref_21 article-title: Smart textile triboelectric nanogenerators: Current status and perspectives publication-title: MRS Bull. doi: 10.1557/s43577-021-00123-2 – volume: 26 start-page: 778 year: 2005 ident: ref_6 article-title: Six minute corridor walk test as an outcome measure for the assessment of treatment in randomized, blinded intervention trials of chronic heart failure: A systematic review publication-title: Eur. Heart J. doi: 10.1093/eurheartj/ehi162 – volume: 48 start-page: 36 year: 2016 ident: ref_24 article-title: Validity of FitBit, Jawbone UP, Nike+ and other wearable devices for level and stair walking publication-title: Gait Posture doi: 10.1016/j.gaitpost.2016.04.025 – volume: 53 start-page: 1346 year: 2006 ident: ref_41 article-title: Quaternion-based extended Kalman filter for determining orientation by inertial and magnetic sensing publication-title: IEEE Trans. Biomed. Eng. doi: 10.1109/TBME.2006.875664 – volume: 39 start-page: 133 year: 2011 ident: ref_7 article-title: The 6-min walk test as a predictor of objectively measured aerobic fitness in healthy working-aged adults publication-title: Phys. Sportsmed. doi: 10.3810/psm.2011.05.1904 – volume: 97 start-page: 463 year: 2004 ident: ref_16 article-title: Quantification of walking mobility in neurological disorders publication-title: QJM doi: 10.1093/qjmed/hch084 – ident: ref_44 – volume: 32 start-page: 2 year: 2009 ident: ref_4 article-title: White Paper: “Walking Speed: The Sixth Vital Sign” publication-title: J. Geriatr. Phys. Ther. doi: 10.1519/00139143-200932020-00002 – volume: 3 start-page: 92 year: 2020 ident: ref_26 article-title: Wearable devices can predict the outcome of standardized 6-minute walk tests in heart disease publication-title: NPJ Digit. Med. doi: 10.1038/s41746-020-0299-2 – volume: 158 start-page: 1384 year: 1998 ident: ref_9 article-title: Reference equations for the six-minute walk in healthy adults publication-title: Am. J. Respir. Crit. Care Med. doi: 10.1164/ajrccm.158.5.9710086 – volume: 43 start-page: 268 year: 1993 ident: ref_1 article-title: Human walking and higher-level gait disorders, particularly in the elderly publication-title: Neurology doi: 10.1212/WNL.43.2.268 – ident: ref_5 doi: 10.1164/ajrccm.166.1.at1102 – volume: 1 start-page: 66 year: 2018 ident: ref_33 article-title: Clinical validation of smartphone-based activity tracking in peripheral artery disease patients publication-title: NPJ Digit. Med. doi: 10.1038/s41746-018-0073-x – volume: 25 start-page: 38 year: 2005 ident: ref_40 article-title: Pedestrian tracking with shoe-mounted inertial sensors publication-title: IEEE Comput. Graph. Appl. doi: 10.1109/MCG.2005.140 – volume: 12 start-page: 17 year: 2013 ident: ref_42 article-title: Tutorial: Implementing a pedestrian tracker using inertial sensors publication-title: IEEE Pervasive Comput. doi: 10.1109/MPRV.2012.16 – volume: 20 start-page: 1035 year: 2014 ident: ref_35 article-title: Health monitors for chronic disease by gait analysis with mobile phones publication-title: Telemed. E-Health doi: 10.1089/tmj.2014.0025 – volume: 40 start-page: 095003 year: 2019 ident: ref_39 article-title: Validity of Mobility Lab (version 2) for gait assessment in young adults, older adults and Parkinson’s disease publication-title: Physiol. Meas. doi: 10.1088/1361-6579/ab4023 – ident: ref_23 doi: 10.3390/s20092660 – volume: 6 start-page: 63 year: 2007 ident: ref_2 article-title: Neurological gait disorders in elderly people: Clinical approach and classification publication-title: Lancet Neurol. doi: 10.1016/S1474-4422(06)70678-0 – volume: 132 start-page: 919 year: 1985 ident: ref_13 article-title: The 6-min walk: A new measure of exercise capacity in patients with chronic heart failure sur sa capacite dans les activites de la vie quotidienne. colleagues’0 introduced the 12-min walking test, in publication-title: Can. Med. Assoc. J. – volume: 6 start-page: e10527 year: 2018 ident: ref_32 article-title: Accuracy of Fitbit Devices: Systematic Review and Narrative Syntheses of Quantitative Data publication-title: JMIR mHealth uHealth doi: 10.2196/10527 – volume: 19 start-page: 1399 year: 2015 ident: ref_34 article-title: A Natural Walking Monitor for Pulmonary Patients Using Mobile Phones publication-title: IEEE J. Biomed. Health Inform. doi: 10.1109/JBHI.2015.2427511 – volume: 75 start-page: 876 year: 2018 ident: ref_22 article-title: Using smartphones and machine learning to quantify Parkinson disease severity the mobile Parkinson disease score publication-title: JAMA Neurol. doi: 10.1001/jamaneurol.2018.0809 – volume: 35 start-page: 1779 year: 2003 ident: ref_30 article-title: Accuracy and reliability of 10 pedometers for measuring steps over a 400-m walk publication-title: Med. Sci. Sports Exerc. doi: 10.1249/01.MSS.0000089342.96098.C4 – volume: 39 start-page: 818 year: 1984 ident: ref_10 article-title: Effect of encouragement on walking test performance publication-title: Thorax doi: 10.1136/thx.39.11.818 – volume: 14 start-page: 383 year: 2008 ident: ref_37 article-title: Evaluation of the six-minute walk in multiple sclerosis subjects and healthy controls publication-title: Mult. Scler. J. doi: 10.1177/1352458507082607 – volume: 86 start-page: 420 year: 1979 ident: ref_47 article-title: Intraclass Correlations: Uses in Assessing Rater Reliability publication-title: Psychol. Bull. doi: 10.1037/0033-2909.86.2.420 – volume: 12 start-page: 1 year: 2021 ident: ref_20 article-title: A non-printed integrated-circuit textile for wireless theranostics publication-title: Nat. Commun. – volume: 17 start-page: 496 year: 2014 ident: ref_29 article-title: Validation of the Fitbit One activity monitor device during treadmill walking publication-title: J. Sci. Med. Sport doi: 10.1016/j.jsams.2013.10.241 – volume: 35 start-page: 1455 year: 2003 ident: ref_31 article-title: Validity of 10 electronic pedometers for measuring steps, distance, and energy cost publication-title: Med. Sci. Sports Exerc. doi: 10.1249/01.MSS.0000078932.61440.A2 – volume: 55 start-page: 87 year: 2017 ident: ref_38 article-title: Validity and repeatability of inertial measurement units for measuring gait parameters publication-title: Gait Posture doi: 10.1016/j.gaitpost.2017.04.013 – volume: 8 start-page: 905 year: 2015 ident: ref_28 article-title: Accuracy and Usability of a Self-Administered 6-Min Walk Test Smartphone Application publication-title: Circ. Heart Fail. doi: 10.1161/CIRCHEARTFAILURE.115.002062 – ident: ref_43 – volume: 284 start-page: 1607 year: 1982 ident: ref_14 article-title: Two-, six-, and 12-min walking tests in respiratory disease publication-title: Br. Med. J. doi: 10.1136/bmj.284.6329.1607 – volume: 30 start-page: 61 year: 2015 ident: ref_36 article-title: Gait characteristics in older adults with diabetes and impaired fasting glucose: The Rotterdam Study publication-title: J. Diabetes Its Complicat. doi: 10.1016/j.jdiacomp.2015.10.006 – volume: 131 start-page: 602 year: 2018 ident: ref_3 article-title: Gait Disorders publication-title: Am. J. Med. doi: 10.1016/j.amjmed.2017.11.051 – volume: 44 start-page: 1428 year: 2014 ident: ref_8 article-title: An official European respiratory society/American thoracic society technical standard: Field walking tests in chronic respiratory disease publication-title: Eur. Respir. J. doi: 10.1183/09031936.00150314 |
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| SubjectTerms | 400 m walk test 6MWD 6MWT Aged Algorithms Clinical trials Consent Data collection Datasets Diabetes Disease Fasting Foot Gait Glucose Heart failure Humans inertial sensors Multiple sclerosis Neurological disorders Older people Sensors Walk Test Walking Walkways |
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| Title | Inertial Sensor Algorithm to Estimate Walk Distance |
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