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Items: 1 to 20 of 122

1.

Thigh-Derived Inertial Sensor Metrics to Assess the Sit-to-Stand and Stand-to-Sit Transitions in the Timed Up and Go (TUG) Task for Quantifying Mobility Impairment in Multiple Sclerosis.

Witchel HJ, Oberndorfer C, Needham R, Healy A, Westling CEI, Guppy JH, Bush J, Barth J, Herberz C, Roggen D, Eskofier BM, Rashid W, Chockalingam N, Klucken J.

Front Neurol. 2018 Sep 14;9:684. doi: 10.3389/fneur.2018.00684. eCollection 2018.

2.
3.

Instrumented balance and walking assessments in persons with multiple sclerosis show strong test-retest reliability.

Craig JJ, Bruetsch AP, Lynch SG, Horak FB, Huisinga JM.

J Neuroeng Rehabil. 2017 May 22;14(1):43. doi: 10.1186/s12984-017-0251-0.

4.

Evaluation of an inertial sensor system for analysis of timed-up-and-go under dual-task demands.

Coulthard JT, Treen TT, Oates AR, Lanovaz JL.

Gait Posture. 2015 May;41(4):882-7. doi: 10.1016/j.gaitpost.2015.03.009. Epub 2015 Mar 21.

PMID:
25827680
5.

Convergent Validity of a Wearable Sensor System for Measuring Sub-Task Performance during the Timed Up-and-Go Test.

Beyea J, McGibbon CA, Sexton A, Noble J, O'Connell C.

Sensors (Basel). 2017 Apr 23;17(4). pii: E934. doi: 10.3390/s17040934.

6.

Transition Between the Timed up and Go Turn to Sit Subtasks: Is Timing Everything?

Weiss A, Mirelman A, Giladi N, Barnes LL, Bennett DA, Buchman AS, Hausdorff JM.

J Am Med Dir Assoc. 2016 Sep 1;17(9):864.e9-864.e15. doi: 10.1016/j.jamda.2016.06.025.

7.

The contribution of the instrumented Timed-Up-and-Go test to detect falls and fear of falling in people with multiple sclerosis.

Hershkovitz L, Malcay O, Grinberg Y, Berkowitz S, Kalron A.

Mult Scler Relat Disord. 2019 Jan;27:226-231. doi: 10.1016/j.msard.2018.10.111. Epub 2018 Oct 27.

PMID:
30415024
8.

Reliability of the sub-components of the instrumented timed up and go test in ambulatory children with traumatic brain injury and typically developed controls.

Newman MA, Hirsch MA, Peindl RD, Habet NA, Tsai TJ, Runyon MS, Huynh T, Zheng N; Carolinas Trauma Network Research Group.

Gait Posture. 2018 Jun;63:248-253. doi: 10.1016/j.gaitpost.2018.05.014. Epub 2018 May 26.

PMID:
29778065
9.

Are static and functional balance abilities related in individuals with Multiple Sclerosis?

Pau M, Porta M, Coghe G, Corona F, Pilloni G, Lorefice L, Marrosu MG, Cocco E.

Mult Scler Relat Disord. 2017 Jul;15:1-6. doi: 10.1016/j.msard.2017.04.002. Epub 2017 Apr 11.

PMID:
28641764
10.

Multi-parametric evaluation of sit-to-stand and stand-to-sit transitions in elderly people.

Ganea R, Paraschiv-Ionescu A, Büla C, Rochat S, Aminian K.

Med Eng Phys. 2011 Nov;33(9):1086-93. doi: 10.1016/j.medengphy.2011.04.015. Epub 2011 May 20.

PMID:
21601505
11.

Quantifying sit-to-stand and stand-to-sit transitions in free-living environments using the activPAL thigh-worn activity monitor.

Pickford CG, Findlow AH, Kerr A, Banger M, Clarke-Cornwell AM, Hollands KL, Quinn T, Granat MH.

Gait Posture. 2019 Sep;73:140-146. doi: 10.1016/j.gaitpost.2019.07.126. Epub 2019 Jul 12.

PMID:
31325738
12.

Auto detection and segmentation of physical activities during a Timed-Up-and-Go (TUG) task in healthy older adults using multiple inertial sensors.

Nguyen HP, Ayachi F, Lavigne-Pelletier C, Blamoutier M, Rahimi F, Boissy P, Jog M, Duval C.

J Neuroeng Rehabil. 2015 Apr 11;12:36. doi: 10.1186/s12984-015-0026-4.

13.

Further construct validity of the Timed Up-and-Go Test as a measure of ambulation in multiple sclerosis patients.

Kalron A, Dolev M, Givon U.

Eur J Phys Rehabil Med. 2017 Dec;53(6):841-847. doi: 10.23736/S1973-9087.17.04599-3. Epub 2017 Mar 13.

14.

Monitoring gait in multiple sclerosis with novel wearable motion sensors.

Moon Y, McGinnis RS, Seagers K, Motl RW, Sheth N, Wright JA Jr, Ghaffari R, Sosnoff JJ.

PLoS One. 2017 Feb 8;12(2):e0171346. doi: 10.1371/journal.pone.0171346. eCollection 2017.

15.

Biomechanical analysis of the timed up-and-go (TUG) test in children with and without Down syndrome.

Beerse M, Lelko M, Wu J.

Gait Posture. 2019 Feb;68:409-414. doi: 10.1016/j.gaitpost.2018.12.027. Epub 2018 Dec 24.

PMID:
30594868
16.

Quantifying turning behavior and gait in Parkinson's disease using mobile technology.

Miller Koop M, Ozinga SJ, Rosenfeldt AB, Alberts JL.

IBRO Rep. 2018 Jun 21;5:10-16. doi: 10.1016/j.ibror.2018.06.002. eCollection 2018 Dec.

17.

Quantitative analysis of fall risk using TUG test.

Zakaria NA, Kuwae Y, Tamura T, Minato K, Kanaya S.

Comput Methods Biomech Biomed Engin. 2015;18(4):426-37. doi: 10.1080/10255842.2013.805211. Epub 2013 Aug 21.

PMID:
23964848
18.

Quantitative mobility metrics from a wearable sensor predict incident parkinsonism in older adults.

von Coelln R, Dawe RJ, Leurgans SE, Curran TA, Truty T, Yu L, Barnes LL, Shulman JM, Shulman LM, Bennett DA, Hausdorff JM, Buchman AS.

Parkinsonism Relat Disord. 2019 Aug;65:190-196. doi: 10.1016/j.parkreldis.2019.06.012. Epub 2019 Jun 22.

PMID:
31272924
19.

Quantitative analysis of the fall-risk assessment test with wearable inertia sensors.

Tmaura T, Zakaria NA, Kuwae Y, Sekine M, Minato K, Yoshida M.

Conf Proc IEEE Eng Med Biol Soc. 2013;2013:7217-20. doi: 10.1109/EMBC.2013.6611223.

PMID:
24111410
20.

Multivariate Analyses and Classification of Inertial Sensor Data to Identify Aging Effects on the Timed-Up-and-Go Test.

Vervoort D, Vuillerme N, Kosse N, Hortobágyi T, Lamoth CJ.

PLoS One. 2016 Jun 6;11(6):e0155984. doi: 10.1371/journal.pone.0155984. eCollection 2016.

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