Quantitative assessment of multiple sclerosis using inertial sensors and the TUG test

被引:0
|
作者
Greene, Barry R. [1 ,2 ]
Healy, Michael [5 ]
Rutledge, Stephanie [5 ]
Caulfield, Brian [3 ,4 ]
Tubridy, Niall [5 ]
机构
[1] Univ Coll Dublin, TRIL Ctr, Dublin 2, Ireland
[2] Kinesis Hlth Technol, Dublin, Ireland
[3] Univ Coll Dublin, Insight Ctr, Dublin 2, Ireland
[4] Univ Coll Dublin, Sch Physiotherapy & Performance Sci, Dublin 2, Ireland
[5] St Vincents Univ Hosp, Dept Neurol, Dublin 4, Ireland
来源
2014 36TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC) | 2014年
关键词
FALLS RISK; GO; MOBILITY;
D O I
暂无
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
Multiple sclerosis (MS) is a progressive neurological disorder affecting between 2 and 2.5 million people globally. Tests of mobility form part of clinical assessments of MS. Quantitative assessment of mobility using inertial sensors has the potential to provide objective, longitudinal monitoring of disease progression in patients with MS. The mobility of 21 patients (aged 25-59 years, 8 M, 13 F), diagnosed with relapsing-remitting MS was assessed using the Timed up and Go (TUG) test, while patients wore shank-mounted inertial sensors. This exploratory, cross-sectional study aimed to examine the reliability of quantitative measures derived from inertial sensors during the TUG test, in patients with MS. Furthermore, we aimed to determine if disease status (as measured by the Multiple Sclerosis Impact Scale (MSIS-29) and the Expanded Disability Status Score (EDSS)) can be predicted by assessment using a TUG test and inertial sensors. Reliability analysis showed that 32 of 52 inertial sensors parameters obtained during the TUG showed excellent intrasession reliability, while 11 of 52 showed moderate reliability. Using the inertial sensors parameters, regression models of the EDSS and MSIS-29 scales were derived using the elastic net procedure. Using cross validation, an elastic net regularized regression model of MSIS yielded a mean square error (MSE) of 334.6 with 25 degrees of freedom (DoF). Similarly, an elastic net regularized regression model of EDSS yielded a cross-validated MSE of 1.5 with 6 DoF. Results suggest that inertial sensor parameters derived from MS patients while completing the TUG test are reliable and may have utility in assessing disease state as measured using EDSS and MSIS.
引用
收藏
页码:2977 / 2980
页数:4
相关论文
共 50 条
  • [21] Assessment of hand kinematics using inertial and magnetic sensors
    Kortier, Henk G.
    Sluiter, Victor I.
    Roetenberg, Daniel
    Veltink, Peter H.
    JOURNAL OF NEUROENGINEERING AND REHABILITATION, 2014, 11
  • [22] Motor Function Assessment Using Wearable Inertial Sensors
    Parnandi, Avinash
    Wade, Eric
    Mataric, Maja
    2010 ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC), 2010, : 86 - 89
  • [23] AXIAL SPONDYLOARTHRITIS POSTURE ASSESSMENT USING INERTIAL SENSORS
    Garrido-Castro, J. L.
    Concha-Aranda, I. C.
    Gardiner, P.
    Machado, P. M.
    Williams, J.
    Collantes-Estevez, E.
    ANNALS OF THE RHEUMATIC DISEASES, 2018, 77 : 1561 - 1561
  • [24] Using the TUG Test for the Functional Assessment of Patients with Selected Disorders
    Graff, Krzysztof
    Szczerbik, Ewa
    Kalinowska, Malgorzata
    Kaczmarczyk, Katarzyna
    Stepien, Agnieszka
    Syczewska, Malgorzata
    INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH, 2022, 19 (08)
  • [25] Objective Clinical Fitness Assessment Using Inertial Sensors
    Ameli, Sina
    Naghdy, Fazel
    Stirling, David
    Naghdy, Golshah
    Aghmesheh, Morteza
    INTERNATIONAL SYMPOSIUM ON ROBOTICS AND INTELLIGENT SENSORS 2012 (IRIS 2012), 2012, 41 : 443 - 449
  • [26] Assessment and Classification of Early-Stage Multiple Sclerosis With Inertial Sensors: Comparison Against Clinical Measures of Disease State
    Greene, Barry R.
    Rutledge, Stephanie
    McGurgan, Iain
    McGuigan, Christopher
    O'Connell, Karen
    Caulfield, Brian
    Tubridy, Niall
    IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS, 2015, 19 (04) : 1356 - 1361
  • [27] Quantitative assessment of self-treated canalith repositioning procedures using inertial measurement unit sensors
    Kwon, Chiheon
    Ku, Yunseo
    Seo, Shinhye
    Jang, Eunsook
    Kong, Hyoun-Joong
    Suh, Myung-Whan
    Kim, Hee Chan
    JOURNAL OF VESTIBULAR RESEARCH-EQUILIBRIUM & ORIENTATION, 2021, 31 (05): : 423 - 431
  • [28] Quantitative assessment of multiple sclerosis lesion load using CAD and expert input
    Gertych, Arkadiusz
    Wong, Alexis
    Sangnil, Alan
    Liu, Brent J.
    MEDICAL IMAGING 2008: COMPUTER-AIDED DIAGNOSIS, PTS 1 AND 2, 2008, 6915
  • [29] Cognitive-motor interference in multiple sclerosis revisited: a dual-task paradigm using wearable inertial sensors and the Paced Auditory Serial Addition Test
    Kremer, Lea
    Schreff, Lucas
    Hamacher, Daniel
    Oschmann, Patrick
    Rothhammer, Veit
    Keune, Philipp M.
    Mueller, Roy
    FRONTIERS IN NEUROLOGY, 2025, 16
  • [30] FDI using multiple parity vectors for redundant inertial sensors
    Yang, Cheol-Kwan
    Shim, Duk-Sun
    EUROPEAN JOURNAL OF CONTROL, 2006, 12 (04) : 437 - 449