#PAGE_PARAMS# #ADS_HEAD_SCRIPTS# #MICRODATA#
CS
proLékaře.cz / Journals / Rehabilitation and Physical Medicine / 2021 - 4

Using inertial sensors in clinical practice

Download PDF Czech version

Authors: Bizovská L.;  Nohelová D.;  Janura M.
Authors‘ workplace: Katedra přírodních věd v kinantropologii, Fakulta tělesné kultury, Univerzita Palackého v Olomouci
Published in: Rehabil. fyz. Lék., 28, 2021, No. 4, pp. 177-184.
Category: Review Article
doi: https://doi.org/10.48095/ccrhfl2021177

Overview

Inertial sensors with their rapid development in the recent years have become useful tools in clinical practice. They can be used in a controlled laboratory environment as well as home environment because of their portability and small size. The aim of this manuscript was to summarise topical possibilities for the use of inertial sensors in clinical practice, including information about suitable activities that can be studied and methodological approaches for their quantification. The assessment of postural stability, instrumented versions of clinical walking tests, Timed Up and Go or Sit-to-Stand tests as well as physical activity monitoring are discussed in detail.

Keywords:

gait – accelerometer – inertial sensor – gyroscope – instrumented Timed Up and Go – instrumented Sit-to-stand

Sources
  1. Moe-Nilssen R. A new method for evaluating motor control in gait under real-life environmental conditions. Part 1: The instrument. Clin Biomech 1998; 13(4–5): 320–327. doi: 10.1016/s0268-0033(98)00089-8.
  2. López-Nava IH, Muñoz-Meléndez A. Wearable inertial sensors for human motion analysis: a review. IEEE Sens J 2016; 16(22); 7821–7834. doi: 10.1109/jsen.2016.2609392.
  3. Warmerdam E, Hausdorff JM, Atrsaei A et al. Long-term unsupervised mobility assessment in movement disorders. Lancet Neurol 2020; 19(5): 462–470. doi: 10.1016/S1474-4422(19)30397-7.
  4. Iosa M, Picerno P, Paolucci S et al. Wearable inertial sensors for human movement analysis. Expert Rev Med Devices 2016; 13(7): 641–659. doi: 10.1080/17434440.2016.1198694.
  5. Hirjaková Z, Neumannová K, Kimijanová J et al. Breathing changes accompanying bal­ance improvement during biofeedback. Neurosci Lett 2017; 651: 30–35. doi: 10.1016/j.neulet.2017.04.051.
  6. Mancini M, Chiari L, Holmstrom L et al. Validity and reliability of an IMU-based meth­­od to detect APAs prior to gait initiation. Gait Posture 2016; 43: 125–131. doi: 10.1016/j.gaitpost.2015.08.015.
  7. Bednáříková H, Janura M, Bizovská L. Využití akcelerometrů v hodnocení vlivu hipoterapie na provedení pohybu u dětí se spastickou formou dětské mozkové obrny – pilotní studie. Rehabil Fyz Lék 2016; 23(4): 190–194.
  8. Winter DA. Human balance and pos­ture control during standing and walking. Gait Posture 1995; 3(4): 193–214. doi: 10.1016/0966-6362(96)82849-9.
  9. Ruhe A, Fejer R, Walker B. The test-retest reliability of centre of pressure measures in bipedal static task conditions – a systematic review of the literature. Gait Posture 2010; 32(4):436–445. doi: 10.1016/j.gaitpost.2010.09.012.
  10. Ghislieri M, Gastaldi L, Pastorelli S et al. Wear­able inertial sensors to assess standing balance: a systematic review. Sensors 2019; 19(19): 4075. doi: 10.3390/s19194075.
  11. Patel M, Pavic A, Goodwin VA. Wearable inertial sensors to measure gait and posture characteristic differences in older adult fallers and non-fallers: a scoping review. Gait Posture 2020; 76: 110–121. doi: 10.1016/j.gaitpost.2019.10.039.
  12. Sun R, Moon Y, McGinnis RS et al. Assessment of postural sway in individuals with multiple sclerosis using a novel wearable inertial sensor. Digit Biomark 2018; 2(1): 1–10. doi: 10.1159/000485958.
  13. Spain RI, St George RJ, Salarian A et al. Body-worn motion sensors detect balance and gait deficits in people with multiple sclerosis who have normal walking speed. Gait Posture 2012; 35(4): 573–578. doi: 10.1016/j.gaitpost.2011.11.026.
  14. Bzdúšková D, Valkovič P, Hirjaková Z et al. Parkinson’s disease versus ageing: different pos­tural responses to soleus muscle vibration. Gait Posture 2018; 65: 169–175. doi: 10.1016/j.gaitpost.2018.07.
  15. Dalton A, Khalil H, Busse M et al. Analysis of gait and balance through a single triaxial accelerometer in presymptomatic and symptomatic Huntington’s disease. Gait Posture 2013; 37(1): 49–54. doi: 10.1016/j.gaitpost.2012.05.028.
  16. Matsushima A, Yoshida K, Genno H et al. Clin­ical assessment of standing and gait in ataxic patients using a triaxial accelerometer. Cerebellum Ataxias 2015; 2: 9. doi: 10.1186/s40673-015-0028-9.
  17. Greene BR, McGrath D, Walsh L et al. Quantitative falls risk estimation through multi-sensor assessment of standing balance. Physiol Meas 2012; 33(12): 2049–2063. doi: 10.1088/0967-3334/33/12/2049.
  18. Cheng PT, Liaw MY, Wong MK et al. The sit-to-stand movement in stroke patients and its correlation with falling. Arch Phys Med Rehabil 1998; 79(9): 1043–1046. doi: 10.1016/s0003-9993(98)90168-x.
  19. Qiu H, Rehman RZU, Yu X et al. Application of wearable inertial sensors and a new test battery for distinguishing retrospective fallers from non-fallers among community-dwelling older people. Sci Rep 2018; 8(1): 16349. doi: 10.1038/s41598-018-34671-6.
  20. Witchel HJ, Oberndorfer C, Needham R et al. 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. Front Neurol 2018; 9: 684. doi: 10.3389/fneur.2018.00684.
  21. Pham MH, Warmerdam E, Elshehabi M et al. Validation of a lower back „wearable“-based Sit-to-Stand and Stand-to-Sit algorithm for pa­tients with Parkinson’s disease and older adults in a home-like environment. Front Neurol 2018; 9: 652. doi: 10.3389/fneur.2018.00652.
  22. Bizovská L, Janura M, Míková M et al. Rovnováha a možnosti jejího hodnocení. Olomouc: Univerzita Palackého 2017.
  23. Pacini Panebianco G, Bisi MC, Stagni R et al. Analysis of the performance of 17 algorithms from a systematic review: influence of sensor position, analysed variable and computational approach in gait timing estimation from IMU measurements. Gait Posture 2018; 66: 76–82. doi: 10.1016/j.gaitpost.2018.08.025.
  24. Howcroft J, Kofman J, Lemaire ED. Review of fall risk assessment in geriatric populations using inertial sensors. J Neuroeng Rehabil 2013; 10(1): 91. doi: 10.1186/1743-0003-10-91.
  25. Bruijn SM, Meijer OG, Beek PJ et al. Assessing the stability of human locomotion: a review of current measures. J R Soc Interface 2013; 10(83): 20120999. doi: 10.1098/rsif.2012.0999.
  26. Bizovska L, Svoboda Z, Kubonova E et al. The differences between overground and treadmill walking in nonlinear, entropy-based and frequency variables derived from accelerometers in young and older women – preliminary report. Acta Bioeng Biomech 2018; 20(1): 93–100.
  27. Bizovska L, Svoboda Z, Vuillerme N et al. Multiscale and Shannon entropies during gait as fall risk predictors – a prospective study. Gait Posture 2017; 52(1): 5–10. doi: 10.1016/j.gaitpost.2016.11.009.
  28. Riva F, Toebes MJP, Pijnappels M et al. Estimating fall risk with inertial sensors using gait stability measures that do not require step detection. Gait Posture 2013; 38(2): 170–174. doi: 10.1016/j.gaitpost.2013.05.002.
  29. Jimenez-Moreno AC, Charman SJ, Nikolenko N et al. Analyzing walking speeds with ankle and wrist worn accelero­meters in a cohort with myotonic dystrophy. Dis­abil Rehabil 2019; 41(24): 2972–2978. doi: 10.1080/09638288.2018.1482376.
  30. Podsiadlo D, Richardson S. The Timed „Up & Go“: a test of basic functional mobility for frail elderly persons. J Am Geriatr Soc 1998; 39(2): 142–148. doi: 10.1111/j.1532-5415.1991.tb01616.x.
  31. Salarian A, Horak FB, Zampieri C et al. iTUG, a sensitive and reliable measure of mobility. IEEE Trans Neural Syst Rehabil Eng 2010; 18(3): 303–310. doi: 10.1109/TNSRE.2010.2047606.
  32. Greene BR, Caulfield B, Lamichhane D et al. Longitudinal assessment of falls in patients with Parkinson’s disease using inertial sensors and the Timed Up and Go test. J Rehabil Assist Technol Eng 2018; 5. doi: 10.1177/2055668317750811.
  33. van Lummel RC, Walgaard S, Hobert MA et al. Intra-rater, inter-rater and test-retest reliability of an instrumented Timed Up and Go (iTUG) test in patients with Parkinson’s disease. Plos One 2016; 11(3): e0151881. doi: 10.1371/journal.pone.0151881.
  34. Sankarpandi SK, Baldwin AJ, Ray J et al. Reli­ability of inertial sensors in the assessment of patients with vestibular disorders: a feasibility study. BMC Ear Nose Throat Disord 2017; 17: 1. doi: 10.1186/s12901-017-0034-z.
  35. Wüest S, Massé F, Aminian K et al. Reliabi­l­ity and validity of the inertial senzor-based Timed “Up and Go” test in individuals affected by ­stroke. J Rehabil Res Dev 2016; 53(5): 599–610. doi: 10.1682/jrrd.2015.04.0065.
  36. Ihlen EAF, Weiss A, Bourke A et al. The complexity of daily life walking in older adult community – dwelling fallers and non-fallers. J Biomech 2016; 49(9): 1420–1428. doi: 10.1016/j.jbiomech.2016.02.055.
  37. Ihlen EAF, Weiss A, Beck Y et al. A compar­ison study of local dynamic stability mea­sures of daily life walking in older adult com­munity – dwelling fallers and non-fallers. J Biomech 2016; 49(9): 1498–1503. doi: 10.1016/j.jbiomech.2016.03.019.
  38. Leach JM, Mellone S, Palumbo P et al. Natural turn measures predict recurrent falls in com­munity – dwelling older adults: a longitudinal cohort study. Sci Rep 2018; 8(1): 4316. doi: 10.1038/s41598-018-22492-6.
  39. Mancini M, Schlueter H, El-Gohary M et al. Continuous monitoring of turning mobility and its association to falls and cognitive function: a pilot study. J Gerontol A Biol Sci Med Sci 2016; 71(8): 1102–1108. doi: 10.1093/gerona/glw019.
  40. Morillo DS, Ojeda JLR, Foix LFC et al. An accelerometer-based device for sleep apnea screen­ing. IEEE Trans Inf Technol Biomed 2010; 14(2): 491–499. doi: 10.1109/TITB.2009.2027231.
  41. World Health Organization (WHO). Global recommendations on physical activity for ­health. Geneva, Switzerland: WHO; 2010. Andre D, Wolf DL. Recent advances in free-living physical activity monitoring: a review.
  42. J Diabetes Sci Technol 2007; 1(5): 760–767. doi: 10.1177/193229680700100522.
  43. Bassett DR. Device-based monitoring in physical activity and public health research. Physiol Meas 2012; 33(11): 1769–1783. doi: 10.1088/0967-3334/33/11/1769.
  44. Block VA, Pitsch E, Tahir P et al. Remote physical activity monitoring in neurological dis­ease: a systematic review. Plos One 2016; 11(4): e0154335. doi: 10.1371/journal.pone.0154335.
  45. Taraldsen K, Chastin SFM, Riphagen II et al. Physical activity monitoring by use of accelerometer-based body-worn sensors in older adults: a systematic literature review of current knowledge and applications. Maturitas 2012; 71(1): 13–19. doi: 10.1016/j.maturitas.2011.11.003.
  46. Yang CC, Hsu YL. A review of accelerometry-based wearable motion detectors for physical activity monitoring. Sensors 2010; 10(8): 7772–7788. doi: 10.3390/s100807772.
  47. Crouter SE, Churilla JR, Bassett Jr DR. Estima­ting energy expenditure using accelerometers. Eur J Appl Physiol 2006; 98(6): 601–612. doi: 10.1007/s00421-006-0307-5.
  48. Ainsworth BE, Haskell WL, Leon AS et al. Compendium of physical activities: classification of energy costs of human physical activities. Med Sci Sports Exerc 1993; 25(1): 71–80. doi: 10.1249/00005768-199301000-00011.
Labels
Physiotherapist, university degree Rehabilitation Sports medicine
Gait rehabilitation in Parkinson’s disease patients – Cueing therapy
Effect of dynamic neuromuscular stabilization in patients after arthroscopy of the shoulder joint
Influencing the range of motion using trigger point therapy – systematic review
Detection of mild cognitive impairment during locomotion after stroke
Update of the Czech translation of the International Classification of Functioning, Disability and Health
K 100. výročí narození doc. MUDr. Františka Véleho, CSc. (1921–2016)
Article was published in

Rehabilitation and Physical Medicine

Issue 4
2021 Issue 4
Most read in this issue
Journals
Login
Forgotten password

Enter the email address that you registered with. We will send you instructions on how to set a new password.

Login

Don‘t have an account?  Create new account

#ADS_BOTTOM_SCRIPTS#