Monitoring training activity during gait-related balance exercise in individuals with Parkinson's disease: a proof-of-concept-study

David Conradsson, Håkan Nero, Niklas Löfgren, Maria Hagströmer, Erika Franzén, David Conradsson, Håkan Nero, Niklas Löfgren, Maria Hagströmer, Erika Franzén

Abstract

Background: Despite the benefits of balance exercise in clinical populations, balance training programs tend to be poorly described, which in turn makes it difficult to evaluate important training components and compare between programs. However, the use of wearable sensors may have the potential to monitor certain elements of balance training. Therefore, this study aimed to investigate the feasibility of using wearable sensors to provide objective indicators of the levels and progression of training activity during gait-related balance exercise in individuals with Parkinson's disease.

Methods: Ten individuals with Parkinson's disease participated in 10 weeks of group training (three sessions/week) addressing highly-challenging balance exercises. The training program was designed to be progressive by gradually increasing the amount of gait-related balance exercise exercises (e.g. walking) and time spent dual-tasking throughout the intervention period. Accelerometers (Actigraph GT3X+) were used to measure volume (number of steps/session) and intensity (time spent walking >1.0 m/s) of dynamic training activity. Training activity was also expressed in relation to the participants' total daily volume of physical activity prior to the training period (i.e. number of steps during training/the number of steps per day). Feasibility encompassed the adequacy of data sampling, the output of accelerometer data and the participants' perception of the level of difficulty of training.

Results: Training activity data were successfully obtained in 98% of the training sessions (n = 256) and data sampling did not interfere with training. Reflecting the progressive features of this intervention, training activity increased throughout the program, and corresponded to a high level of the participants' daily activity (28-43%). In line with the accelerometer data, a majority of the participants (n = 8) perceived the training as challenging.

Conclusions: The findings of this proof-of-concept study support the feasibility of applying wearable sensors in clinical settings to gain objective informative measures of gait-related balance exercise in individuals with Parkinson's disease. Still, this activity monitoring approach needs to be further validated in other populations and programs including gait-related balance exercises.

Trial registration: NCT01417598 , 15th August 2011.

Keywords: Accelerometry; Balance exercise; Dual-task; Postural control; Training progression; Wearable sensors.

Figures

Fig. 1
Fig. 1
The level of dynamic exercises throughout the 10-week intervention. a Volume (steps/session), b Slow walking (minutes in <1 m/s) and c Brisk walking (minutes in >1 m/s) plotted as group and individual mean values for Block A (week 1–2), Block B (week 3–6) and Block C (week 7–10). *P ≤ 0.05
Fig. 2
Fig. 2
Individual data of training activity. Typical patterns of a Training volume, b Slow walking (minutes in <1 m/s) and c Brisk walking (minutes in >1 m/s) plotted for all 30 trainings sessions for a low performance (participant six) and high performance individual (participant nine)

References

    1. Nilsen P. Making sense of implementation theories, models and frameworks. Implement Sci. 2015;10:53. doi: 10.1186/s13012-015-0242-0.
    1. Hoffmann TC, Glasziou PP, Boutron I, Milne R, Perera R, Moher D, Altman DG, Barbour V, Macdonald H, Johnston M, et al. Better reporting of interventions: template for intervention description and replication (TIDieR) checklist and guide. BMJ. 2014;348:g1687. doi: 10.1136/bmj.g1687.
    1. Thompson W, Gordon N, Pescatello L. ACSM's guidelines for exercise testing and prescription, vol. 8. Philadelphia: Wolters Kluwer; 2010.
    1. Farlie MK, Molloy E, Keating JL, Haines TP. Clinical markers of the intensity of balance challenge: observational study of older adult responses to balance tasks. Phys Ther. 2016;96:313–23. doi: 10.2522/ptj.20140524.
    1. Farlie MK, Robins L, Keating JL, Molloy E, Haines TP. Intensity of challenge to the balance system is not reported in the prescription of balance exercises in randomised trials: a systematic review. J Physiother. 2013;59:227–35. doi: 10.1016/S1836-9553(13)70199-1.
    1. Haas R, Maloney S, Pausenberger E, Keating JL, Sims J, Molloy E, Jolly B, Morgan P, Haines T. Clinical decision making in exercise prescription for fall prevention. Phys Ther. 2012;92:666–79. doi: 10.2522/ptj.20110130.
    1. Lesinski M, Hortobagyi T, Muehlbauer T, Gollhofer A, Granacher U. Dose-response relationships of balance training in healthy young adults: a systematic review and meta-analysis. Sports Med. 2015;45:557–76. doi: 10.1007/s40279-014-0284-5.
    1. Lesinski M, Hortobagyi T, Muehlbauer T, Gollhofer A, Granacher U. Effects of balance training on balance performance in healthy older adults: a systematic review and meta-analysis. Sports Med. 2015;45:1721–38. doi: 10.1007/s40279-015-0375-y.
    1. Strouwen C, Molenaar EA, Munks L, Keus SH, Bloem BR, Rochester L, Nieuwboer A. Dual tasking in Parkinson’s disease: should we train hazardous behavior? Expert Rev Neurother. 2015;15:1031–9. doi: 10.1586/14737175.2015.1077116.
    1. Plummer P, Eskes G, Wallace S, Giuffrida C, Fraas M, Campbell G, Clifton K, Skidmore ER, American Congress of Rehabilitation Medicine Stroke Networking Group Cognition Task F Cognitive-motor interference during functional mobility after stroke: state of the science and implications for future research. Arch Phys Med Rehabil. 2013;94:2565–74. doi: 10.1016/j.apmr.2013.08.002.
    1. Wang X, Pi Y, Chen P, Liu Y, Wang R, Chan C. Cognitive motor interference for preventing falls in older adults: a systematic review and meta-analysis of randomised controlled trials. Age Ageing. 2015;44:205–12. doi: 10.1093/ageing/afu175.
    1. Corder K, Brage S, Ekelund U. Accelerometers and pedometers: methodology and clinical application. Curr Opin Clin Nutr Metab Care. 2007;10:597–603. doi: 10.1097/MCO.0b013e328285d883.
    1. Matthews CE, Hagstromer M, Pober DM, Bowles HR. Best practices for using physical activity monitors in population-based research. Med Sci Sports Exerc. 2012;44:S68–76. doi: 10.1249/MSS.0b013e3182399e5b.
    1. Howe TE, Rochester L, Neil F, Skelton DA, Ballinger C. Exercise for improving balance in older people. Cochrane Database Syst Rev. 2011;(11):CD004963. doi:10.1002/14651858.CD004963.pub3.
    1. Tomlinson CL, Patel S, Meek C, Herd CP, Clarke CE, Stowe R, Shah L, Sackley CM, Deane KH, Wheatley K, et al. Physiotherapy versus placebo or no intervention in Parkinson’s disease. Cochrane Database Syst Rev. 2013;9:CD002817.
    1. Schwenk M, Grewal GS, Honarvar B, Schwenk S, Mohler J, Khalsa DS, Najafi B. Interactive balance training integrating sensor-based visual feedback of movement performance: a pilot study in older adults. J Neuroeng Rehabil. 2014;11:164. doi: 10.1186/1743-0003-11-164.
    1. Grewal GS, Schwenk M, Lee-Eng J, Parvaneh S, Bharara M, Menzies RA, Talal TK, Armstrong DG, Najafi B. Sensor-based interactive balance training with visual joint movement feedback for improving postural stability in diabetics with peripheral neuropathy: a randomized controlled trial. Gerontology. 2015;61:567–74. doi: 10.1159/000371846.
    1. Kim SD, Allen NE, Canning CG, Fung VS. Postural instability in patients with Parkinson’s disease. Epidemiology, pathophysiology and management. CNS Drugs. 2013;27:97–112. doi: 10.1007/s40263-012-0012-3.
    1. Pickering RM, Grimbergen YA, Rigney U, Ashburn A, Mazibrada G, Wood B, Gray P, Kerr G, Bloem BR. A meta-analysis of six prospective studies of falling in Parkinson’s disease. Mov Disord. 2007;22:1892–900. doi: 10.1002/mds.21598.
    1. Cavanaugh JT, Ellis TD, Earhart GM, Ford MP, Foreman KB, Dibble LE. Capturing ambulatory activity decline in Parkinson’s disease. J Neurol Phys Ther. 2012;36:51–7. doi: 10.1097/NPT.0b013e318254ba7a.
    1. Canning CG, Paul SS, Nieuwboer A. Prevention of falls in Parkinson’s disease: a review of fall risk factors and the role of physical interventions. Neurodegener Dis Manag. 2014;4:203–21. doi: 10.2217/nmt.14.22.
    1. Allen NE, Sherrington C, Paul SS, Canning CG. Balance and falls in Parkinson’s disease: a meta-analysis of the effect of exercise and motor training. Mov Disord. 2011;26:1605–15. doi: 10.1002/mds.23790.
    1. Heinzel S, Maechtel M, Hasmann SE, Hobert MA, Heger T, Berg D, Maetzler W. Motor dual-tasking deficits predict falls in Parkinson’s disease: A prospective study. Parkinsonism Relat Disord. 2016;26:73–7. doi: 10.1016/j.parkreldis.2016.03.007.
    1. Bloem BR, Grimbergen YA, van Dijk JG, Munneke M. The “posture second” strategy: a review of wrong priorities in Parkinson’s disease. J Neurol Sci. 2006;248:196–204. doi: 10.1016/j.jns.2006.05.010.
    1. Kelly VE, Eusterbrock AJ, Shumway-Cook A. A review of dual-task walking deficits in people with Parkinson’s disease: motor and cognitive contributions, mechanisms, and clinical implications. Park Dis. 2012;2012:918719.
    1. Canning CG, Ada L, Woodhouse E. Multiple-task walking training in people with mild to moderate Parkinson’s disease: a pilot study. Clin Rehabil. 2008;22:226–33. doi: 10.1177/0269215507082341.
    1. Brauer SG, Morris ME. Can people with Parkinson’s disease improve dual tasking when walking? Gait Posture. 2010;31:229–33. doi: 10.1016/j.gaitpost.2009.10.011.
    1. Conradsson D, Löfgren N, Nero H, Hagströmer M, Ståhle A, Lökk J, Franzen E. The Effects of Highly Challenging Balance Training in Elderly With Parkinson’s Disease: A Randomized Controlled Trial. Neuroreh Neur Re. 2015.
    1. Keus S, Munneke M, Graziano M, Paltamaa J, Pelosin E, Domingos J, Bruhlmann S, Ramaswamy B, Prins J, Struiksma C, et al. European physiotherapy guideline for Parkinson’s disease: development & implementation. Mov Disord. 2014;29:S537.
    1. Conradsson D, Löfgren N, Ståhle A, Hagströmer M, Franzén E. A novel conceptual framework for balance training in Parkinson’s disease-study protocol for a randomised controlled trial. BMC Neurol. 2012;12:111. doi: 10.1186/1471-2377-12-111.
    1. Conradsson D, Löfgren N, Ståhle A, Franzen E. Is highly challenging and progressive balance training feasible in older adults with Parkinson’s disease? Arch Phys Med Rehabil. 2014;95:1000–3. doi: 10.1016/j.apmr.2013.10.024.
    1. Hughes AJ, Daniel SE, Kilford L, Lees AJ. Accuracy of clinical diagnosis of idiopathic Parkinson’s disease: a clinico-pathological study of 100 cases. J Neurol Neurosurg Psychiatry. 1992;55:181–4. doi: 10.1136/jnnp.55.3.181.
    1. Hoehn MM, Yahr MD. Parkinsonism: onset, progression and mortality. Neurology. 1967;17:427–42. doi: 10.1212/WNL.17.5.427.
    1. 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;12:189–98. doi: 10.1016/0022-3956(75)90026-6.
    1. Kelly LA, McMillan DG, Anderson A, Fippinger M, Fillerup G, Rider J. Validity of actigraphs uniaxial and triaxial accelerometers for assessment of physical activity in adults in laboratory conditions. BMC Med Phys. 2013;13:5. doi: 10.1186/1756-6649-13-5.
    1. John D, Freedson P. ActiGraph and Actical physical activity monitors: a peek under the hood. Med Sci Sports Exerc. 2012;44:S86–9. doi: 10.1249/MSS.0b013e3182399f5e.
    1. Aadland E, Ylvisaker E. Reliability of the actigraph GT3X+ accelerometer in adults under free-living conditions. PLoS One. 2015;10:e0134606. doi: 10.1371/journal.pone.0134606.
    1. Santos-Lozano A, Marin PJ, Torres-Luque G, Ruiz JR, Lucia A, Garatachea N. Technical variability of the GT3X accelerometer. Med Eng Phys. 2012;34:787–90. doi: 10.1016/j.medengphy.2012.02.005.
    1. Benka Wallen M, Franzen E, Nero H, Hagströmer M. Levels and patterns of physical activity and sedentary behavior in elderly people with mild to moderate Parkinson disease. Phys Ther. 2015;95:1135–41. doi: 10.2522/ptj.20140374.
    1. Wallen MB, Nero H, Franzen E, Hagströmer M. Comparison of two accelerometer filter settings in individuals with Parkinson’s disease. Physiol Meas. 2014;35:2287–96. doi: 10.1088/0967-3334/35/11/2287.
    1. Nero H, Benka Wallén M, Franzén E, Ståhle A, Hagströmer M. Accelerometer Cut Points for Physical Activity Assessment of Older Adults with Parkinson’s Disease. PLoS One. 2015;10(9):e0135899.
    1. Aguilar-Farias N, Brown WJ, Peeters GM. ActiGraph GT3X+ cut-points for identifying sedentary behaviour in older adults in free-living environments. J Sci Med Sport. 2014;17:293–9. doi: 10.1016/j.jsams.2013.07.002.
    1. van Nimwegen M, Speelman AD, Overeem S, van de Warrenburg BP, Smulders K, Dontje ML, Borm GF, Backx FJ, Bloem BR, Munneke M, et al. Promotion of physical activity and fitness in sedentary patients with Parkinson’s disease: randomised controlled trial. BMJ. 2013;346:f576. doi: 10.1136/bmj.f576.
    1. Horak FB. Postural orientation and equilibrium: what do we need to know about neural control of balance to prevent falls? Age Ageing. 2006;35(Suppl 2):ii7–ii11.
    1. Mancini M, El-Gohary M, Pearson S, McNames J, Schlueter H, Nutt JG, King LA, Horak FB. Continuous monitoring of turning in Parkinson’s disease: Rehabilitation potential. NeuroRehabilitation. 2015;37:3–10. doi: 10.3233/NRE-151236.
    1. Horak FB, Mancini M. Objective biomarkers of balance and gait for Parkinson’s disease using body-worn sensors. Mov Disord. 2013;28:1544–51. doi: 10.1002/mds.25684.
    1. Al-Yahya E, Dawes H, Smith L, Dennis A, Howells K, Cockburn J. Cognitive motor interference while walking: a systematic review and meta-analysis. Neurosci Biobehav Rev. 2011;35:715–28. doi: 10.1016/j.neubiorev.2010.08.008.
    1. Nieuwboer A, Rochester L, Muncks L, Swinnen SP. Motor learning in Parkinson’s disease: limitations and potential for rehabilitation. Parkinsonism Relat Disord. 2009;15(Suppl 3):S53–8. doi: 10.1016/S1353-8020(09)70781-3.
    1. Yogev-Seligmann G, Giladi N, Brozgol M, Hausdorff JM. A training program to improve gait while dual tasking in patients with Parkinson’s disease: a pilot study. Arch Phys Med Rehabil. 2012;93:176–81. doi: 10.1016/j.apmr.2011.06.005.
    1. Mirelman A, Maidan I, Herman T, Deutsch JE, Giladi N, Hausdorff JM. Virtual reality for gait training: can it induce motor learning to enhance complex walking and reduce fall risk in patients with Parkinson’s disease? J Gerontol A Biol Sci Med Sci. 2011;66:234–40. doi: 10.1093/gerona/glq201.

Source: PubMed

3
Sottoscrivi