Skip to main content

Advertisement

SpringerLink
Log in

Wearables in the home-based assessment of abnormal movements in Parkinson’s disease: a systematic review of the literature

  • Review
  • Published:
Journal of Neurology Aims and scope Submit manuscript

Abstract

At present, the standard practices for home-based assessments of abnormal movements in Parkinson’s disease (PD) are based either on subjective tools or on objective measures that often fail to capture day-to-day fluctuations and long-term information in real-life conditions in a way that patient’s compliance and privacy are secured. The employment of wearable technologies in PD represents a great paradigm shift in healthcare remote diagnostics and therapeutics monitoring. However, their applicability in everyday clinical practice seems to be still limited. We carried out a systematic search across the Medline Database. In total, 246 publications, published until 1 June 2020, were identified. Among them, 26 reports met the inclusion criteria and were included in the present review. We focused more on clinically relevant aspects of wearables’ application including feasibility and efficacy of the assessment, the number, type and body position of the wearable devices, type of PD motor symptom, environment and duration of assessments and validation methodology. The aim of this review is to provide a systematic overview of the current knowledge and state-of-the-art of the home-based assessment of motor symptoms and fluctuations in PD patients using wearable technology, highlighting current problems and laying foundations for future works.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1

Similar content being viewed by others

References

  1. Tysnes OB, Storstein A (2017) Epidemiology of Parkinson’s disease. J Neural Transm 124:901–905. https://doi.org/10.1007/s00702-017-1686-y

    Article  PubMed  Google Scholar 

  2. Kalia LV, Lang AE (2015) Seminar Parkinson’s disease. Lancet 386:896–912

    Article  CAS  PubMed  Google Scholar 

  3. Williams-gray CH (2016) Parkinson’s disease key points. Medicine 44:542–546. https://doi.org/10.1016/j.mpmed.2016.06.001

    Article  Google Scholar 

  4. Xia R, Mao Z-H (2012) Progression of motor symptoms in Parkinson’s disease. Neurosci Bull 28:39–48. https://doi.org/10.1007/s12264-012-1050-z

    Article  PubMed  PubMed Central  Google Scholar 

  5. Manson A, Stirpe P, Schrag A (2012) Levodopa-induced-dyskinesias clinical features, incidence, risk factors, management and impact on quality of life. J Parkinson’s Dis 2:189–198. https://doi.org/10.3233/JPD-2012-120103

    Article  CAS  Google Scholar 

  6. Sringean J, Taechalertpaisarn P, Thanawattano C, Bhidayasiri R (2016) How well do Parkinson’s disease patients turn in bed? Quantitative analysis of nocturnal hypokinesia using multisite wearable inertial sensors. Parkinsonism Relat Disord 23:10–16. https://doi.org/10.1016/j.parkreldis.2015.11.003

    Article  PubMed  Google Scholar 

  7. Bhidayasiri R, Sringean J, Taechalertpaisarn P, Thanawattano C (2016) Capturing nighttime symptoms in Parkinson disease: technical development and experimental verification of inertial sensors for nocturnal hypokinesia. J Rehabil Res Dev 53:487–498. https://doi.org/10.1682/JRRD.2015.04.0062

    Article  PubMed  Google Scholar 

  8. Stack EL, Ashburn AM (2006) Impaired bed mobility and disordered sleep in Parkinson’s disease. Mov Disord 21:1340–1342. https://doi.org/10.1002/mds.20944

    Article  PubMed  Google Scholar 

  9. Bargiotas P, Bassetti CL (2017). Sleep-related movement disorders and disturbances of motor control. https://doi.org/10.1097/WCO.0000000000000466

    Article  Google Scholar 

  10. Pérez-lópez C, Samà A, Rodríguez-martín D, Moreno-aróstegui JM, Cabestany J, Bayes A, Mestre B, Alcaine S, Quispe P, Laighin GÓ, Sweeney D, Quinlan LR, Counihan TJ, Browne P, Annicchiarico R, Costa A, Lewy H, Rodríguez-molinero A (2016) Dopaminergic-induced dyskinesia assessment based on a single belt-worn accelerometer. Artif Intell Med 67:47–56

    Article  PubMed  Google Scholar 

  11. Nieuwboer A, de Weerdt W, Dom R, Lesaffre E (1998) A frequency and correlation analysis of motor deficits in Parkinson patients. Disabil Rehabil 20:142–150. https://doi.org/10.3109/09638289809166074

    Article  CAS  PubMed  Google Scholar 

  12. Mera TO, Heldman DA, Espay AJ, Payne M, Giuffrida JP (2012) Feasibility of home-based automated Parkinson’s disease motor assessment. J Neurosci Methods 203:152–156. https://doi.org/10.1016/j.jneumeth.2011.09.019

    Article  PubMed  Google Scholar 

  13. Ramsperger R, Meckler S, Heger T, Van Uem J, Hucker S, Braatz U, Graessner H, Berg D, Manoli Y (2016) Parkinsonism and Related Disorders Continuous leg dyskinesia assessment in Parkinson’s disease e clinical validity and ecological effect Lab-based Investigation only on medication ON. Parkinsonism Relat Disord 26:41–46

    Article  PubMed  Google Scholar 

  14. Bayés À, Samá A, Prats A, Pérez-López C, Crespo-Maraver M, Moreno JM, Alcaine S, Rodriguez-Molinero A, Mestre B, Quispe P, de Barros AC, Castro R, Costa A, Annicchiarico R, Browne P, Counihan T, Lewy H, Vainstein G, Quinlan LR, Sweeney D, G. ÓLaighin, J. Rovira, D. Rodrigue z-Martin, J. Cabestany, (2008) A “HOLTER” for Parkinson’s disease: validation of the ability to detect on-off states using the REMPARK system. Gait Posture 59:1–6. https://doi.org/10.1016/j.gaitpost.2017.09.031

    Article  Google Scholar 

  15. Reimer J, Grabowski M, Lindvall O, Hagell P (2004) Use and interpretation of on/off diaries in Parkinson’s disease. J Neurol Neurosurg Psychiatry 75:396–400. https://doi.org/10.1136/jnnp.2003.022780

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Goetz CG, Poewe W, Rascol O, Sampaio C, Stebbins GT (2003) State of the art review the unified parkinson’s disease rating scale (updrs): status and recommendations. Mov Disord Soc 18:738–750. https://doi.org/10.1002/mds.10473

    Article  Google Scholar 

  17. Postuma RB, Berg D, Stern M, Poewe W, Olanow CW, Oertel W, Obeso J, Marek K, Litvan I, Lang AE, Halliday G, Goetz CG, Gasser T, Dubois B, Chan P, Bloem BR, Adler CH, Deuschl G (2015) MDS clinical diagnostic criteria for Parkinson’s disease. Mov Disord 30:1591–1601. https://doi.org/10.1002/mds.26424

    Article  PubMed  Google Scholar 

  18. Pietracupa S, Latorre A, Berardelli A, Fabbrini G (2014) Parkinsonian patients and poor awareness of dyskinesias. Mov Disord. https://doi.org/10.1002/mds.24017

    Article  Google Scholar 

  19. Godinho C, Domingos J, Cunha G, Santos AT, Fernandes RM, Abreu D, Gonçalves N, Matthews H, Isaacs T, Duffen J, Al-jawad A, Larsen F, Serrano A, Weber P, Thoms A, Sollinger S, Graessner H, Maetzler W, Ferreira JJ (2016) A systematic review of the characteristics and validity of monitoring technologies to assess Parkinson’s disease. J NeuroEng Rehabil. https://doi.org/10.1186/s12984-016-0136-7

    Article  PubMed  PubMed Central  Google Scholar 

  20. Griffiths RI, Kotschet K, Arfon S, Ming Z, Johnson W (2012) Automated Assessment of Bradykinesia and Dyskinesia in Parkinson’s disease. J Parkinson’s Dis 2:47–55. https://doi.org/10.3233/JPD-2012-11071

    Article  Google Scholar 

  21. Samà A, Pérez-López C, Rodríguez-Martín D, Català A, Moreno-Aróstegui JM, Cabestany J, de Mingo E, Rodríguez-Molinero A (2017) Estimating bradykinesia severity in Parkinson’s disease by analysing gait through a waist-worn sensor. Comput Biol Med 84:114–123. https://doi.org/10.1016/j.compbiomed.2017.03.020

    Article  PubMed  Google Scholar 

  22. Binder S, Deuschl G, Volkmann J (2009) Effect of cabergoline on Parkinsonian tremor assessed by long-term actigraphy. Eur Neurol 61:149–153. https://doi.org/10.1159/000186505

    Article  CAS  PubMed  Google Scholar 

  23. Weiss A, Herman T, Giladi N, Hausdorff JM (2014) Objective assessment of fall risk in Parkinson’s disease using a body-fixed sensor worn for 3 days. PLoS ONE. https://doi.org/10.1371/journal.pone.0096675

    Article  PubMed  PubMed Central  Google Scholar 

  24. Weiss A, Sharifi S, Plotnik M, Van Vugt JPP, Giladi N, Hausdorff JM (2011) Toward automated, at-home assessment of mobility among patients with Parkinson disease, using a body-worn accelerometer. Neurorehabil Neural Repair 25:810–818. https://doi.org/10.1177/1545968311424869

    Article  PubMed  Google Scholar 

  25. Dijkstra B, Kamsma YP, Zijlstra W (2010) Detection of gait and postures using a miniaturized triaxial accelerometer-based system: Accuracy in patients with mild to moderate Parkinson’s disease. Arch Phys Med Rehabil 91:1272–1277. https://doi.org/10.1016/j.apmr.2010.05.004

    Article  PubMed  Google Scholar 

  26. Pan W, Kwak S, Li F, Wu C, Chen Y, Yamamoto Y, Cai D (2013) Actigraphy monitoring of symptoms in patients with Parkinson’s disease. Physiol Behav 119:156–160. https://doi.org/10.1016/j.physbeh.2013.05.044

    Article  CAS  PubMed  Google Scholar 

  27. Heldman DA, Giuffrida JP, Cubo E (2016) Wearable sensors for advanced therapy referral in Parkinson’s disease. J Parkinson’s Dis 6:631–638. https://doi.org/10.3233/JPD-160830

    Article  Google Scholar 

  28. Herman T, Weiss A, Brozgol M, Giladi N, Hausdorff JM (2014) Gait and balance in Parkinson’s disease subtypes: objective measures and classification considerations. J Neurol 261:2401–2410. https://doi.org/10.1007/s00415-014-7513-6

    Article  PubMed  Google Scholar 

  29. Bernad-Elazari H, Herman T, Mirelman A, Gazit E, Giladi N, Hausdorff JM (2016) Objective characterization of daily living transitions in patients with Parkinson’s disease using a single body-fixed sensor. J Neurol 263:1544–1551. https://doi.org/10.1007/s00415-016-8164-6

    Article  PubMed  Google Scholar 

  30. Lipsmeier F, Taylor KI, Kilchenmann T, Wolf D, Scotland A, Schjodt-Eriksen J, Cheng WY, Fernandez-Garcia I, Siebourg-Polster J, Jin L, Soto J, Verselis L, Boess F, Koller M, Grundman M, Monsch AU, Postuma RB, Ghosh A, Kremer T, Czech C, Gossens C, Lindemann M (2018) Evaluation of smartphone-based testing to generate exploratory outcome measures in a phase 1 Parkinson’s disease clinical trial. Mov Disord 33:1287–1297. https://doi.org/10.1002/mds.27376

    Article  PubMed  PubMed Central  Google Scholar 

  31. Tan EE, Hogg EJ, Tagliati M (2019) The role of personal kinetigraphTM fluctuator score in quantifying the progression of motor fluctuations in Parkinson’s disease. Funct Neurol 34:21–28

    CAS  PubMed  Google Scholar 

  32. Fisher JM, Hammerla NY, Ploetz T, Andras P, Rochester L, Walker RW (2016) Unsupervised home monitoring of Parkinson’s disease motor symptoms using body-worn accelerometers. Parkinsonism Relat Disord 33:44–50. https://doi.org/10.1016/j.parkreldis.2016.09.009

    Article  PubMed  Google Scholar 

  33. De Lima ALS, Hahn T, Evers LJW, De Vries NM, Cohen E, Afek M, Bataille L, Daeschler M, Claes K, Boroojerdi B, Terricabras D, Little MA, Baldus H, Bloem BR, Faber MJ (2017) Feasibility of large-scale deployment of multiple wearable sensors in Parkinson’s disease. PLoS ONE 12:1–15. https://doi.org/10.1371/journal.pone.0189161

    Article  CAS  Google Scholar 

  34. Boroojerdi B, Ghaffari R, Mahadevan N, Markowitz M, Melton K, Morey B, Otoul C, Patel S, Phillips J, Sen-Gupta E, Stumpp O, Tatla D, Terricabras D, Claes K, Wright JA, Sheth N (2019) Clinical feasibility of a wearable, conformable sensor patch to monitor motor symptoms in Parkinson’s disease. Parkinsonism Related Disord 61:70–76. https://doi.org/10.1016/j.parkreldis.2018.11.024

    Article  Google Scholar 

  35. M. Pastorino, J. Cancela, M.T. Arredondo, L. Pastor-Sanz, S. Contardi, F. Valzania (2013) Preliminary results of ON/OFF detection using an integrated system for Parkinson’s disease monitoring. In: 35th Annual international conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pp 941–944. Doi: https://doi.org/10.1109/EMBC.2013.6609657.

  36. M. Pastorino, J. Cancela, M.T. Arredondo, M. Pansera, L. Pastor-Sanz, F. Villagra, M.A. Pastor, J.A. Martín (2011) Assessment of bradykinesia in Parkinson’s disease patients through a multi-parametric system. In: 33rd Annual international conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pp 1810–1813. doi: https://doi.org/10.1109/IEMBS.2011.6090516.

  37. S. Das, B. Amoedo, F.D. la Torre, J. Hodgins (2012) Detecting parkinson’s symptoms in uncontrolled home environments : a multiple instance learning approach. In: 34th Annual international conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pp 3688–3691

  38. Chen B, Patel S, Buckley T, Rednic R, Mcclure DJ, Shih L, Tarsy D, Welsh M, Bonato P (2011) A web-based system for home monitoring of patients with Parkinson’s disease using wearable sensors. IEE Trans Biomed Eng 58:831–836

    Article  Google Scholar 

  39. Patel S, Member S, Chen B, Mancinelli C, Paganoni S, Shih L, Welsh M, Dy J, Bonato P, Member S (2011) Wearable sensor technology in the home setting. In: Annual international conference of the IEEE Engineering in Medicine and |Biological Society, pp 1552–1555.

  40. Tarnita D (2016) Wearable sensors used for human gait analysis. Rom J Morphol Embryol 57:373–382

    PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Neurology, University Hospital Bern (Inselspital), University of Bern, Bern, Switzerland

    Stefania Ancona, Oriella Gnarra, Tobias Nef, Claudio L. A. Bassetti & Panagiotis Bargiotas

  2. Institute for Information Systems and Networking, University of Applied Sciences and Arts of Southern Switzerland, Manno, Switzerland

    Francesca D. Faraci & Luigi Fiorillo

  3. Department of Neurology, Medical School, University of Cyprus, Nicosia, Cyprus

    Elina Khatab & Panagiotis Bargiotas

  4. Institute of Informatics, University of Bern, Bern, Switzerland

    Luigi Fiorillo

  5. Sensory-Motor System Lab, IRIS, ETH Zurich, Zurich, Switzerland

    Oriella Gnarra

  6. Neurotec, Swiss Institute for Translational and Entrepreneurial Medicine, Bern, Switzerland

    Oriella Gnarra, Tobias Nef & Claudio L. A. Bassetti

  7. ARTORG Center for Biomedical Engineering Research, Gerontechnology and Rehabilitation, University of Bern, Bern, Switzerland

    Oriella Gnarra & Tobias Nef

Authors
  1. Stefania Ancona
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Francesca D. Faraci
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Elina Khatab
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Luigi Fiorillo
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Oriella Gnarra
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Tobias Nef
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Claudio L. A. Bassetti
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Panagiotis Bargiotas
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Panagiotis Bargiotas.

Ethics declarations

Conflicts of interest

The authors declare that they have no conflict of interest.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (DOCX 14 KB)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ancona, S., Faraci, F.D., Khatab, E. et al. Wearables in the home-based assessment of abnormal movements in Parkinson’s disease: a systematic review of the literature. J Neurol 269, 100–110 (2022). https://doi.org/10.1007/s00415-020-10350-3

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00415-020-10350-3

Keywords

Search

Navigation