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. 2018 Aug;265(8):1740-1752.
doi: 10.1007/s00415-018-8786-y. Epub 2018 Feb 9.

Wearable sensors for clinical applications in epilepsy, Parkinson's disease, and stroke: a mixed-methods systematic review

Dongni Johansson  1 , Kristina Malmgren  2 , Margit Alt Murphy  2
Affiliations

Wearable sensors for clinical applications in epilepsy, Parkinson's disease, and stroke: a mixed-methods systematic review

Dongni Johansson et al. J Neurol. 2018 Aug.

Abstract

Objectives: Wearable technology is increasingly used to monitor neurological disorders. The purpose of this systematic review was to synthesize knowledge from quantitative and qualitative clinical researches using wearable sensors in epilepsy, Parkinson's disease (PD), and stroke.

Methods: A systematic literature search was conducted in PubMed and Scopus spanning from 1995 to January 2017. A synthesis of the main findings, reported adherence to wearables and missing data from quantitative studies, is provided. Clinimetric properties of measures derived from wearables in laboratory, free activities in hospital, and free-living environment were also evaluated. Qualitative thematic synthesis was conducted to explore user experiences and acceptance of wearables.

Results: In total, 56 studies (50 reporting quantitative and 6 reporting qualitative data) were included for data extraction and synthesis. Among studies reporting quantitative data, 5 were in epilepsy, 21 PD, and 24 studies in stroke. In epilepsy, wearables are used to detect and differentiate seizures in hospital settings. In PD, the focus is on quantification of cardinal motor symptoms and medication-evoked adverse symptoms in both laboratory and free-living environment. In stroke upper extremity activity, walking and physical activity have been studied in laboratory and during free activities. Three analytic themes emerged from thematic synthesis of studies reporting qualitative data: acceptable integration in daily life, lack of confidence in technology, and the need to consider individualization.

Conclusions: Wearables may provide information of clinical features of interest in epilepsy, PD and stroke, but knowledge regarding the clinical utility for supporting clinical decision making remains to be established.

Keywords: Epilepsy; Parkinson’s disease; Stroke; Systematic review; Wearable sensors.

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Conflict of interest statement

None of the authors report any conflicts of interest with regard to the present study.

Figures

Fig. 1
Fig. 1
Flow diagram of the systematic review selection process
Fig. 2
Fig. 2
Reported outcomes of measures derived from wearables applied in epilepsy, PD, and stroke. GTCS generalized tonic–clonic seizures, PNES pshychogenic non-epileptic seizures, PD Parkinson’s disease, Sens sensitivity, Spec specificity, COP center of pressure, ICC intraclass correlations, PSG polysomnography, OMCS optical motion capture system, ARAT the Action Research Arm Test, MAL The Motor Activity Log, FMA Fugl–Meyer Assessment, NIHSS the Nation Institutes of Health Stroke Scale, UPDRS Unified Parkinson’s Disease Rating Scale, MiniBEST Mini Balance Evaluation Systems Test, PIGD postural instability and gait disorder, UDysRS Unified Dyskinesia Rating Scale, mAIMS modified Abnormal Involuntary Movement Scale, CDRS Clinical Dyskinesia Rating Scale. *Mean value is presented; §Negative correlation is shown
Fig. 3
Fig. 3
a Adherence of continuous monitoring using wearables. b Reported missing data due to technical errors and/or insufficient time of wearing or person related reasons. Mean data is presented. #Adherence rate is shown
See this image and copyright information in PMC

References

    1. Steins D, Dawes H, Esser P, Collett J. Wearable accelerometry-based technology capable of assessing functional activities in neurological populations in community settings: a systematic review. J Neuroeng Rehabil. 2014;11:36. doi: 10.1186/1743-0003-11-36. - DOI - PMC - PubMed
    1. Ramgopal S, Thome-Souza S, Jackson M, Kadish NE, Sanchez Fernandez I, Klehm J, Bosl W, Reinsberger C, Schachter S, Loddenkemper T. Seizure detection, seizure prediction, and closed-loop warning systems in epilepsy. Epilepsy Behav. 2014;37:291–307. doi: 10.1016/j.yebeh.2014.06.023. - DOI - PubMed
    1. Ozanne A, Johansson D, Hallgren Graneheim U, Malmgren K, Bergquist F, Alt Murphy M. Wearables in epilepsy and Parkinson’s disease—a focus group study. Acta Neurol Scand. 2017 - PubMed
    1. Richardson WS, Wilson MC, Nishikawa J, Hayward RS. The well-built clinical question: a key to evidence-based decisions. ACP J Club. 1995;123(3):A12–A13. - PubMed
    1. Cooke A, Smith D, Booth A. Beyond PICO: the SPIDER tool for qualitative evidence synthesis. Qual Health Res. 2012;22(10):1435–1443. doi: 10.1177/1049732312452938. - DOI - PubMed

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