Evidence map›Paper›PMID 29427026›Full record

SynthesisJournal of neurology2018

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

Dongni Johansson, Kristina Malmgren, Margit Alt Murphy

Registry-linked trialOpen access · hybridAbstract readSystematic Review
PubMed Full text at PMC Publisher
In one paragraph

Synthesis in Journal of neurology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04291716 (Validation of an Algorithm for Identification and Notification of Generalized Major Motor Seizures), which is not on this map. Cited by 81 papers, 12 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
81citing papers in PubMed, 12 pooled it
13.2field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT04291716 naunknown statusnot on this mapstarted 2020, after this paper: background citation

Validation of an Algorithm for Identification and Notification of Generalized Major Motor Seizures

TypeinterventionalSponsorOverwatch Digital HealthRan2020 to 2020Enrolled15ConditionsSeizures, Motor, Seizures, Seizure Disorder, EpilepsyArmsMotor Seizure Detection Algorithm (mSDA)
3 · Its place in the literature

Who cites it

81 citing papers in PubMed, 12 syntheses or guidelines pooled it, 193 citations in OpenAlex.

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  18. Wearable Artificial Intelligence for Epilepsy: Scoping Review.Journal of medical Internet research · 2025
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21 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 1 institution in 1 country.

Dongni JohanssonDepartment of Clinical Neuroscience, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden. dongni.johansson@gu.se.ORCID http://orcid.org/0000-0003-3152-9508
Kristina MalmgrenDepartment of Clinical Neuroscience, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
Margit Alt MurphyDepartment of Clinical Neuroscience, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
University of Gothenburg · SE

Funding

Stiftelsen för Strategisk Forskning grant SBE 13-0086Västra Götalandsregionen grant ALFGBG-429901
6 · The paper itself

Abstract

objectivesWearable 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.

methodsA 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.

resultsIn 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.

conclusionsWearables 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.

Indexed as

Wearable Electronic DevicesEpilepsyHumansParkinson DiseaseStrokeEpilepsyParkinson’s diseaseStrokeSystematic reviewWearable sensors

Identifiers

PMID29427026
PMCPMC6060770
OpenAlexW2789915296

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.