Evidence map›Paper›PMID 35200335›Full record

ArticleBiosensors2022

Quantification Analysis of Sleep Based on Smartwatch Sensors for Parkinson's Disease.

Yi-Feng Ko, Pei-Hsin Kuo, Ching-Fu Wang, Yu-Jen Chen, Pei-Chi Chuang, Shih-Zhang Li, Bo-Wei Chen, Fu-Chi Yang, Yu-Chun Lo, Yi Yang and 4 more

Open access · goldAbstract readControlled Clinical Trial
PubMed Full text at PMC Publisher
In one paragraph

Article in Biosensors, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed, 1 pooled it
4.7field-weighted citation impact, top 4% 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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

22 citing papers in PubMed, 1 synthesis or guideline pooled it, 40 citations in OpenAlex.

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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

14 authors at 6 institutions in 2 countries.

Yi-Feng KoDepartment of Biomedical Engineering, National Taiwan University, Taipei 10617, Taiwan.ORCID 0000-0003-3422-3889
Pei-Hsin KuoDepartment of Neurology, Hualien Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation, Hualien 97002, Taiwan.
Ching-Fu WangDepartment of Biomedical Engineering, National Yang Ming Chiao Tung University, Taipei 11221, Taiwan.ORCID 0000-0001-5874-6591
Yu-Jen ChenDepartment of Healthcare Solution FW R&D, ASUSTeK Computer Incrporation, Taipei 11259, Taiwan.
Pei-Chi ChuangDepartment of Healthcare Solution FW R&D, ASUSTeK Computer Incrporation, Taipei 11259, Taiwan.
Shih-Zhang LiDepartment of Biomedical Engineering, National Yang Ming Chiao Tung University, Taipei 11221, Taiwan.
Bo-Wei ChenDepartment of Biomedical Engineering, National Yang Ming Chiao Tung University, Taipei 11221, Taiwan.
Fu-Chi YangSchool of Health Care Administration, Taipei Medical University, Taipei 11031, Taiwan.ORCID 0000-0003-1835-2808
Yu-Chun LoThe Ph.D. Program for Neural Regenerative Medicine, Taipei Medical University, Taipei 11031, Taiwan.
Yi YangDepartment of Biomedical Engineering, National Yang Ming Chiao Tung University, Taipei 11221, Taiwan.
Shuan-Chu Vina RoDepartment of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, MD 21205, USA.
Fu-Shan JawDepartment of Biomedical Engineering, National Taiwan University, Taipei 10617, Taiwan.
Sheng-Huang LinDepartment of Neurology, Hualien Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation, Hualien 97002, Taiwan.
You-Yin ChenDepartment of Biomedical Engineering, National Yang Ming Chiao Tung University, Taipei 11221, Taiwan.
National Yang Ming Chiao Tung University · TWNational Taiwan University · TWTaipei Medical University · TWTzu Chi University · TWAsus (Taiwan) · TWJohns Hopkins University · US

Funding

Hualien Tzu Chi Medical Center TCRD 107-29
6 · The paper itself

Abstract

Rapid eye movement (REM) sleep behavior disorder (RBD) is associated with Parkinson's disease (PD). In this study, a smartwatch-based sensor is utilized as a convenient tool to detect the abnormal RBD phenomenon in PD patients. Instead, a questionnaire with sleep quality assessment and sleep physiological indices, such as sleep stage, activity level, and heart rate, were measured in the smartwatch sensors. Therefore, this device can record comprehensive sleep physiological data, offering several advantages such as ubiquity, long-term monitoring, and wearable convenience. In addition, it can provide the clinical doctor with sufficient information on the patient's sleeping patterns with individualized treatment. In this study, a three-stage sleep staging method (i.e., comprising sleep/awake detection, sleep-stage detection, and REM-stage detection) based on an accelerometer and heart-rate data is implemented using machine learning (ML) techniques. The ML-based algorithms used here for sleep/awake detection, sleep-stage detection, and REM-stage detection were a Cole-Kripke algorithm, a stepwise clustering algorithm, and a k-means clustering algorithm with predefined criteria, respectively. The sleep staging method was validated in a clinical trial. The results showed a statistically significant difference in the percentage of abnormal REM between the control group (1.6 ± 1.3;

Indexed as

ClonazepamParkinson DiseaseREM Sleep Behavior DisorderAlgorithmsHumansSleepClonazepammachine learningParkinson’s diseaseREM sleep behavior disordersmartwatch sensors

Identifiers

PMID35200335
PMCPMC8869576
OpenAlexW4210806878

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.