ArticleBiosensors2025
Wearable Sensors for Sleep Monitoring in Free-Living Environments: A Scoping Review on Parkinson's Disease.
Article in Biosensors, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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.
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.
Who cites it
3 citing papers in PubMed.
- Associations Between Daily Step Counts and Sleep Parameters in Parkinson's Disease: A Scoping Review.Sensors (Basel, Switzerland) · 2025Article
- The relation between passively collected data and PTSD: a systematic review and meta-analysis.NPJ digital medicine · 2025Article
- Exercise modulation of BDNF/TrkB signaling in Parkinson's disease: an evidence-calibrated review of neuroprotective mechanisms, biomarker limitations, and translational gaps.Frontiers in neurologyReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Parkinson's disease (PD) is a neurodegenerative disorder that affects multiple neural pathways, leading to a broad spectrum of motor and non-motor symptoms. Sleep disorders, such as insomnia and excessive daytime sleepiness, are prevalent among PD patients and significantly impact symptomatology and patients' quality of life. Wearable technology presents an opportunity to study these interactions in patients' daily life environments without the limitations of in-clinic sleep studies. Thus, this review aims to explore how wearable technology has been employed or developed for the sleep monitoring of PD patients in free-living environments. A comprehensive search was conducted across PubMed, Scopus, and IEEE Xplore to identify original research articles focusing on wearable sleep technology for the ambulatory monitoring of PD patients. Twenty-six studies fulfilled the inclusion criteria and underwent structured data extraction and quality assessment. Key aspects analysed included subject demographics, extracted sleep parameters, identified sleep disorders, and the application of machine-learning algorithms. Wearable devices could offer a practical solution for long-term sleep monitoring in PD, though further validation is needed. The absence of standardised protocols and the lack of device validation within PD populations remain significant challenges. The evidence gathered in this study remains insufficient to define a standardised protocol for sleep assessment of PD patients in free-living environments.
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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.