ArticleMicromachines2018
Activity Monitoring with a Wrist-Worn, Accelerometer-Based Device.
Article in Micromachines, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
What it found
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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
14 citing papers in PubMed.
- SE-Res-U-Net: an improved U-Net architecture for efficient sleep state detection and classification.Scientific reports · 2025Article
- Differential Patterns in Motivations for Practicing Sport and Their Effects on Physical Activity Engagement across the Lifespan.Healthcare (Basel, Switzerland) · 2023Article
- Applications of Smart Material Sensors and Soft Electronics in Healthcare Wearables for Better User Compliance.Micromachines · 2022Review
- Article
- Wrist Photoplethysmography Signal Quality Assessment for Reliable Heart Rate Estimate and Morphological Analysis.Sensors (Basel, Switzerland) · 2022Article
- Proof of Concept in Artificial-Intelligence-Based Wearable Gait Monitoring for Parkinson's Disease Management Optimization.Biosensors · 2022Article
- Connection between sleeping patterns and cognitive deterioration in women with Alzheimer's disease.Sleep & breathing = Schlaf & Atmung · 2022Article
- Article
- Quality Assessment and Morphological Analysis of Photoplethysmography in Daily Life.Frontiers in digital health · 2022Article
- Review of Wearable Devices and Data Collection Considerations for Connected Health.Sensors (Basel, Switzerland) · 2021Review
- Virtual Reality in Home Palliative Care: Brief Report on the Effect on Cancer-Related Symptomatology.Frontiers in psychology · 2021Article
- Design and Implementation of a Multifunction Wearable Device to Monitor Sleep Physiological Signals.Micromachines · 2020Article
- Prediction of 30-Day Readmission for COPD Patients Using Accelerometer-Based Activity Monitoring.Sensors (Basel, Switzerland) · 2019Article
- Editorial for the Special Issue on MEMS Accelerometers.Micromachines · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
This study condenses huge amount of raw data measured from a MEMS accelerometer-based, wrist-worn device on different levels of physical activities (PAs) for subjects wearing the device 24 h a day continuously. In this study, we have employed the device to build up assessment models for quantifying activities, to develop an algorithm for sleep duration detection and to assess the regularity of activity of daily living (ADL) quantitatively. A new parameter, the activity index (AI), has been proposed to represent the quantity of activities and can be used to categorize different PAs into 5 levels, namely, rest/sleep, sedentary, light, moderate, and vigorous activity states. Another new parameter, the regularity index (RI), was calculated to represent the degree of regularity for ADL. The methods proposed in this study have been used to monitor a subject's daily PA status and to access sleep quality, along with the quantitative assessment of the regularity of activity of daily living (ADL) with the 24-h continuously recorded data over several months to develop activity-based evaluation models for different medical-care applications. This work provides simple models for activity monitoring based on the accelerometer-based, wrist-worn device without trying to identify the details of types of activity and that are suitable for further applications combined with cloud computing services.
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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.