ArticleSensors (Basel, Switzerland)2024
Comparative Assessment of Multimodal Sensor Data Quality Collected Using Android and iOS Smartphones in Real-World Settings.
Article in Sensors (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 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.
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Who cites it
4 citing papers in PubMed.
- Wearable-Based Assessment for Relapse Prediction Following Repetitive Transcranial Magnetic Stimulation for Depression: Protocol for a Feasibility Study (WARN-D Study).JMIR research protocols · 2026Article
- National implementation of a digital Parkinson's disease screening programme in Thailand: reach, adoption, and real-world performance of the CheckPD app.BMC public health · 2026Article
- A Neurosurgeon's Guide to Mobile Health Application Development With a Case Study for Cervical Myelopathy.Neurosurgery · 2026Article
- Measuring Walking Stability with a Mobile Phone in Older Adults: A Validation Study.Sensors (Basel, Switzerland) · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
Abstract
Healthcare researchers are increasingly utilizing smartphone sensor data as a scalable and cost-effective approach to studying individualized health-related behaviors in real-world settings. However, to develop reliable and robust digital behavioral signatures that may help in the early prediction of the individualized disease trajectory and future prognosis, there is a critical need to quantify the potential variability that may be present in the underlying sensor data due to variations in the smartphone hardware and software used by large population. Using sensor data collected in real-world settings from 3000 participants' smartphones for up to 84 days, we compared differences in the completeness, correctness, and consistency of the three most common smartphone sensors-the accelerometer, gyroscope, and GPS- within and across Android and iOS devices. Our findings show considerable variation in sensor data quality within and across Android and iOS devices. Sensor data from iOS devices showed significantly lower levels of anomalous point density (APD) compared to Android across all sensors (
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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 Socratic graph.