ArticleSensors (Basel, Switzerland)2024
2SpamH: A Two-Stage Pre-Processing Algorithm for Passively Sensed mHealth Data.
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 2 papers.
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Who cites it
2 citing papers in PubMed.
- Smartphone-Based Passive Sensing of Activity Levels and Behavioral Activation During Psychosocial Interventions for Older Adults With Depression: Longitudinal Observational Study.Journal of medical Internet research · 2026Observational
- A Co-Segmentation Algorithm to Predict Emotional Stress From Passively Sensed mHealth Data.Statistics in medicine · 2025Article
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Authors and funding
7 authors.
Funding
Abstract
Recent advancements in mobile health (mHealth) technology and the ubiquity of wearable devices and smartphones have expanded a market for digital health and have emerged as innovative tools for data collection on individualized behavior. Heterogeneous levels of device usage across users and across days within a single user may result in different degrees of underestimation in passive sensing data, subsequently introducing biases if analyzed without addressing this issue. In this work, we propose an unsupervised 2-Stage Pre-processing Algorithm for Passively Sensed mHealth Data (2SpamH) algorithm that uses device usage variables to infer the quality of passive sensing data from mobile devices. This article provides a series of simulation studies to show the utility of the proposed algorithm compared to existing methods. Application to a real clinical dataset is also illustrated.
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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.