ArticleJournal of medical systems2020
A Scalable Smartwatch-Based Medication Intake Detection System Using Distributed Machine Learning.
Article in Journal of medical systems, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled 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.
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
18 citing papers in PubMed, 1 synthesis or guideline pooled it, 49 citations in OpenAlex.
- The Use of Artificial Intelligence and Wearable Inertial Measurement Units in Medicine: Systematic Review.JMIR mHealth and uHealth · 2025Pooled it
- Integrating Generative AI Into Patient-Centered Clinical Decision Support: Viewpoint on Research and Practice Considerations.Journal of medical Internet research · 2026Article
- Multimodal Sensing and Modeling of Endocrine Therapy Adherence in Breast Cancer Survivors.Proceedings of the ACM on interactive, mobile, wearable and ubiquitous technologies · 2025Article
- Medication Management Initiatives Using Wearable Devices: Scoping Review.JMIR human factors · 2024Article
- Sea Horse Optimization-Deep Neural Network: A Medication Adherence Monitoring System Based on Hand Gesture Recognition.Sensors (Basel, Switzerland) · 2024Article
- Artificial intelligence, medications, pharmacogenomics, and ethics.Pharmacogenomics · 2024Article
- Detecting Medication-Taking Gestures Using Machine Learning and Accelerometer Data Collected via Smartwatch Technology: Instrument Validation Study.JMIR human factors · 2023Article
- Involvement of Human Volunteers in the Development and Evaluation of Wearable Devices Designed to Improve Medication Adherence: A Scoping Review.Sensors (Basel, Switzerland) · 2023Article
- Digital health technologies to support medication adherence in chronic kidney disease.Nephrology (Carlton, Vic.) · 2022Review
- The use of machine learning to support the therapeutic process - strengths and weaknesses.Postepy psychiatrii neurologii · 2022Review
- Technologies for Medication Adherence Monitoring and Technology Assessment Criteria: Narrative Review.JMIR mHealth and uHealth · 2022Review
- Machine Learning and Medication Adherence: Scoping Review.JMIRx med · 2021Article
- A Genetic Attack Against Machine Learning Classifiers to Steal Biometric Actigraphy Profiles from Health Related Sensor Data.Journal of medical systems · 2020Article
- Digital Health Around Clinical High Risk and First-Episode Psychosis.Current psychiatry reports · 2020Review
- Smart Environments and Social Robots for Age-Friendly Integrated Care Services.International journal of environmental research and public health · 2020Article
- Evaluation of Functional Abilities in 0-6 Year Olds: an Analysis with the eEarlyCare Computer Application.International journal of environmental research and public health · 2020Article
- Article
- Machine learning-based prediction of mortality in lung cancer: Application of severity-adjustment method.Digital healthArticle
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 at 2 institutions in 1 country.
Funding
Abstract
Poor Medication adherence causes significant economic impact resulting in hospital readmission, hospital visits and other healthcare costs. The authors developed a smartwatch application and a cloud based data pipeline for developing a user-friendly medication intake monitoring system that can contribute to improving medication adherence. The developed Android smartwatch application collects activity sensor data using accelerometer and gyroscope. The cloud-based data pipeline includes distributed data storage, distributed database management system and distributed computing frameworks in order to build a machine learning model which identifies activity types using sensor data. With the proposed sensor data extraction, preprocessing and machine learning algorithms, this study successfully achieved a high F1 score of 0.977 with 13.313 seconds of training time and 0.139 seconds for testing.
Indexed as
Identifiers
What OpenQuestion holds
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.