ArticleSensors (Basel, Switzerland)2019
Wearable IoT Smart-Log Patch: An Edge Computing-Based Bayesian Deep Learning Network System for Multi Access Physical Monitoring System.
Article in Sensors (Basel, Switzerland), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 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
19 citing papers in PubMed, 213 citations in OpenAlex.
- Smart patches for healthcare industry: a review of emerging technologies, challenges, and developmental opportunities.Biomedical engineering online · 2026Review
- Leveraging Classifier Performance Using Heuristic Optimization for Detecting Cardiovascular Disease from PPG Signals.Diagnostics (Basel, Switzerland) · 2024Article
- Integrating OpenPose and SVM for Quantitative Postural Analysis in Young Adults: A Temporal-Spatial Approach.Bioengineering (Basel, Switzerland) · 2024Article
- Football teaching and training based on video surveillance using deep learning.Technology and health care : official journal of the European Society for Engineering and Medicine · 2024Article
- Machine Learning Electrocardiogram for Mobile Cardiac Pattern Extraction.Sensors (Basel, Switzerland) · 2023Article
- A Review of Artificial Intelligence in Embedded Systems.Micromachines · 2023Review
- At the Confluence of Artificial Intelligence and Edge Computing in IoT-Based Applications: A Review and New Perspectives.Sensors (Basel, Switzerland) · 2023Review
- Deep Neural Network for the Detections of Fall and Physical Activities Using Foot Pressures and Inertial Sensing.Sensors (Basel, Switzerland) · 2023Article
- Identifying the Posture of Young Adults in Walking Videos by Using a Fusion Artificial Intelligent Method.Biosensors · 2022Article
- Wearables and their applications for the rehabilitation of elderly people.Medical & biological engineering & computing · 2022Review
- Real-time tracking and detection of patient conditions in the intelligent m-Health monitoring system.Frontiers in public health · 2022Article
- Detection of Cardiovascular Disease Based on PPG Signals Using Machine Learning with Cloud Computing.Computational intelligence and neuroscience · 2022Article
- Mucosa-interfacing electronics.Nature reviews. Materials · 2022Review
- Wearable Edge AI Applications for Ecological Environments.Sensors (Basel, Switzerland) · 2021Article
- A Generalization Performance Study Using Deep Learning Networks in Embedded Systems.Sensors (Basel, Switzerland) · 2021Article
- Artificial Intelligence in Nutrients Science Research: A Review.Nutrients · 2021Review
- A bird's-eye view of brain activity in socially interacting mice through mobile edge computing (MEC).Science advances · 2020Article
- A Wristwatch-Based Wireless Sensor Platform for IoT Health Monitoring Applications.Sensors (Basel, Switzerland) · 2020Article
- Wearables Meet IoT: Synergistic Personal Area Networks (SPANs).Sensors (Basel, Switzerland) · 2019Review
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 at 7 institutions in 6 countries.
Funding
Abstract
According to the survey on various health centres, smart log-based multi access physical monitoring system determines the health conditions of humans and their associated problems present in their lifestyle. At present, deficiency in significant nutrients leads to deterioration of organs, which creates various health problems, particularly for infants, children, and adults. Due to the importance of a multi access physical monitoring system, children and adolescents' physical activities should be continuously monitored for eliminating difficulties in their life using a smart environment system. Nowadays, in real-time necessity on multi access physical monitoring systems, information requirements and the effective diagnosis of health condition is the challenging task in practice. In this research, wearable smart-log patch with Internet of Things (IoT) sensors has been designed and developed with multimedia technology. Further, the data computation in that smart-log patch has been analysed using edge computing on Bayesian deep learning network (EC-BDLN), which helps to infer and identify various physical data collected from the humans in an accurate manner to monitor their physical activities. Then, the efficiency of this wearable IoT system with multimedia technology is evaluated using experimental results and discussed in terms of accuracy, efficiency, mean residual error, delay, and less energy consumption. This state-of-the-art smart-log patch is considered as one of evolutionary research in health checking of multi access physical monitoring systems with multimedia technology.
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.