ArticleSensors (Basel, Switzerland)2020
A Decentralized Peer-to-Peer Remote Health Monitoring System.
Article in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 2 of them syntheses 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
8 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Blockchain applications in health care for COVID-19 and beyond: a systematic review.The Lancet. Digital health · 2021Pooled it
- Security Engineering of Patient-Centered Health Care Information Systems in Peer-to-Peer Environments: Systematic Review.Journal of medical Internet research · 2021Pooled it
- Privacy preservation in blockchain-based healthcare data sharing: A systematic review.Peer-to-peer networking and applications · 2025Review
- An optimal peer selection for peer-to-peer video content distribution using fuzzy linear programming approach.PeerJ. Computer science · 2025Article
- A novel fuzzy programming approach for piece selection problem in P2P content distribution network.PeerJ. Computer science · 2024Article
- A Fully Open-Source Approach to Intelligent Edge Computing: AGILE's Lesson.Sensors (Basel, Switzerland) · 2021Article
- Blockchain in Health Care Innovation: Literature Review and Case Study From a Business Ecosystem Perspective.Journal of medical Internet research · 2020Review
- Implementation of High-Performance Blockchain Network Based on Cross-Chain Technology for IoT Applications.Sensors (Basel, Switzerland) · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Within the Internet of Things (IoT) and blockchain research, there is a growing interest in decentralizing health monitoring systems, to provide improved privacy to patients, without relying on trusted third parties for handling patients' sensitive health data. With public blockchain deployments being severely limited in their scalability, and inherently having latency in transaction processing, there is room for researching and developing new techniques to leverage the security features of blockchains within healthcare applications. This paper presents a solution for patients to share their biomedical data with their doctors without their data being handled by trusted third party entities. The solution is built on the Ethereum blockchain as a medium for negotiating and record-keeping, along with Tor for delivering data from patients to doctors. To highlight the applicability of the solution in various health monitoring scenarios, we have considered three use-cases, namely cardiac monitoring, sleep apnoea testing, and EEG following epileptic seizures. Following the discussion about the use cases, the paper outlines a security analysis performed on the proposed solution, based on multiple attack scenarios. Finally, the paper presents and discusses a performance evaluation in terms of data delivery time in comparison to existing centralized and decentralized solutions.
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.