ReviewSensors (Basel, Switzerland)2019
Multiple Physiological Signals Fusion Techniques for Improving Heartbeat Detection: A Review.
Review 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 7 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
7 citing papers in PubMed.
- From G tolerance to physiological state monitoring: mechanisms and adaptive protection.Frontiers in physiology · 2026Review
- A Multimodal System for Comprehensive Cardiovascular Monitoring Using ECG, PCG, and PPG Signal Fusion.Sensors (Basel, Switzerland) · 2025Article
- Robust in-vehicle heartbeat detection using multimodal signal fusion.Scientific reports · 2023Article
- Detection of COVID-19 using multimodal data from a wearable device: results from the first TemPredict Study.Scientific reports · 2022Article
- Hidden Markov model-based heartbeat detector using electrocardiogram and arterial pressure signals.Biomedical engineering letters · 2021Article
- Homology Characteristics of EEG and EMG for Lower Limb Voluntary Movement Intention.Frontiers in neurorobotics · 2021Article
- ECG Monitoring Systems: Review, Architecture, Processes, and Key Challenges.Sensors (Basel, Switzerland) · 2020Review
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
Abstract
This paper presents a review of the techniques found in the literature that aim to achieve a robust heartbeat detection from fusing multi-modal physiological signals (e.g., electrocardiogram (ECG), blood pressure (BP), artificial blood pressure (ABP), stroke volume (SV), photoplethysmogram (PPG), electroencephalogram (EEG), electromyogram (EMG), and electrooculogram (EOG), among others). Techniques typically employ ECG, BP, and ABP, of which usage has been shown to obtain the best performance under challenging conditions. SV, PPG, EMG, EEG, and EOG signals can help increase performance when included within the fusion. Filtering, signal normalization, and resampling are common preprocessing steps. Delay correction between the heartbeats obtained over some of the physiological signals must also be considered, and signal-quality assessment to retain the
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.