[HTML][HTML] Information fusion and artificial intelligence for smart healthcare: a bibliometric study

X Chen, H **e, Z Li, G Cheng, M Leng… - Information Processing & …, 2023 - Elsevier
With the fast progress in information technologies and artificial intelligence (AI), smart
healthcare has gained considerable momentum. By using advanced technologies like AI …

Toward a robust estimation of respiratory rate from pulse oximeters

MAF Pimentel, AEW Johnson… - IEEE Transactions …, 2016 - ieeexplore.ieee.org
Goal: Current methods for estimating respiratory rate (RR) from the photoplethysmogram
(PPG) typically fail to distinguish between periods of high-and low-quality input data, and fail …

A review of methods for the signal quality assessment to improve reliability of heart rate and blood pressures derived parameters

N Gambarotta, F Aletti, G Baselli, M Ferrario - Medical & biological …, 2016 - Springer
The assessment of signal quality has been a research topic since the late 1970s, as it is
mainly related to the problem of false alarms in bedside monitors in the intensive care unit …

Multiple physiological signals fusion techniques for improving heartbeat detection: A review

J Tejedor, CA García, DG Márquez, R Raya, A Otero - Sensors, 2019 - mdpi.com
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 (eg …

Robust heartbeat detection from multimodal data via CNN-based generalizable information fusion

BS Chandra, CS Sastry, S Jana - IEEE Transactions on …, 2018 - ieeexplore.ieee.org
Objective: Heartbeat detection remains central to cardiac disease diagnosis and
management, and is traditionally performed based on electrocardiogram (ECG). To improve …

Control synthesis of hidden semi-Markov uncertain fuzzy systems via observations of hidden modes

B Cai, L Zhang, Y Shi - IEEE Transactions on Cybernetics, 2019 - ieeexplore.ieee.org
This paper investigates the stability analysis and fuzzy control problems for a class of
discrete-time fuzzy systems with hidden semi-Markov stochastic uncertainties. The nonlinear …

A robust fusion model for estimating respiratory rate from photoplethysmography and electrocardiography

DA Birrenkott, MAF Pimentel… - IEEE Transactions …, 2017 - ieeexplore.ieee.org
Objective: Respiratory rate (RR) estimation algorithms based on the photoplethymogram
(PPG) and electrocardiogram (ECG) lack clinical robustness. This is because the PPG and …

Accelerometry-based estimation of respiratory rate for post-intensive care patient monitoring

D Jarchi, SJ Rodgers, L Tarassenko… - IEEE Sensors …, 2018 - ieeexplore.ieee.org
This paper evaluates the use of accelerometers for continuous monitoring of respiratory rate
(RR), which is an important vital sign in post-intensive care patients or those inside the …

Non-invasive fetal ECG signal quality assessment for multichannel heart rate estimation

F Andreotti, F Gräßer, H Malberg… - IEEE Transactions on …, 2017 - ieeexplore.ieee.org
Objective: The noninvasive fetal ECG (NIFECG) from abdominal recordings offers novel
prospects for prenatal monitoring. However, NI-FECG signals are corrupted by various …

Reduction of false arrhythmia alarms using signal selection and machine learning

LM Eerikäinen, J Vanschoren… - Physiological …, 2016 - iopscience.iop.org
In this paper, we propose an algorithm that classifies whether a generated cardiac
arrhythmia alarm is true or false. The large number of false alarms in intensive care is a …