A real time algorithm for the portable recording of fetal and maternal heart rates

2002 ◽  
Author(s):  
F. Ahmed ◽  
M.A.M. Ali ◽  
E. Zahedi
Keyword(s):  
Real Time ◽  
Time Algorithm ◽  
Heart Rates

scholarly journals Real-Time Cardiac Beat Detection and Heart Rate Monitoring from Combined Seismocardiography and Gyrocardiography

Sensors ◽  
2019 ◽  
Vol 19 (16) ◽  
pp. 3472 ◽  
Author(s):  
D’Mello ◽  
Skoric ◽  
Xu ◽  
Roche ◽  
Lortie ◽  
...  
Keyword(s):  
Heart Rate ◽  
Real Time ◽  
Time Algorithm ◽  
Cardiac Monitoring ◽  
Computational Time ◽  
Heart Rate Monitoring ◽  
Heart Rates ◽  
Non Invasive ◽  
Beat Detection ◽  
Speed Accuracy

Cardiography is an indispensable element of health care. However, the accessibility of at-home cardiac monitoring is limited by device complexity, accuracy, and cost. We have developed a real-time algorithm for heart rate monitoring and beat detection implemented in a custom-built, affordable system. These measurements were processed from seismocardiography (SCG) and gyrocardiography (GCG) signals recorded at the sternum, with concurrent electrocardiography (ECG) used as a reference. Our system demonstrated the feasibility of non-invasive electro-mechanical cardiac monitoring on supine, stationary subjects at a cost of $100, and with the SCG–GCG and ECG algorithms decoupled as standalone measurements. Testing was performed on 25 subjects in the supine position when relaxed, and when recovering from physical exercise, to record 23,984 cardiac cycles at heart rates in the range of 36–140 bpm. The correlation between the two measurements had r2 coefficients of 0.9783 and 0.9982 for normal (averaged) and instantaneous (beat identification) heart rates, respectively. At a sampling frequency of 250 Hz, the average computational time required was 0.088 s per measurement cycle, indicating the maximum refresh rate. A combined SCG and GCG measurement was found to improve accuracy due to fundamentally different noise rejection criteria in the mutually orthogonal signals. The speed, accuracy, and simplicity of our system validated its potential as a real-time, non-invasive, and affordable solution for outpatient cardiac monitoring in situations with negligible motion artifact.

A Distributed Real-Time Algorithm for Preference-Based Agreement

2011 ◽  
Vol 44 (1) ◽  
pp. 8933-8938
Author(s):  
Daniel Zelazo ◽  
Mathias Bürger ◽  
Frank Allgöwer
Keyword(s):  
Real Time ◽  
Time Algorithm

scholarly journals Real-Time Algorithm for Versatile Displacement Sensors Based on Self-Mixing Interferometry

2016 ◽  
Vol 16 (1) ◽  
pp. 195-202 ◽  
Author(s):  
Antonio Luna Arriaga ◽  
Francis Bony ◽  
Thierry Bosch
Keyword(s):  
Real Time ◽  
Time Algorithm ◽  
Displacement Sensors

Detecting Pedestrian Situation Awareness in Real-Time: Algorithm Development Using Heart Rate Variability and Phone Position

2018 ◽  
Vol 62 (1) ◽  
pp. 1579-1583
Author(s):  
Yourui Tong ◽  
Bochen Jia ◽  
Yi Wang ◽  
Si Yang
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Real Time ◽  
Situation Awareness ◽  
Mental State ◽  
Time Algorithm ◽  
Support Vector ◽  
Vehicle Design ◽  
Automated Vehicle ◽  
Hrv Analysis

To help automated vehicles learn surrounding environments via V2X communications, it is important to detect and transfer pedestrian situation awareness to the related vehicles. Based on the characteristics of pedestrians, a real-time algorithm was developed to detect pedestrian situation awareness. In the study, the heart rate variability (HRV) and phone position were used to understand the mental state and distractions of pedestrians. The HRV analysis was used to detect the fatigue and alert state of the pedestrian, and the phone position was used to define the phone distractions of the pedestrian. A Support Vector Machine algorithm was used to classify the pedestrian’s mental state. The results indicated a good performance with 86% prediction accuracy. The developed algorithm shows high applicability to detect the pedestrian’s situation awareness in real-time, which would further extend our understanding on V2X employment and automated vehicle design.

A real-time algorithm for fault identification in machining centres

2011 ◽  
Vol 44 (1) ◽  
pp. 5201-5206 ◽  
Author(s):  
L. Ferrarini ◽  
M. Allevi ◽  
A. Dedè
Keyword(s):  
Real Time ◽  
Time Algorithm ◽  
Fault Identification

scholarly journals Aggressive, Tense or Shy? Identifying Personality Traits from Crowd Videos

2017 ◽  
Author(s):  
Aniket Bera ◽  
Tanmay Randhavane ◽  
Dinesh Manocha
Keyword(s):  
Personality Traits ◽  
Real Time ◽  
Personality Trait ◽  
User Study ◽  
Movement Patterns ◽  
Time Algorithm ◽  
High Density ◽  
Motion Model ◽  
Classification Criterion ◽  
Trait Theory

We present a real-time algorithm to automatically classify the behavior or personality of a pedestrian based on his or her movements in a crowd video. Our classification criterion is based on Personality Trait theory. We present a statistical scheme that dynamically learns the behavior of every pedestrian and computes its motion model. This model is combined with global crowd characteristics to compute the movement patterns and motion dynamics and use them for crowd prediction. Our learning scheme is general and we highlight its performance in identifying the personality of different pedestrians in low and high density crowd videos. We also evaluate the accuracy by comparing the results with a user study.

scholarly journals A Flexible, Real-Time Algorithm for Simulating Correlated Random Fields and Its Properties

2017 ◽  
Vol 13 (3) ◽  
pp. 197-208 ◽  
Author(s):  
Michael A. Kouritzin ◽  
Fraser Newton ◽  
Biao Wu
Keyword(s):  
Real Time ◽  
Random Fields ◽  
Time Algorithm
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