MFC histogram and Poincare plot images for automated gait detection

2004 ◽  
Author(s):  
R. Begg ◽  
M. Palaniswam ◽  
B. Owen ◽  
S. Taylor ◽  
L. Dell'Oro
Keyword(s):  
Poincaré Plot

scholarly journals Heart Rate Variability Monitoring during Interferential Current Application in the Lower Back Area: A Cross-Sectional Study

2021 ◽  
Vol 18 (7) ◽  
pp. 3394
Author(s):  
Blanca De-la-Cruz-Torres ◽  
Eva Martínez-Jiménez ◽  
Emmanuel Navarro-Flores ◽  
Patricia Palomo-López ◽  
Vanesa Abuín-Porras ◽  
...  
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Placebo Group ◽  
Intervention Group ◽  
Lumbar Pain ◽  
Poincaré Plot ◽  
Current Application ◽  
Cross Sectional ◽  
Vasovagal Reactions ◽  
Interferential Current

Vasovagal reactions may occur occasionally during electrical stimulation using interferential current (IFC). The purpose of this study was to examine variations in autonomic activity during the application of IFC in asymptomatic participants by analysis of their heart rate variability (HRV). Seventy-three male volunteers were randomly assigned to a placebo group (n = 36; HRV was documented for 10 min, both at rest and during a placebo intervention) and an intervention group (n = 37; HRV was documented for 10 min in two conditions labelled as (1) rest and (2) application of IFC technique on the lumbar segment). The diameters of the Poincaré plot (SD1, SD2), stress score (SS), and the ratio between sympathetic and parasympathetic activity (S/PS) were measured. After interventions, differences amongst the placebo group and the IFC group were found in SD2 (p < 0.001), SS (p = 0.01) and S/PS ratio (p = 0.003). The IFC technique was associated with increased parasympathetic modulation, which could induce a vasovagal reaction. Monitorization of adverse reactions should be implemented during the application of IFC technique. HRV indicators might have a part in prevention of vasovagal reactions. Further studies in patients with lumbar pain are needed to explore possible differences in HRV responses due to the presence of chronic pain.

scholarly journals Cardiac Parasympathetic Withdrawal and Sympathetic Activity: Effect of Heat Exposure on Heart Rate Variability

2021 ◽  
Vol 18 (11) ◽  
pp. 5934
Author(s):  
Oriol Abellán-Aynés ◽  
Pedro Manonelles ◽  
Fernando Alacid
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Environmental Conditions ◽  
Sympathetic Activity ◽  
Heat Exposure ◽  
Repeated Measurements ◽  
Control Group ◽  
Poincaré Plot ◽  
Activity Effect ◽  
And Control

(1) Background: Research on heart rate variability has increased in recent years and the temperature has not been controlled in some studies assessing repeated measurements. This study aimed to analyze how heart rate variability may change based on environmental temperature during measurement depending on parasympathetic and sympathetic activity variations. (2) Methods: A total of 22 volunteers participated in this study divided into an experimental (n = 12) and control group (n = 10). Each participant was assessed randomly under two different environmental conditions for the experimental group (19 °C and 35 °C) and two identical environmental conditions for the control group (19 °C). During the procedure, heart rate variability measurements were carried out for 10 min. (3) Results: Significantly changes were observed for time and frequency domains as well as Poincaré plot variables after heat exposure (p < 0.05). These findings were not observed in the control group, whose conditions between measurements did not change. (4) Conclusions: The reduction of heart rate variability due to exposure to hot conditions appears to be produced mostly by a parasympathetic withdrawal rather than a sympathetic activation. Therefore, if consecutive measurements have to be carried out, these should always be done under the same temperature conditions.

scholarly journals Fault severity detection of a worm gearbox based on several feature extraction methods through a developed condition monitoring system

2021 ◽  
Vol 3 (1) ◽  
Author(s):  
Berkan Hızarcı ◽  
Rafet Can Ümütlü ◽  
Zeki Kıral ◽  
Hasan Öztürk
Keyword(s):  
Fault Detection ◽  
Condition Monitoring ◽  
Extraction Methods ◽  
Poincaré Plot ◽  
Vibration Data ◽  
Sliding Motion ◽  
Fault Severity ◽  
Fault Features ◽  
Gearbox Vibration ◽  
Condition Monitoring System

AbstractThis study presents the severity detection of pitting faults on worm gearbox through the assessment of fault features extracted from the gearbox vibration data. Fault severity assessment on worm gearbox is conducted by the developed condition monitoring instrument with observing not only traditional but also multidisciplinary features. It is well known that the sliding motion between the worm gear and wheel gear causes difficulties about fault detection on worm gearboxes. Therefore, continuous monitoring and observation of different types of fault features are very important, especially for worm gearboxes. Therefore, in this study, time-domain statistics, the features of evaluated vibration analysis method and Poincaré plot are examined for fault severity detection on worm gearbox. The most reliable features for fault detection on worm gearbox are determined via the parallel coordinate plot. The abnormality detection during worm gearbox operation with the developed system is performed successfully by means of a decision tree.

Análisis de la Variabilidad de la Frecuencia Cardiaca durante Entrenamiento Físico de Distinta Intensidad a través de Índices de la Gráfica de Poincaré

2021 ◽  
Author(s):  
◽  
V. J. Martínez Hernández
Keyword(s):  
Cardiovascular Health ◽  
Autonomic Function ◽  
Moderate Intensity ◽  
Vagal Activity ◽  
Cardiac Autonomic Function ◽  
Test Protocol ◽  
Poincaré Plot ◽  
Control Stage ◽  
Control Exercise

Exercise induces parasympathetic withdrawal and sympathetic activation. Heart rate variability (HRV) is a noninvasive tool for the assessment of cardiac autonomic function. Physical training can improve cardiovascular health through an increase in HRV. In this study, two physical trainings were conducted, one with moderate intensity (MT) and the second one with higher intensity (IT), for 10 weeks. A test protocol which consisted of 3 maneuvers: control, exercise, and recovery was performed each week of training to follow up the HRV changes in 18 sedentary volunteers aged 20.3±2 years. The RR intervals were analyzed by indexes of traditional Poincaré plot (SPP) and segmented Poincaré plot (SEPP). The results showed an increase in column 7 probabilities in week 10 with respect to week 4 during control stage for both trainings. Regarding, trainings differences, row 9 probability decreases in MT training suggesting a higher cardiac vagal activity in this training.

Heart Rate Asymmetry Analysis Using Poincaré Plot

2013 ◽  
pp. 69-91
Author(s):  
Ahsan Habib Khandoker ◽  
Chandan Karmakar ◽  
Michael Brennan ◽  
Andreas Voss ◽  
Marimuthu Palaniswami
Keyword(s):  
Heart Rate ◽  
Poincaré Plot ◽  
Asymmetry Analysis ◽  
Rate Asymmetry ◽  
Heart Rate Asymmetry

TECHNIQUES TO ENHANCE FLUID MICRO-MIXING AND CHAOTIC MICROMIXERS

2005 ◽  
Vol 19 (28n29) ◽  
pp. 1567-1570 ◽  
Author(s):  
Y. T. CHEW ◽  
H. M. XIA ◽  
C. SHU ◽  
S. Y. M. WAN
Keyword(s):  
Chaotic Advection ◽  
Chaotic Mixing ◽  
Inertial Effects ◽  
Passive Mixer ◽  
Poincaré Plot ◽  
Mixer Design ◽  
Recent Developments ◽  
Fast Development ◽  
Active Mixing ◽  
Working Mechanisms

With fast development of microfluidic systems, fluid micro-mixing becomes a very important issue. In this paper, recent developments on various micromixers and their working mechanisms are reviewed, including the external agitation methods applied in active mixing and the channel geometries adopted in passive mixer design. The chaotic mixing and the influences of Re would be mainly discussed. At moderate and high Re , the fluid inertial effects usually facilitate the chaotic mixing. At low Re , generation of chaotic advection becomes more difficult but can still be achieved through fluid manipulations such as stretching and folding. Chaotic mixers can be characterized using dynamical system techniques, such as Poincaré plot, and Lyapunov exponent.

Abstract 127: Machine Learning Techniques to Predict Cardiac Re-Arrest in Out-Of-Hospital Setting

Circulation ◽  
2019 ◽  
Vol 140 (Suppl_2) ◽  
Author(s):  
Andoni Elola ◽  
Elisabete Aramendi ◽  
Unai Irusta ◽  
Naroa Amezaga ◽  
Jon Urteaga ◽  
...  
Keyword(s):  
Cardiac Arrest ◽  
Prediction Model ◽  
Prehospital Care ◽  
Hospital Setting ◽  
Area Under The Curve ◽  
Interquartile Range ◽  
Machine Learning Techniques ◽  
Survival Prediction ◽  
Poincaré Plot ◽  
Rr Intervals

Background: Re-arrest occurs when a cardiac arrest patient being treated by the emergency medical services experiences another cardiac arrest after return of spontaneous circulation (ROSC).The incidence of re-arrest is high, close to 40% in out-of-hospital cardiac arrest (OHCA), and it is associated with lower survival. Prediction of re-arrest could improve prehospital care. The aim of this study was to develop a re-arrest prediction model based on heart rate variability (HRV) features. Materials and methods: OHCA cases treated by Dallas-FortWorth Center of Resuscitation Research were analyzed. Patients with at least two minutes of ROSC were included. Re-arrest was ascertained by the presence of life-threatening ECG and/or presence of chest compressions within 12 minutes after ROSC. Eighteen HRV characteristics for 1 min and 2 min intervals after ROSC were computed. Features were fed into a Random Forest (RF) classifier with 100 trees to predict re-arrest cases. Ten-fold cross-validation with 30 repetitions was applied to train the model and assess the performance in terms of area under the curve (AUC). Results: Inclusion criteria were met by 98 patients, 41 of which suffered re-arrest. The median time (interquartile range) to re-arrest from ROSC onset was 5 (3-7) min. The re-arrest prediction model showed a median AUC of 0.71 and 0.75 for 1 and 2 min post ROSC intervals, respectively. The most important HRV features in the RF predictor were the SD1/SD2 ratio (where SD1 and SD2 are the dispersions of points both perpendicular and parallel to the line-of-identity in the Poincaré plot), SD2, the interquartile range of the RR intervals, peak frequency in the high frequency band (0.15-0.4 Hz) and coefficient of variation of RR intervals (the ratio between the mean and standard deviation of RR intervals). Conclusions: HRV metrics predict re-arrest in OHCA. Further studies with larger datasets are needed to better understand re-arrest dynamics and confirm conclusions.

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