A Novel Wearable Real-Time Sleep Apnea Detection System Based on the Acceleration Sensor
ConclusionsThis work proposed using an acceleration sensor as a reliable method of sleep apnea screening, detection of an apnea event, sending alert to the patient, and detection of the patient lying position. The developed device is more economical, comfortable, and convenient than existing systems for not only the patients but also the doctors. The patients can easily use this device in their home environment.Graphical abstract (Source: IRBM)
Source: IRBM - November 16, 2019 Category: Biomedical Engineering Source Type: research
A Non-invasive Method for Determining Biomechanical Properties of the Internal Carotid Artery
ConclusionThus, the in vivo application of this technique shows its potential for clinical evaluation of arterial stiffness ICA as it is fully quantitative, non-invasive and can be performed in real time.Graphical abstract (Source: IRBM)
Source: IRBM - November 15, 2019 Category: Biomedical Engineering Source Type: research
Editorial Board
Publication date: December 2019Source: IRBM, Volume 40, Issue 6Author(s): (Source: IRBM)
Source: IRBM - November 8, 2019 Category: Biomedical Engineering Source Type: research
A Review of Ultrasound Imaging Techniques for the Detection of Down Syndrome
Publication date: Available online 5 November 2019Source: IRBMAuthor(s): S.P. Arjunan, M.C. ThomasAbstractDown syndrome is the most common chromosomal disorder that affects the life of a person. Early detection of Down syndrome is important and significant for a better assessment of the fetus. The detection can be performed by identifying various parameters from the ultrasound images recorded during the 1st (11-14 weeks) and 2nd trimester (15-22 weeks) of the gestational period. The most important features are short Nasal bone (Hypoplasia) or absence of nasal bone, increased thickness of the back of the neck, fetal heart r...
Source: IRBM - November 6, 2019 Category: Biomedical Engineering Source Type: research
A Deep Feature Learning Model for Pneumonia Detection Applying a Combination of mRMR Feature Selection and Machine Learning Models
In this study, lung X-ray images that are available for the diagnosis of pneumonia were used. The convolutional neural network was employed as feature extractor, and some of existing convolutional neural network models that are AlexNet, VGG-16 and VGG-19 were utilized so as to realize this specific task. Then, the number of deep features was reduced from 1000 to 100 by using the minimum redundancy maximum relevance algorithm for each deep model. Accordingly, we achieved 100 deep features from each deep model, and we combined these features so as to provide an efficient feature set consisting of totally 300 deep features. I...
Source: IRBM - November 6, 2019 Category: Biomedical Engineering Source Type: research
Intelligent Toilet System for Non-invasive Estimation of Blood-Sugar Level from Urine
DiscussionThis system is efficient to estimate blood sugar level from urine. This system senses the urine sugar level indirectly using the color sensor. The color sensor is not directly in touch with the chemical of the reaction chamber. The normal toilet cleaning (acidic) solution can be used to clean the chambers. So, maintenance process is quite easy. The proposed system can reduce the probability of glaucoma, kidney problem etc. by assisting doctors to control high blood sugar level through regular monitoring of urine sugar level.Graphical abstract (Source: IRBM)
Source: IRBM - November 1, 2019 Category: Biomedical Engineering Source Type: research
R-Peak Detection Using Chaos Analysis in Standard and Real Time ECG Databases
ConclusionThe proposed technique outperforms the other existing works on various selected evaluation parameters even without pre-processing. Hence, the proposed technique has successfully demonstrated its ability to discriminate different types of heartbeats in most of the critical situations. Therefore, there are strong merits in using chaos analysis as a feature extraction method to reduce the incidence of false diagnosis.Graphical abstract (Source: IRBM)
Source: IRBM - October 25, 2019 Category: Biomedical Engineering Source Type: research
Multi-day Longitudinal Assessment of Physical Activity and Sleep Behavior Among Healthy Young and Older Adults Using Wearable Sensors
ConclusionThe advantages of collecting longitudinal data about human movement and sleep transition data can lead us to important clinical diagnosis. The information from longitudinal assessment can help develop lifestyle interventions for disease prevention, monitoring of chronic diseases to prevent or slow disease progression among elderly people.Graphical abstract (Source: IRBM)
Source: IRBM - October 24, 2019 Category: Biomedical Engineering Source Type: research
Assessment of Techniques for Teaching School Children with Autism
ConclusionResults of our study revealed that raw and the standard scores of stereotyped behaviors was notably (p<0.05) low in S1 school children when collated with the other two (S2 and S3) schools. Similarly, the raw and the standard score of communication, the socially interaction sub-score was notably (p<0.05) low for the children in S3 when collated with the children in the other two schools. The study concluded that the horseback riding, the yoga therapy and the cue cards-based teaching methods improve the stereotyped behavior, increase concentration power and also helps in maintaining the children's mind stab...
Source: IRBM - October 22, 2019 Category: Biomedical Engineering Source Type: research
An Efficient Automated Algorithm for Distinguishing Normal and Abnormal ECG Signal
ConclusionThe ECG signal representing the electrical activity of the heart at different time intervals involves some important information. The signal is considered as one of the common tools used by physicians to diagnose various cardiovascular diseases, but unfortunately the proper diagnosis of disease in many cases is accompanied by an error due to limited time accuracy and hiding some important information related to this signal from the physicians' vision leading to the risks of irreparable harm for patients. Based on the results, designing the proposed alarm system can help physicians with higher speed and accuracy i...
Source: IRBM - October 11, 2019 Category: Biomedical Engineering Source Type: research
Myocardial Infarction Detection and Localization Using Optimal Features Based Lead Specific Approach
ConclusionThus for MI detection and localization, the proposed technique is independent of time-domain ECG fiducial markers and can work using specific leads of ECG.Graphical abstract (Source: IRBM)
Source: IRBM - October 6, 2019 Category: Biomedical Engineering Source Type: research
Editorial Board
Publication date: October 2019Source: IRBM, Volume 40, Issue 5Author(s): (Source: IRBM)
Source: IRBM - September 26, 2019 Category: Biomedical Engineering Source Type: research
Prognosis Analysis of Heart Failure Based on Recurrent Attention Model
ConclusionExperiments show that the prognostic effect of the recurrent attention model is significantly higher than that of other traditional machine learning models. Because the model increases the attention mechanism, the important features affecting the prognostic results are obtained, which enables doctors to prescribe drugs according to the symptoms, take timely precautions and help patients to treat in time.Graphical abstract (Source: IRBM)
Source: IRBM - September 13, 2019 Category: Biomedical Engineering Source Type: research
A Deep Learning Architecture for P300 Detection with Brain-Computer Interface Application
Publication date: Available online 11 September 2019Source: IRBMAuthor(s): S. Kundu, S. AriAbstractIn this paper, a brain-computer interface (BCI) system for character recognition is proposed based on the P300 signal. A P300 speller is used to spell the word or character without any muscle movement. P300 detection is the first step to detect the character from the electroencephalogram (EEG) signal. The character is recognized from the detected P300 signal. In this paper, sparse autoencoder (SAE) and stacked sparse autoencoder (SSAE) based feature extraction methods are proposed for P300 detection. This work also proposes a...
Source: IRBM - September 12, 2019 Category: Biomedical Engineering Source Type: research
Patient-Specific Epileptic Seizure Prediction in Long-Term Scalp EEG Signal Using Multivariate Statistical Process Control
ConclusionThis study proposed a temporal based patient-specific epileptic seizure prediction method using MSPC in long-term scalp EEG signals. It also provides the possibility of realizing an EEG-based epileptic seizure prediction system which requires less computational power.SignificanceThe proposed method does not require preictal data for modeling. The extracted features are computationally easy. The tested result shows good accuracy on the CHB-MIT data base.Graphical abstract (Source: IRBM)
Source: IRBM - September 12, 2019 Category: Biomedical Engineering Source Type: research
