AIMC Topic: Respiratory Rate

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Energy-Efficient PPG-Based Respiratory Rate Estimation Using Spiking Neural Networks.

Sensors (Basel, Switzerland)
Respiratory rate (RR) is a vital indicator for assessing the bodily functions and health status of patients. RR is a prominent parameter in the field of biomedical signal processing and is strongly associated with other vital signs such as blood pres...

Deep Survival Analysis With Latent Clustering and Contrastive Learning.

IEEE journal of biomedical and health informatics
Survival analysis is employed to analyze the time before the event of interest occurs, which is broadly applied in many fields. The existence of censored data with incomplete supervision information about survival outcomes is one key challenge in sur...

Improving respiratory signal prediction with a deep neural network and simple changes to the input and output data format.

Physics in medicine and biology
To improve respiratory gating accuracy and radiation treatment throughput, we developed a generalized model based on a deep neural network (DNN) for predicting any given patient's respiratory motion.Our model uses long short-term memory (LSTM) based ...

Contactless Respiration Monitoring Using Wi-Fi and Artificial Neural Network Detection Method.

IEEE journal of biomedical and health informatics
Detecting respiration in a non-intrusive manner is beneficial not only for convenience but also for cases where the traditional ways cannot be applied. This paper presents a novel simple low-cost system where ambient Wi-Fi signals are acquired by a t...

An Accelerometer-Based Wearable Patch for Robust Respiratory Rate and Wheeze Detection Using Deep Learning.

Biosensors
Wheezing is a critical indicator of various respiratory conditions, including asthma and chronic obstructive pulmonary disease (COPD). Current diagnosis relies on subjective lung auscultation by physicians. Enabling this capability via a low-profile,...

Classification of Breathing Signals According to Human Motions by Combining 1D Convolutional Neural Network and Embroidered Textile Sensor.

Sensors (Basel, Switzerland)
Research on healthcare and body monitoring has increased in recent years, with respiratory data being one of the most important factors. Respiratory measurements can help prevent diseases and recognize movements. Therefore, in this study, we measured...

Detection of Multiple Respiration Patterns Based on 1D SNN from Continuous Human Breathing Signals and the Range Classification Method for Each Respiration Pattern.

Sensors (Basel, Switzerland)
Human respiratory information is being used as an important source of biometric information that can enable the analysis of health status in the healthcare domain. The analysis of the frequency or duration of a specific respiration pattern and the cl...

Direct machine learning reconstruction of respiratory variation waveforms from resting state fMRI data in a pediatric population.

NeuroImage
In many functional magnetic resonance imaging (fMRI) studies, respiratory signals are unavailable or do not have acceptable quality due to issues with subject compliance, equipment failure or signal error. In large databases, such as the Human Connec...

Investigating Cardiorespiratory Interaction Using Ballistocardiography and Seismocardiography-A Narrative Review.

Sensors (Basel, Switzerland)
Ballistocardiography (BCG) and seismocardiography (SCG) are non-invasive techniques used to record the micromovements induced by cardiovascular activity at the body's center of mass and on the chest, respectively. Since their inception, their potenti...

Predicting respiratory motion using a novel patient specific dual deep recurrent neural networks.

Biomedical physics & engineering express
Real-time tracking of a target volume is a promising solution for reducing the planning margins and both dosimetric and geometric uncertainties in the treatment of thoracic and upper-abdomen cancers. Respiratory motion prediction is an integral part ...