AIMC Topic: Heart Rate

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Adaptive heartbeat regulation using double deep reinforcement learning in a Markov decision process framework.

Scientific reports
The erratic nature of cardiac rhythms can precipitate a multitude of pathologies. Consequently, the endeavor to achieve stabilization of the human heartbeat has garnered significant scholarly interest in recent years. In this context, an adaptive non...

SHAP-driven insights into multimodal data: behavior phase prediction for industrial safety applications.

Scientific reports
Unsafe behaviors among coal miners are a primary factor contributing to accidents, posing significant challenges for safety management. This study develops a behavior state prediction framework using artificial intelligence and machine learning (ML) ...

Electrocardiogram heart rate variability for machine learning diagnosis of obstructive sleep Apnoea: A bayesian meta-analysis.

Sleep & breathing = Schlaf & Atmung
PURPOSE: Obstructive sleep apnoea syndrome (OSA) is a common yet underdiagnosed condition associated with significant health risks. Although polysomnography is the diagnostic gold standard, it is resource-intensive and unsuitable for widespread scree...

Predictors of Anemia Intolerance for Real-Time Transfusion Decision-Making During Resuscitation of Trauma Subjects: A Machine Learning Approach Using Heart Rate Variability.

Critical care explorations
OBJECTIVES: RBC transfusion in anemic patients with sustainable tolerance may cause harm, emphasizing the need for reliable metrics that quantify adequacy (oxygen delivery ≥ demand) and sustainability (oxygen delivery remains adequate without transfu...

Robotic reading companions can mitigate oral reading anxiety in children.

Science robotics
Reading fluency is a vital building block for developing literacy, yet the best way to practice fluency-reading aloud-can cause anxiety severe enough to inhibit literacy development in ways that can have an adverse effect on students through adulthoo...

Machine learning enhanced expert system for detecting heart failure decompensation using patient reported vitals and electronic health records.

Scientific reports
Heart failure (HF) is a condition with periods of stability interrupted by periods of worsening symptoms, known as decompensation episodes. Digital interventions are promising tools to alleviate burdens on HF management through automated alerts at th...

An effective multi-modality analysis for stress classification: A signal-to-image conversion using local pattern techniques.

Computers in biology and medicine
Stress is an intensified reaction that occurs when humans experience challenges(stressors) due to complex and nonlinear responses. The study proposes a pattern-driven framework that combines signal and image-based modalities, incorporating Local Bina...

IoT enabled health monitoring system using rider optimization algorithm and joint process estimation.

Scientific reports
The timely detection of abnormal health conditions is crucial in achieving successful medical intervention and enhancing patient outcomes. Despite advances in health monitoring, existing methods often struggle with achieving high accuracy, sensitivit...

Identifying key physiological and clinical factors for traumatic brain injury patient management using network analysis and machine learning.

PloS one
In the intensive care unit (ICU), managing traumatic brain injury (TBI) patients presents significant challenges due to the dynamic interaction between physiological and clinical markers. This study aims to uncover these subtle interconnections and i...

Understanding Physical Activity Facilitated by a Single Session of Robotic Walking for Children and Small Adults Living With Severe Mobility Impairments.

Journal of physical activity & health
BACKGROUND: Physical activity has many benefits but can be hard to achieve for people living with severe mobility impairments. Robotic walking may be an effective way for these individuals to achieve physical activity.