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Pain

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Scalp EEG-Based Pain Detection Using Convolutional Neural Network.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Pain is an integrative phenomenon coupled with dynamic interactions between sensory and contextual processes in the brain, often associated with detectable neurophysiological changes. Recent advances in brain activity recording tools and machine lear...

Automated Pain Assessment in Children Using Electrodermal Activity and Video Data Fusion via Machine Learning.

IEEE transactions on bio-medical engineering
Pain assessment in children continues to challenge clinicians and researchers, as subjective experiences of pain require inference through observable behaviors, both involuntary and deliberate. The presented approach supplements the subjective self-r...

Identification of Uncontrolled Symptoms in Cancer Patients Using Natural Language Processing.

Journal of pain and symptom management
CONTEXT: For patients with cancer, uncontrolled pain and other symptoms are the leading cause of unplanned hospitalizations. Early access to specialty palliative care (PC) is effective to reduce symptom burden, but more efficient approaches are neede...

The Route of Motor Recovery in Stroke Patients Driven by Exoskeleton-Robot-Assisted Therapy: A Path-Analysis.

Medical sciences (Basel, Switzerland)
: Exoskeleton-robot-assisted therapy is known to positively affect the recovery of arm functions in stroke patients. However, there is a lack of evidence regarding which variables might favor a better outcome and how this can be modulated by other fa...

Cutoff criteria for the placebo response: a cluster and machine learning analysis of placebo analgesia.

Scientific reports
Computations of placebo effects are essential in randomized controlled trials (RCTs) for separating the specific effects of treatments from unspecific effects associated with the therapeutic intervention. Thus, the identification of placebo responder...

Machine learning approaches applied in spinal pain research.

Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology
The purpose of this narrative review is to provide a critical reflection of how analytical machine learning approaches could provide the platform to harness variability of patient presentation to enhance clinical prediction. The review includes a sum...

Systematic Review of the Effectiveness of Machine Learning Algorithms for Classifying Pain Intensity, Phenotype or Treatment Outcomes Using Electroencephalogram Data.

The journal of pain
Recent attempts to utilize machine learning (ML) to predict pain-related outcomes from Electroencephalogram (EEG) data demonstrate promising results. The primary aim of this review was to evaluate the effectiveness of ML algorithms for predicting pai...

Comparison of Feature Extraction Methods for Physiological Signals for Heat-Based Pain Recognition.

Sensors (Basel, Switzerland)
While even the most common definition of pain is under debate, pain assessment has remained the same for decades. But the paramount importance of precise pain management for successful healthcare has encouraged initiatives to improve the way pain is ...

Exploration of physiological sensors, features, and machine learning models for pain intensity estimation.

PloS one
In current clinical settings, typically pain is measured by a patient's self-reported information. This subjective pain assessment results in suboptimal treatment plans, over-prescription of opioids, and drug-seeking behavior among patients. In the p...

Objective pain stimulation intensity and pain sensation assessment using machine learning classification and regression based on electrodermal activity.

American journal of physiology. Regulatory, integrative and comparative physiology
An objective measure of pain remains an unmet need of people with chronic pain, estimated to be 1/3 of the adult population in the United States. The current gold standard to quantify pain is highly subjective, based upon self-reporting with numerica...