AIMC Topic: Pain

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Cluster-Then-Classify Methodology for the Identification of Pain Episodes in Chronic Diseases.

IEEE journal of biomedical and health informatics
Chronic diseases benefit of the advances on personalize medicine coming out of the integrative convergence of significant developments in systems biology, the Internet of Things and Artificial Intelligence. 70% to 80% of all healthcare costs in the E...

Sacroiliac Joint Fusion Using Robotic Navigation: Technical Note and Case Series.

Operative neurosurgery (Hagerstown, Md.)
BACKGROUND: Patients undergoing sacroiliac (SI) fusion can oftentimes experience significant improvements in pain and quality of life.

Assessment of Pain Onset and Maximum Bearable Pain Thresholds in Physical Contact Situations.

Sensors (Basel, Switzerland)
With the development of robot technology, robot utilization is expanding in industrial fields and everyday life. To employ robots in various fields wherein humans and robots share the same space, human safety must be guaranteed in the event of a huma...

Simulating dynamic facial expressions of pain from visuo-haptic interactions with a robotic patient.

Scientific reports
Medical training simulators can provide a safe and controlled environment for medical students to practice their physical examination skills. An important source of information for physicians is the visual feedback of involuntary pain facial expressi...

Automatic detection and classification of knee osteoarthritis using deep learning approach.

La Radiologia medica
PURPOSE: We developed a tool for locating and grading knee osteoarthritis (OA) from digital X-ray images and illustrate the possibility of deep learning techniques to predict knee OA as per the Kellgren-Lawrence (KL) grading system. The purpose of th...

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...