PainMeter: Automatic Assessment of Pain Intensity Levels from Multiple Physiological Signals using Machine Learning
W Aljebreen, DM Ibrahim - IEEE Access, 2024 - ieeexplore.ieee.org
Pain assessment traditionally relies on self-report, but it is subjective and influenced by
various factors. To address this, there'sa need for an affordable and scalable objective pain
identification method. Current research suggests that pain has physiological markers
beyond the brain, such as changes in cardiovascular activity and electrodermal responses.
Utilizing these markers, real-time pain detection algorithms were developed using the
BioVid Heat Pain dataset, consisting of 86 healthy individuals experiencing acute pain …
various factors. To address this, there'sa need for an affordable and scalable objective pain
identification method. Current research suggests that pain has physiological markers
beyond the brain, such as changes in cardiovascular activity and electrodermal responses.
Utilizing these markers, real-time pain detection algorithms were developed using the
BioVid Heat Pain dataset, consisting of 86 healthy individuals experiencing acute pain …
[PDF][PDF] PainMeter: Automatic Assessment of Pain Intensity Levels from Multiple Physiological Signals using Machine Learning
A DA'AD, W ALJEBREEN, DM Ibrahim - 2024 - researchgate.net
Pain assessment traditionally relies on self-report, but it is subjective and influenced by
various factors. To address this, there'sa need for an affordable and scalable objective pain
identification method. Current research suggests that pain has physiological markers
beyond the brain, such as changes in cardiovascular activity and electrodermal responses.
Utilizing these markers, real-time pain detection algorithms were developed using the
BioVid Heat Pain dataset, consisting of 86 healthy individuals experiencing acute pain …
various factors. To address this, there'sa need for an affordable and scalable objective pain
identification method. Current research suggests that pain has physiological markers
beyond the brain, such as changes in cardiovascular activity and electrodermal responses.
Utilizing these markers, real-time pain detection algorithms were developed using the
BioVid Heat Pain dataset, consisting of 86 healthy individuals experiencing acute pain …
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