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DTSTART:19700308T020000
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DTSTART:19701101T020000
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DTSTAMP:20251016T135200Z
LOCATION:Riverside East
DTSTART;TZID=America/Chicago:20251015T173000
DTEND;TZID=America/Chicago:20251015T183000
UID:HFESAM_ASPIRE 2025_sess138_POST492@linklings.com
SUMMARY:Beyond Pain Intensity Scores: A Systematic Review of Multimodal Di
 gital Neurophysiological Sensors for Objective Pain Assessment in the Clin
 ical Application
DESCRIPTION:Wenchao Zhu and Yingzi Lin (Northeastern University)\n\nPeople
  have been looking for an objective measure of chronic pain for decades. C
 urrent objective measures can be achieved by correlating patients’ self-re
 port with physiological signal features, but such measures often yield inc
 onsistent results due to individual variability. While existing approaches
  heavily rely on pain intensity, this study reviewed literatures in differ
 entiating pain types and pain locations using neurophysiological sensors, 
 (e.g., electroencephalograms (EEG), electrodermal activity (EDA), respirat
 ion rate (RR), photoplethysmography (PPG), functional near-infrared spectr
 oscopy (fNIRS)). Results showed that using modalities like EEG and fNIRS, 
 high classification accuracy for specific stimuli can be achieve. However,
  most existing datasets lack integration of both neurological and peripher
 al physiological signals and do not label multimodal pain dimensions, such
  as type, intensity, and location. The review highlights an urgent need fo
 r datasets that combine these modalities to support clinically meaningful,
  objective pain assessment. Rather than replacing subjective patient repor
 ts, these approaches should be developed to complement and refine them in 
 clinical contexts. Future research should also prioritize multidimensional
  labeling, population diversity, and transparent validation frameworks to 
 advance reliable diagnostics and personalized pain management.\n\n
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