Chronic pain (CP) is disabling for people triggering important costs for society. A deficit of diffuse noxious inhibitory controls (DNIC) is one of the CP mechanisms. DNICs are evaluated in research setting using a CPM protocol (conditioned pain modulation). There is a lack of reference values on the effectiveness of DNICs. Wider research on DNIC will help to understand CP and to develop a clinical screening test evaluating DNICs. This study aims more specifically to determine whether it is possible to develop a facial recognition system to automate pain measurement and the effectiveness of pain control mechanisms.
This study aims: 1. To develop and validate a predictive tool (using deep learning and artificial intelligence) to estimate the efficacy of pain control mechanisms. 2. To estimate references values for facial expressions of pain control mechanisms in healthy and in chronic pain participants. The target population will be healthy volunteers and volunteers with chronic pain, male and female, stratified by age. The reference values (healthy volunteers) will be established via a non-parametric method for a standard conditioned pain modulation (CPM) protocol in which two "stimuli tests" of the same intensity and nature (heat) will be applied before and after the application of another "conditioning stimulus" (cold water bath). The perceived pain difference between the 1st and 2nd stimuli tests will reflect the intensity of the DNICs. Participants' facial expressions will be captured simultaneously by three cameras during the CPM testing. These results will be compared to those from volunteers suffering with chronic pain. The clinical decision rule will result from clinical and paraclinical elements correlating with the amplitude of the efficacy of CPM (serum noradrenaline, intensity of pain, heart rate and blood pressure measurements, psychometric questionnaires assessing anxiety, depressive feelings and pain catastrophizing). Logistic regression analysis will determine the best predictors of a CPM deficit.
Study Type
OBSERVATIONAL
Enrollment
244
Conditioned pain modulation (CPM) protocol consist of evaluating pain during a heat test, before and after one conditioning stimulus (cold water bath); 3 cameras will be capturing participants' facial expressions during the tests.
Université de Sherbrooke
Sherbrooke, Quebec, Canada
Conditioned pain modulation (CPM) profiles
Sensitivity and specificity of the classification algorithm according to different profiles (normal vs altered) of conditioned pain modulation, as defined by the change of pain perception before and after the cold water bath measured by computerized visual analog scale (CoVAS) ranging from 0 \[no pain\] to 100 \[most intense pain that could be tolerated\] in healthy and in chronic pain volunteers together.
Time frame: Once, at baseline, at recruitment (comparison between 1st and 2nd test, after the conditioning stimuli)
Temporal summation profiles
Sensitivity and specificity of the classification algorithm according to different profiles (normal vs altered) of temporal summation, as defined by the change of pain perception during the first stimuli test measured by computerized visual analog scale (CoVAS) ranging from 0 \[no pain\] to 100 \[most intense pain that could be tolerated\] in healthy and in chronic pain volunteers together.
Time frame: Once, at baseline, at recruitment (during the first stimuli test)
Conditioned pain modulation (CPM) profiles of healthy volunteers
Conditioned pain modulation, as defined by the change of pain perception before and after the cold water bath measured by computerized visual analog scale (CoVAS) ranging from 0 \[no pain\] to 100 \[most intense pain that could be tolerated\] only in healthy volunteers.
Time frame: Once, at baseline, at recruitment (comparison between 1st and 2nd test, after the conditioning stimuli
Temporal summation profiles of healthy volunteers
Temporal summation, as defined by the change of pain perception during the first stimuli test measured by computerized visual analog scale (CoVAS) ranging from 0 \[no pain\] to 100 \[most intense pain that could be tolerated\] only in healthy volunteers.
Time frame: Once, at baseline, at recruitment (during the first stimuli test)
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Conditioned pain modulation (CPM) profiles of volunteers with chronic pain
Conditioned pain modulation, as defined by the change of pain perception before and after the cold water bath measured by computerized visual analog scale (CoVAS) ranging from 0 \[no pain\] to 100 \[most intense pain that could be tolerated\] only in volunteers with chronic pain.
Time frame: Once, at baseline, at recruitment (comparison between 1st and 2nd test, after the conditioning stimuli)
Temporal summation profiles of volunteers with chronic pain
Temporal summation, as defined by the change of pain perception during the first stimuli test measured by computerized visual analog scale (CoVAS) ranging from 0 \[no pain\] to 100 \[most intense pain that could be tolerated\] only in volunteers with chronic pain.
Time frame: Once, at baseline, at recruitment (during the first stimuli test)
Demographic factors
Association of demographic factors (age, gender) with different response profiles of CPM and temporal summation established by the algorithm.
Time frame: Once, at baseline, at recruitment
Psychologic factors
Association of psychologic factors (anxiety measured with HADS questionnaire) with different response profiles of CPM and temporal summation established by the algorithm.
Time frame: Once, at baseline, at recruitment
Physiologic factors
Association of physiologic factors (continuous blood pressure, heart rate, electrodermal activity) with different response profiles of CPM and temporal summation established by the algorithm.
Time frame: Once, at baseline, at recruitment
Facial expressions and postures
Association of facial expressions and postures with different response profiles of CPM and temporal summation established by the algorithm.
Time frame: Once, at baseline, at recruitment