Association between myofascial trigger point therapy and conditioned pain modulation.

INTRODUCTION: Myofascial trigger point therapy (MTrP) is a widely used therapeutic approach, although the underlying mechanisms remain unclear. Mechanisms discussed include peripheral involvement of muscles as well as central pain modulating processes such as the conditioned pain modulation (CPM). The aim of this study was to investigate whether the analgesic response of MTrP and the analgesic response of CPM correlate in asymptomatic participants in order to identify shared underlying mechanisms of MTrP and CPM. METHOD: Both, CPM and MTrP protocols consisted of heat-based test stimuli (heat pain thresholds before and after the intervention) and pressure-based (conditioning) stimuli. Asymptomatic participants (n = 94) were randomly assigned to receive either mild, intense or no pressure stimuli (between-group design) to both the fingernail and the MTrP of the infraspinatus muscle (within-group design). Pressure stimuli at both locations (fingernail, MTrP) were applied with a pressure algometer for 120 s and continuously adjusted to maintain a constant pain intensity of mild or intense pain. All thermal stimuli were applied on the lower leg with a thermal stimulator. RESULTS: A significant correlation was shown between the analgesic effect of CPM and MTrP therapy for mild (r = 0.53, p = 0.002) and intensive stimuli (r = 0.73, p < 0.001). 17.3% of the variance of the MTrP effect were explained by CPM after mild stimulation, and 47.1% after intense stimulation. Pain-related characteristics did not explain the variance within the analgesic response using a regression analysis. CONCLUSIONS: Between the analgesic responses following MTrP and CPM paradigms, a moderate to strong correlation was observed, suggesting shared underlying mechanisms.

Differential Effects of Thermal Stimuli in Eliciting Temporal Contrast Enhancement: A Psychophysical Study.

Offset analgesia (OA) is observed when pain relief is disproportional to the reduction of noxious input and is based on temporal contrast enhancement (TCE). This phenomenon is believed to reflect the function of the inhibitory pain modulatory system. However, the mechanisms contributing to this phenomenon remain poorly understood, with previous research focusing primarily on painful stimuli and not generalizing to nonpainful stimuli. Therefore, the aim of this study was to investigate whether TCE can be induced by noxious as well as innocuous heat and cold stimuli. Asymptomatic subjects (n = 50) were recruited to participate in 2 consecutive experiments. In the first pilot study (n = 17), the parameters of noxious and innocuous heat and cold stimuli were investigated in order to implement them in the main study. In the second (main) experiment, subjects (n = 33) participated in TCE paradigms consisting of 4 different modalities, including noxious heat (NH), innocuous heat (IH), noxious cold (NC), and innocuous cold (IC). The intensity of the sensations of each thermal modality was assessed using an electronic visual analog scale. TCE was confirmed for NH (P < .001), NC (P = .034), and IC (P = .002). Conversely, TCE could not be shown for IH (P = 1.00). No significant correlation between TCE modalities was found (r < .3, P > .05). The results suggest that TCE can be induced by both painful and nonpainful thermal stimulation but not by innocuous warm temperature. The exact underlying mechanisms need to be clarified. However, among other potential mechanisms, this may be explained by a thermo-specific activation of C-fiber afferents by IH and of A-fiber afferents by IC, suggesting the involvement of A-fibers rather than C-fibers in TCE. More research is needed to confirm a peripheral influence. PERSPECTIVE: This psychophysical study presents the observation of temporal contrast enhancement during NH, NC, and innocuous cold stimuli but not during stimulation with innocuous warm temperatures in healthy volunteers. A better understanding of endogenous pain modulation mechanisms might be helpful in explaining the underlying aspects of pain disorders.

Objective Measurement of Subjective Pain Perception with Autonomic Body Reactions in Healthy Subjects and Chronic Back Pain Patients: An Experimental Heat Pain Study.

Multiple attempts to quantify pain objectively using single measures of physiological body responses have been performed in the past, but the variability across participants reduces the usefulness of such methods. Therefore, this study aims to evaluate whether combining multiple autonomic parameters is more appropriate to quantify the perceived pain intensity of healthy subjects (HSs) and chronic back pain patients (CBPPs) during experimental heat pain stimulation. HS and CBPP received different heat pain stimuli adjusted for individual pain tolerance via a CE-certified thermode. Different sensors measured physiological responses. Machine learning models were trained to evaluate performance in distinguishing pain levels and identify key sensors and features for the classification task. The results show that distinguishing between no and severe pain is significantly easier than discriminating lower pain levels. Electrodermal activity is the best marker for distinguishing between low and high pain levels. However, recursive feature elimination showed that an optimal subset of features for all modalities includes characteristics retrieved from several modalities. Moreover, the study's findings indicate that differences in physiological responses to pain in HS and CBPP remain small.

Effectiveness of online teaching during the COVID-19 pandemic on practical manual therapy skills of undergraduate physiotherapy students.

OBJECTIVES: This study includes two separate parts: the objective for part A was to evaluate the practical manual therapy skills of undergraduate physiotherapy students who had learned manual therapy techniques either online or in classroom depending on the phases of the pandemic. The objective for part B was to evaluate in a randomized prospective design the effectiveness of video-based versus traditional teaching of a manual therapy technique. DESIGN: Cross-sectional cohort study (part A) and randomized controlled trial (part B). SETTING: University of Luebeck, undergraduate physiotherapy students in years 1-3. METHOD: In part A, physiotherapy students who had learned manual therapy either online (during the pandemic) or in classroom (prior to and after the lock down periods of the pandemic) were videotaped while performing two manual techniques on the knee joint and on the lumbar spine. Recordings were analyzed independently by two blinded raters according to a 10-item list of criteria. Inter-rater reliability was assessed using Cohen's kappa for each item. Performance across cohorts was analyzed using analysis of variance. In part B, students were randomized to learn a new technique on the cervical spine either from a lecturer or from the same lecturer on a video recording (independent variable). Practical performance of the technique was analyzed by two raters blinded to group allocation according to a 10-item list of criteria (dependent variable). Results were analyzed statistically by using ANCOVA with year of study as a covariate. RESULTS: Sixty-three and 56 students participated in part A and part B of the study, respectively. The inter-rater reliability for video analyses for both parts of the study was moderate (k = 0.402 to 0.441). In part A, there was no statistically significant difference across years of study for the practical performance of the technique on the back F(2,59) = 2.271; p = 0.112 or the knee joint F(2,59) = 3.028; p = 0.056. In part B, performance was significantly better when learned from a lecturer and practiced on a peer than when learned from a video and practiced on a rescue dummy (p < 0.001). CONCLUSION: Practical skill performance can be acquired from videos but immediate skill reproduction is significantly better when the technique is presented by a lecturer in classroom and practiced on peer students.

Explainable Artificial Intelligence (XAI) in Pain Research: Understanding the Role of Electrodermal Activity for Automated Pain Recognition.

Artificial intelligence and especially deep learning methods have achieved outstanding results for various applications in the past few years. Pain recognition is one of them, as various models have been proposed to replace the previous gold standard with an automated and objective assessment. While the accuracy of such models could be increased incrementally, the understandability and transparency of these systems have not been the main focus of the research community thus far. Thus, in this work, several outcomes and insights of explainable artificial intelligence applied to the electrodermal activity sensor data of the PainMonit and BioVid Heat Pain Database are presented. For this purpose, the importance of hand-crafted features is evaluated using recursive feature elimination based on impurity scores in Random Forest (RF) models. Additionally, Gradient-weighted class activation mapping is applied to highlight the most impactful features learned by deep learning models. Our studies highlight the following insights: (1) Very simple hand-crafted features can yield comparative performances to deep learning models for pain recognition, especially when properly selected with recursive feature elimination. Thus, the use of complex neural networks should be questioned in pain recognition, especially considering their computational costs; and (2) both traditional feature engineering and deep feature learning approaches rely on simple characteristics of the input time-series data to make their decision in the context of automated pain recognition.