The objective measurement of subjective, multi-dimensionally experienced pain is a problem for which there has not been an adequate solution. Although verbal methods (e.g., pain scales and questionnaires) are commonly used to measure clinical pain, they tend to lack objectivity, reliability, or validity when applied to mentally impaired individuals. Biopotential and behavioral parameters may represent a solution. Such coding systems already exist, but they are either very costly or time-consuming or have not been sufficiently evaluated. In this context, we collected a database of biopotentials to advance an automated pain recognition system, determine its theoretical testing quality, and optimize its performance. For this purpose, participants were subjected to painful heat stimuli under controlled conditions. One hundred thirty-five features were extracted from the mathematical groupings of amplitude, frequency, stationarity, entropy, linearity, and variability. The following features were chosen as the most selective: (1) electromyography corrugator peak to peak, (2) corrugator shannon entropy, and (3) heart rate variability slope RR. Individual-specific calibration allows the adjustment of feature patterns, resulting in significantly more accurate pain detection rates. The objective measurement of pain in patients will provide valuable information for the clinical team, which may aid the objective assessment of treatment (e.g., effectiveness of drugs for pain reduction, information on surgical indication, and quality of care provided to patients).

Pain assessment is very important in establishing the efficacy of analgesics and therapies, but because pain is a subjective experience, using methods that represent pain objectively is necessary. A number of biopotentials have been employed in studies of the objective assessment of pain. However, few investigations have considered the peripheral nervous system response to electrical stimulation. The present study evaluated a method for pain quantification based on the analysis of biopotentials. We assessed electromyographic activity that resulted from evoked movements from the nociceptive flexion reflex (NFR). We investigated correlations between stimulus intensity, features extracted from surface electromyography (EMG), and subjective pain reported by subjects using a Visual Analog Scale (VAS). A total of 10 healthy male subjects without any pain disorder, aged 20-27 years, participated in the study. A high correlation (r2 > .87) was found between stimulus intensity and the following features extracted from the EMG: area, root mean square (RMS), and entropy. A high correlation (r2 > .99) was also found between stimulus intensity and subjective pain reported on the VAS. We conclude that estimating features from electromyographic signals that are correlated with subjective pain sensations and the intensity of the electrical stimulus is possible. Entropy, RMS, and the area of the electromyographic signal appear to be relevant parameters in correlations with subjective pain.

This study proposed the development of a new clinical tool capable of quantifying the movements of opening-closing, protrusion and laterotrusion of the mandible. These movements are important for the clinical evaluation of the temporomandibular function and muscles involved in mastication. Unlike current commercial systems, the proposed system employs a low-cost video camera and a computer program that is used for reconstructing the trajectory of a reflective marker that is fixed on the mandible. In order to illustrate the clinical application of this tool, a clinical experiment consisting on the evaluation of the mandibular movements of 12 subjects was conducted. The results of this study were compatible with those found in the literature with the advantage of using a low cost, simple, non-invasive, and flexible tool customized for the needs of the practical clinic.