The authors would like to thank Verena Friedrich, Maria Velana, Sandra Gebhardt, Romy B&#228;rwaldt, and Tina Daucher for their precious help in conducting the study. In addition, a special thank you goes out to Dr. Stefanie Rukavina for her scientific support. This research was part of the DFG/TR233/12 (http://www.dfg.de/) &#8220;Advancement and Systematic Validation of an Automated Pain Recognition System on the Basis of Facial Expression and Psychobiological Parameters&#8221; project, funded by the German Research Foundation.

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The authors have nothing to disclose.

The presented protocol focuses on the experimental elicitation of thermal (heat) and electrical pain while recording physiological, visual and paralinguistic signals. This novel approach, combining two pain models with different stimuli intensities and two different stimuli durations (phasic and tonic), offers a broad perspective about the psychophysiological patterns and expressions of pain. However, for the realization of this protocol several steps need to be considered.&#160;
In general, if working with pain stimuli it is crucial to ensure the safety of the subjects. All pain stimuli have to be highly controlled and should only be carried out by experienced experimenters.&#160; 
Furthermore, for recording and collecting reliable and high quality data, the proper attachment of devices (electrodes), the perfect functioning of recording devices and a smooth communication between computers is highly recommended. All sources of interferences should be eliminated or reduced to a minimum. To guarantee consistency between participants, it is important to provide standardized instructions and unvarying experimental conditions.&#160;
According to our experience, finding suitable participants who meet all criteria and are willing to receive numerous painful stimuli, takes a long time and is quite challenging. In addition to that, the monetary compensation has to be high enough to attract subjects to the study. Especially persons between 30 and 50 years are hard to find. This may be because the experiment is too long (ca. 4 hours, including arrival and departure) and they have to take half a day off from work.
Because the safety of the participants is of top priority, pain induction may need to be restricted. Due to ethical guidelines, the stimulus intensities must not exceed certain levels to prevent burns and unconsciousness in terms of thermal and electrical pain induction, respectively. A general cutoff of intensities may result in a ceiling effect as some subjects may reach the intensity limits before feeling intolerable pain. In this study, approximately 42% (considering&#160;thermal calibration part 1 and 2) of the participants reached the thermal cutoffs (see representative results). As they did not reach their &#8220;real&#8221; pain tolerances, their physiological responses to the highest thermal stimuli might behave differently in contrast to physiological responses of subjects who reached them. If so, mixing these two groups could influence classification results in terms of pain recognition.
An important point to address is the pain modalities in this experiment. Participants are subjected only to thermal and electrical pain stimuli (due to the fact that these are highly controllable in an experimental setting). Thus, if examining pain patterns regarding quality, findings may not translate to other pain modalities such as pressure, chemical or visceral pain. 
The same consideration on transferability of results applies to the study sample. The protocol is ethically restricted to healthy adults. For example, it does not include children or cognitively and verbally impaired persons. Furthermore, in our study only European people participated. Also here, analytical results may not apply to groups not considered in this experiment.
Another limitation may concern the Hawthorne effect24: The subjects are aware that they are being filmed/observed in the study. This might change their behavior.
Compared to existing pain databases, the protocol provides significant advantages for analyzing pain response patterns as it combines two pain models and two time courses (phasic and tonic): Besides the intensity and duration of pain, it also considers the quality of pain. As thermal pain is described differently than electrical pain (e.g., burning vs. sharp), it may also differ in the pain reactions. If so, those findings could link a pain response pattern to the underlying source of pain. Furthermore, the study is multi-modal to widen the range of pain investigation opportunities: Employing 5 psychophysiological signals, 2 face (front/side) camera signals, 1 body view camera signal, 1 thermal camera and 1 audio signal, pain may be analyzed and assessed more precisely.&#160;
For a more complex investigation of pain response patterns, future extensions of this method should include more biosignals such as electroencephalography (EEG), body temperature and respiration. It would also be of great benefit to employ controlled pressure as a further pain model. Researchers aiming at automatic pain recognition via data gathered with this protocol should further test promising machine learning models with clinical control groups.&#160;

Pain is a very personal and unpleasant sensation that is perceived differently by everyone. It lasts from seconds to months and may vary in its quality (throbbing, sharp, burning, etc.). If treated inadequately, pain influences physical and psychological functions of the body, reduces the quality of life, and bears the risk of becoming a chronic condition. In clinical care, the accurate assessment of pain intensity and quality is highly relevant to provide successful pain management1,2. Gold standard methods for assessing pain, such as the visual analog scales (VAS), the numeric rating scale (NRS), or the McGill Pain Questionnaire3, rely on self-reports of patients and, thus, only work sufficiently with cognitively and verbally unimpaired persons. Consequently, all those established methods lack validity and reliability when it comes to neonates4, delirious, somnolent, sedated, or ventilated patients5, or people suffering from dementia6,7. In addition to or as an alternative to self-report scales, methods to measure pain through observation by trained personnel (e.g., the Zurich Observation Pain Assessment8 or the Abbey Pain Scale9) have been developed in recent years. Nevertheless, even these tools suffer from limitations in reliability and validity, as even trained raters cannot guarantee an objective assessment. Furthermore, the application is often too time-consuming for clinical staff when pain assessment should be done on a regular basis.&#160;
Several research teams have focused on developing automated pain recognizing systems, which allow for measuring pain by means of physiological, visual, and/or paralinguistic signal sets as new approaches for assessing and monitoring pain and its intensities objectively. Previous studies show promising results in detecting and differentiating pain10,11,12,13,16,17,18 or discriminating pain from basic emotions14,15 based solely on one of the signal sets10,11,12,13,14,15 as well as on a combination/fusion16,17,19 of the sets. The abovementioned modalities react almost autonomously to stressful stimuli such as pain. Using them has the advantage that they do not require a person&#8217;s ability to report her/his pain. Such individuals would greatly benefit from an objective pain recognition system which incorporates such modalities. Data sets consisting of reactions to elicited pain provide precious information for analyzing pain patterns and developing practical applications for detecting and monitoring pain. Amongst others, Walter et al.20 created the &#8220;BioVid Heat Pain Database&#8221;, a multimodal database that is publicly available and provides data from short-time induced painful heat stimuli and corresponding psychophysiological and visual reactions. The &#8220;SenseEmotion Database&#8221; of Velana et al.21 includes biosignals, videos, and paralinguistic information from volunteers affected by phasic heat pain and emotional stimuli.
While these databases are well suited for examining pain reactions, they are mostly based on one specific pain model. As pain differs in its quality (supposedly depending on the pain model) and in its duration, it also may differ in its physiological, visual, and paralinguistic correlates. To the best of the authors&#8217; knowledge, no multimodal studies or databases exist that combine two or more pain models and vary pain stimuli in intensity and duration in order to not only detect pain patterns but also distinguish between pain qualities.
This paper provides a protocol on how to conduct a complex psychophysiological experiment to elicit pain and simultaneously record physiological responses (e.g., ECG, EMG of Musculus trapezius, corrugator supercilii, and zygomaticus major, SCL) as well as video (e.g., facial expressions, body gestures, facial skin temperature) and audio data. Participants are stimulated with short (phasic) and longer lasting (tonic) heat and electrical pain stimuli that differ in intensity. A calibration phase prior to the experiment determines pain thresholds for each subject individually.
The study aims at collecting multimodal data for investigating pain (patterns) regarding intensity, quality and length by means of statistical methods, machine learning algorithms, etc. Additionally, the already collected data is planned to be published for academic research purposes under the name &#8220;X-ITE (Experimentally Induced Thermal and Electrical) Pain Database&#8221;. It may extend existing databases, such as BioVid Heat Pain and SenseEmotion20,21, and contribute to the further development, improvement, and/or evaluation of automated pain recognition systems in matters of validity, reliability, and real-time recognition.&#160;
The rest of the paper is organized in the following way. The protocol describes how to carry out the pain elicitation study step-by-step. Then, the representative results present the outcome of the experiment. Finally, the discussion covers critical steps, limitations, and benefits of the study followed by suggestions for future extensions.

<table><tbody><tr><td>PATHWAY Model ATS</td><td>Medoc Ltd., Ramat Yishai, Israel</td><td></td><td>Thermal Stimulator</td></tr><tr><td>30 mm x 30 mm ATS Thermode</td><td>Medoc Ltd., Ramat Yishai, Israel</td><td></td><td>Thermode</td></tr><tr><td>PATHWAY Software Arbel 6.3.7.22.1</td><td>Medoc Ltd., Ramat Yishai, Israel</td><td></td><td>Thermal Stimulator Software</td></tr><tr><td>Digitimer DS7A Current Stimulator</td><td>Digitimer Ltd., Hertfordshire, UK</td><td></td><td>Electrical Stimulator</td></tr><tr><td>Inquisit 5</td><td>Millisecond Software, Seattle, WA, USA</td><td></td><td>Software for triggering electrical stimuli</td></tr><tr><td>Analogue-To-Digital Converter</td><td>Wissenschaftliche Werkstatt Elektronik, University of Ulm, Ulm, Germany</td><td>custom built</td><td></td></tr><tr><td>BIOPAC MP150 System</td><td>BIOPAC Systems, Inc., Goleta, CA, USA</td><td></td><td>Biosignal Recording Hardware</td></tr><tr><td>AcqKnowledge Software 4.1.1</td><td>BIOPAC Systems, Inc., Goleta, CA, USA</td><td></td><td>Biosignal Recording Software</td></tr><tr><td>NTG-2 Dual Powered Directional Condenser Microphone</td><td>R&amp;Oslash;DE Microphones, Silverwater, Australia</td><td></td><td>Audio Recording Microphone</td></tr><tr><td>Kinect v2</td><td>Microsoft, Redmond, WA, USA</td><td></td><td>Body View Camera</td></tr><tr><td>AV Pike F-145C</td><td>Allied Vision Technologies GmbH, Stadtroda, Germany</td><td></td><td>Face Camera (frontal view)</td></tr><tr><td>AV Prosilica GT 1600C</td><td>Allied Vision Technologies GmbH, Stadtroda, Germany</td><td></td><td>Face Camera (side view)</td></tr><tr><td>PIR uc 180 Thermal Camera</td><td>InfraTec GmbH, Dresden, Germany</td><td></td><td>Thermal Face Camera</td></tr><tr><td>Synchronization Hardware</td><td>Werkstatt, IIKT, University of Magdeburg, Magdeburg, Germany</td><td>custom built</td><td>Hardware triggering of cameras, trigger signal is recorded by BIOPAC and Audacity</td></tr><tr><td>Recording and Synchronization Software</td><td>Philipp Werner, Neuro-Information Technology, University of Magdeburg, Magdeburg, Germany</td><td>custom software</td><td>Real-time recording, offline video encoding, and offline synchronization</td></tr><tr><td>Examination Couch</td><td>ClinicalCare GmbH, Bremen, Germany</td><td></td><td></td></tr><tr><td>Ag-AgCl Electrodes EL254 / EL254S (Reusable, 4mm recording diameter)</td><td>BIOPAC Systems, Inc., Goleta, CA, USA</td><td></td><td>Used to record EMG &lt;em&gt;M. corrugator&lt;/em&gt; and &lt;em&gt;M. zygomaticus&lt;/em&gt;</td></tr><tr><td>Ag-AgCl Electrodes BlueSensor P (Disposable, skin contact size: 34 mm diameter, measuring area 154 mm&lt;sup&gt;2&lt;/sup&gt;)</td><td>Ambu GmbH, Bad Nauheim, Germany</td><td></td><td>Used to record ECG and EMG &lt;em&gt;M. trapezius&lt;/em&gt;. Also used for electrical stimulation</td></tr><tr><td>Audacity 2.1.2</td><td>Dominic Mazzoni (Audacity)</td><td></td><td>Audio Recording Software</td></tr><tr><td>Cold Gel Pack</td><td>C+V Pharma Depot GmbH, Versmold, Germany</td><td></td><td></td></tr><tr><td>Panthenol 50mg/g</td><td>ratiopharm GmbH, Ulm, Germany</td><td></td><td>Ointment</td></tr><tr><td>Alumnium Profiles</td><td>item Industrietechnik GmbH, Solingen, Germany</td><td></td><td>Used to install all cameras and microphone</td></tr><tr><td>Electrode Gel GEL1</td><td>BIOPAC Systems, Inc., Goleta, CA, USA</td><td></td><td></td></tr><tr><td>ELPREP Skin Preparation Gel</td><td>BIOPAC Systems, Inc., Goleta, CA, USA</td><td></td><td></td></tr></tbody></table>

multi-modal signals for analyzing pain responses to thermal and electrical stimuli

The assessment of pain relies mostly on methods that require a person to communicate. However, for people with cognitive and verbal impairments, existing methods are not sufficient as they lack reliability and validity. To approach this problem, recent research focuses on an objective pain assessment facilitated by parameters of responses derived from physiology, and video and audio signals. To develop reliable automated pain recognition systems, efforts have been made in creating multimodal databases in order to analyze pain and detect valid pain patterns. While the results are promising, they only focus on discriminating pain or pain intensities versus no pain. In order to advance this, research should also consider the quality and duration of pain as they provide additional valuable information for more advanced pain management. To complement existing databases and the analysis of pain regarding quality and length, this paper proposes a psychophysiological experiment to elicit, measure, and collect valid pain reactions. Participants are subjected to painful stimuli that differ in intensity (low, medium, and high), duration (5 s / 1 min), and modality (heat / electric pain) while audio, video (e.g., facial expressions, body gestures, facial skin temperature), and physiological signals (e.g., electrocardiogram [ECG], skin conductance level [SCL], facial electromyography [EMG], and EMG of M. trapezius) are being recorded. The study consists of a calibration phase to determine a subject&#8217;s individual pain range (from low to intolerable pain) and a stimulation phase in which pain stimuli, depending on the calibrated range, are applied. The obtained data may allow refining, improving, and evaluating automated recognition systems in terms of an objective pain assessment. For further development of such systems and to investigate pain reactions in more detail, additional pain modalities such as pressure, chemical, or cold pain should be included in future studies. Recorded data of this study will be released as the &#8220;X-ITE Pain Database&#8221;.

Pain is perceived differently by any person and may express itself diversely in facial expressions, paralinguistic and/or physiological signals. The design of this study is suitable to analyze pain responses in numerous ways with respect to the underlying aims. The obtained data may allow answering research questions, such as: Are there specific pain response patterns? Do they differ regarding pain model and duration?
A total of 134 subjects participated in our experiment. The sex ratio was 50/50. We divided them in the following age groups: 1) 18-29 years (N = 49, 23 men, 26 women), 2) 30-39 years (N = 45, 23 men, 22 women), 3) 40-50 years (N = 40, 21 men, 19 women). The average age of all subjects was 31.4 (SD = 9.7), of all men = 33.4 (SD = 9.3) and of all women = 32.9 (SD = 10.2) years. The study took place at the Department of Medical Psychology of the University of Ulm, Germany.
The main outcome of this protocol is a data set of audio, video and psychophysiological signals reflecting the subjects&#8217; responses to pain stimuli. Table 1 provides a general overview on the technical features of the recorded signals and on the numbers of induced pain stimuli in the study.&#160;
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td colspan="5">Technical Features</td>
		</tr>
		<tr>
			<td>Signal:</td>
			<td colspan="2">Sampling Rate:</td>
			<td colspan="2">Attributes:</td>
		</tr>
		<tr>
			<td>Audio</td>
			<td colspan="2">44100 Hz</td>
			<td colspan="2">Mono, MP3 320 kbps</td>
		</tr>
		<tr>
			<td>Camera 1 (face, frontal view)</td>
			<td colspan="2">25 Hz</td>
			<td colspan="2">Color video: resolution 1384 x 1032, 
			HEVC encoded with libx265 (CRF 16, preset medium)</td>
		</tr>
		<tr>
			<td>Camera 2 (face, side view)</td>
			<td colspan="2">25 Hz</td>
			<td colspan="2">Color video: resolution 1620 x 840, 
			HEVC encoded with libx265 (CRF 16, preset medium)</td>
		</tr>
		<tr>
			<td>Body Camera</td>
			<td colspan="2">ca. 30 Hz</td>
			<td colspan="2">Color video: resolution 1500 x 600, 
			HEVC encoded with libx265 (CRF 16, preset medium); 
			Depth video: resolution 500 x 200, lossless encoding</td>
		</tr>
		<tr>
			<td>Thermal Camera</td>
			<td colspan="2">ca. 120.8 Hz</td>
			<td colspan="2">Surface temperature video: resolution 120 x 160, 
			grayscale MPEG-4-AVC encoded with&#160; libx264 
			(CRF 0,&#160; preset veryfast), 
			encoded temperature range 26.5-52.0 &#176;C (steps of 0.1)</td>
		</tr>
		<tr>
			<td>ECG</td>
			<td colspan="2">1000 Hz</td>
			<td colspan="2">Hardware filtered via BioPac: 35 Hz LP, 0.5 Hz HP, 
			50 Hz notch filter</td>
		</tr>
		<tr>
			<td>SCL</td>
			<td colspan="2">1000 Hz</td>
			<td colspan="2">Hardware filtered via BioPac: 10 Hz LP, no HP, 
			no notch filter</td>
		</tr>
		<tr>
			<td>EMG M. trapezius</td>
			<td colspan="2">1000 Hz</td>
			<td colspan="2">Hardware filtered via BioPac: 500 Hz LP, 10 Hz HP, 
			no notch filter</td>
		</tr>
		<tr>
			<td>EMG M. corrugator supercilii</td>
			<td colspan="2">1000 Hz</td>
			<td colspan="2">Hardware filtered via BioPac: 500 Hz LP, 10 Hz HP, 
			no notch filter</td>
		</tr>
		<tr>
			<td>EMG M. zygomaticus major</td>
			<td colspan="2">1000 Hz</td>
			<td colspan="2">Hardware filtered via BioPac: 500 Hz LP, 10 Hz HP, 
			no notch filter</td>
		</tr>
		<tr>
			<td>Stimuli</td>
			<td colspan="2">Thermal</td>
			<td colspan="2">Electrical</td>
		</tr>
		<tr>
			<td>Subjects:</td>
			<td>Phasic Stimuli (5 s):</td>
			<td>Tonic Stimuli (60 s):</td>
			<td>Phasic Stimuli (5 s):</td>
			<td>Tonic Stimuli (60 s):</td>
		</tr>
		<tr>
			<td>Per subject</td>
			<td>90 (30 per intensity)</td>
			<td>3 (1 per intensity)</td>
			<td>90 (30 per intensity)</td>
			<td>3 (1 per intensity)</td>
		</tr>
		<tr>
			<td>All (N = 134)</td>
			<td>12060 (4020 per intensity)</td>
			<td>402 (134 per intensity)</td>
			<td>12060 (4020 per intensity)</td>
			<td>402 (134 per intensity)</td>
		</tr>
		<tr>
			<td>Men (n = 67)</td>
			<td>6030 (2010 per intensity)</td>
			<td>201 (67 per intensity)</td>
			<td>6030 (2010 per intensity)</td>
			<td>201 (67 per intensity)</td>
		</tr>
		<tr>
			<td>Women (n = 67)</td>
			<td>6030 (2010 per intensity)</td>
			<td>201 (67 per intensity)</td>
			<td>6030 (2010 per intensity)</td>
			<td>201 (67 per intensity)</td>
		</tr>
	</tbody>
</table>
Table 1: Technical features and number of induced stimuli. The upper half (Technical Features) shows the sampling rates and attributes of the specific signals. The lower half (Stimuli) shows the numbers of the induced specific (thermal/electrical) pain stimuli for one subject, for all subjects and for each gender. (MP3 = Moving Picture Experts Group Layer-3 Audio, kbps = kilobits per second, HEVC = High Efficiency Video Coding, CRF = Constant Rate Factor, MPEG-4-AVC = Motion Picture Experts Group Layer-4 Video Advanced Video Coding, Hz = Hertz, &#176;C = degrees Celsius, s = seconds, ECG = Electrocardiogram, SCL = Skin Conductance Level, EMG = Electromyography, LP = low-pass filter, HP = high-pass filter, M. = Musculus).
A secondary outcome concerning the calibration phase of the study is presented in Table 2. It shows the mean stimulation temperatures and currents of pain intensities 1 and 3 (as calculated in step 5.11 of the protocol) for all subjects and additionally for the male and female subgroup.&#160;
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Stimuli</td>
			<td colspan="4">Thermal [in &#176;C] mean (SD)</td>
			<td colspan="4">Electrical [in mA] mean (SD)</td>
		</tr>
		<tr>
			<td>Subjects</td>
			<td>pH1</td>
			<td>pH3</td>
			<td>tH1</td>
			<td>tH3</td>
			<td>pE1</td>
			<td>pE3</td>
			<td>tE1</td>
			<td>tE3</td>
		</tr>
		<tr>
			<td>All (N = 134)</td>
			<td>44.03 (2.25)</td>
			<td>49.17 (1.20)</td>
			<td>42.50 (2.14)</td>
			<td>47.76 (1.02)</td>
			<td>1.63 (0.94)</td>
			<td>5.64 (2.72)</td>
			<td>1.69 (1.12)</td>
			<td>5.70 (2.59)</td>
		</tr>
		<tr>
			<td>Men (n = 67)</td>
			<td>44.56 (2.18)</td>
			<td>49.48 (0.89)</td>
			<td>43.11 (1.98)</td>
			<td>47.93 (1.04)</td>
			<td>1.94 (1.01)</td>
			<td>6.83 (3.02)</td>
			<td>1.96 (1.16)</td>
			<td>6.90 (2.72)</td>
		</tr>
		<tr>
			<td>Women (n = 67)</td>
			<td>43.51 (2.74)</td>
			<td>48.87 (1.39)</td>
			<td>41.89 (2.14)</td>
			<td>47.59 (0.98)</td>
			<td>1.32 (0.75)</td>
			<td>4.45 (1.70)</td>
			<td>1.43 (1.01)</td>
			<td>4.51 (1.80)</td>
		</tr>
	</tbody>
</table>
Table 2: Mean stimulation temperatures and currents of pain intensities 1 and 3. (pH1, pH3 = phasic heat pain with intensity 1, 3; tH1, tH3 = tonic heat pain with intensity 1, 3; pE1, pE3 = phasic electrical pain with intensity 1, 3; tE1, tE3 = tonic electrical pain with intensity 1, 3; &#176;C = degrees Celsius; mA = milliampere, SD = standard deviation).
If all steps of the protocol are conducted carefully and no technical problems occur (in terms of computer or recording device crashes, etc.), a successful outcome may look similar as depicted in Figure 4. All signals are of high quality and not affected by external sources of interferences. The participant is clearly visible in every camera.&#160;
<img alt="Figure 4" class="xfigimg" src="/files/ftp_upload/59057/59057fig4.jpg" /> 
Figure 4: Example data from a successful experiment. The figure depicts recorded signals a few seconds before, during and after an intense pain stimulus. All signals are non-filtered and synchronized in time. For clarity, only representative screenshots of the video signals are shown here. (EMG = Electromyography, SCL = Skin Conductance Level, ECG = Electrocardiogram, M. = Musculus, s = seconds). <a href="https://jove.unicartagenaproxy.elogim.com/files/ftp_upload/59057/59057fig4large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
However, unexpected incidents may cause the data to become noisy or corrupted. Besides computer or recording device crashes, the coming-off of electrodes (especially reusable electrodes with small diameter which are attached by means of double-sided adhesive collars) mostly leads to unusable signals. As an example for a sub-optimal data set, Figure 5 shows the moment when an EMG electrode comes off and renders the corresponding signal useless.&#160;
<img alt="Figure 5" class="xfigimg" src="/files/ftp_upload/59057/59057fig5.jpg" /> 
Figure 5: Example data from a sub-optimal experiment. The red circle indicates the time one of the EMG electrodes (M. zygomaticus major) fell off the subject&#8217;s cheek. This might have been due to sweat or head movement. From this moment on, the signal was lost. (EMG = Electromyography, SCL = Skin Conductance Level, ECG = Electrocardiogram, M. = Musculus, s = seconds). <a href="https://jove.unicartagenaproxy.elogim.com/files/ftp_upload/59057/59057fig5large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
Due to ethical guidelines, the maximum intensities of thermal and electrical stimuli had to be restricted. Regarding thermal calibration control part (see supplementary file), 37 subjects (31 men, 6 women) reached the given cutoff of 50.5 &#176;C (ratio = 37/134 = 27.61 %). As for thermal calibration part 1, 60 participants (39 men, 21 women) reached the cutoff of 50.0 &#176;C (ratio = 60/134 = 44.78 %) and concerning part 2, 57 persons (37 men, 20 women) reached the cutoff of 49.5 &#176;C (ratio = 57/134 = 42.54 %). The cutoff for both electrical calibration parts was 25 mA. None of the 134 subjects reached it.
As we plan to publish the data (see next paragraph), the data sets of participants who have reached the cutoffs will additionally be marked and their subjective pain ratings for the corresponding cutoffs will be included.
We would like to point out that the main focus of the protocol is obtaining multi-modal signals for analyzing thermal and electrical pain. Therefore, no other results are discussed here. After checking and excluding data sets due to missing data or rejected written consent for data sharing, the data sets of this study will be made available under the name &#8220;X-ITE Pain Database&#8221;. For further information on when and how to obtain the X-ITE Pain DB please visit https://github.com/philippwerner/pain-database-list.
Supplementary File 1.&#160;<a href="https://jove.unicartagenaproxy.elogim.com/files/ftp_upload/59057/Supplementary_File_1.docx" target="_blank">Please click here to download this file.</a>

Watch this Scientific Journal Video about Multi-Modal Signals for Analyzing Pain Responses to Thermal and Electrical Stimuli at JoVE.com

Multi-Modal Signals for Analyzing Pain Responses to Thermal and Electrical Stimuli

This article focuses on the experimental elicitation of pain through heat (thermal) and electrical stimulation while recording physiological, visual, and paralinguistic responses. It aims at collecting valid multimodal data for analyzing pain based on its intensity, quality, and duration.&#160;

The assessment of pain relies mostly on methods that require a person to communicate. However, for people with cognitive and verbal impairments, existing ...

multi-modal-signals-for-analyzing-pain-responses-to-thermal

Universidad de Cartagena UDEC

Research

JoVE Journal

Behavior

10.4K Views.  Ulm University. This article focuses on the experimental elicitation of pain through heat (thermal) and electrical stimulation while recording physiological, visual, and paralinguistic responses. It aims at collecting valid multimodal data for analyzing pain based on its intensity, quality, and duration. 

Video: Multi-Modal Signals for Analyzing Pain Responses to Thermal and Electrical Stimuli

Determining Pain Detection and Tolerance Thresholds Using an Integrated, Multi-Modal Pain Task Battery

Human pain models are useful in the assessing the analgesic effect of drugs, providing information about a drug&#39;s pharmacology and identify potentially suitable therapeutic populations. The need to use a comprehensive battery of pain models is highlighted by studies whereby only a single pain model, thought to relate to the clinical situation, demonstrates lack of efficacy. No single experimental model can mimic the complex nature of clinical pain. The integrated, multi-modal pain task&#160;battery presented here encompasses the electrical stimulation task, pressure stimulation task, cold pressor task, the UVB inflammatory model which includes a thermal task and a paradigm for inhibitory conditioned pain modulation. These human pain models have been tested for predicative validity and reliability both in their own right and in combination, and can be used repeatedly, quickly, in short succession, with minimum burden for the subject and with a modest quantity of equipment. This allows a drug to be fully characterized and profiled for analgesic effect which is especially useful for drugs with a novel or untested mechanism of action.

Human pain models are valuable tools used to assess the analgesic potential of novel compounds and predict their clinical efficacy, especially when used in an integrated manner. Although implementation of these models is complex, with proper execution, the pain models described in this protocol can provide predictive and reliable results.

Human pain models are useful in the assessing the analgesic effect of drugs, providing information about a drug&#39;s pharmacology and identify ...

A Protocol of Manual Tests to Measure Sensation and Pain in Humans

Numerous qualitative and quantitative techniques can be used to test sensory nerves and pain in both research and clinical settings. The current study demonstrates a quantitative sensory testing protocol using techniques to measure tactile sensation and pain threshold for pressure and heat using portable and easily accessed equipment. These techniques and equipment are ideal for new laboratories and clinics where cost is a concern or a limiting factor. We demonstrate measurement techniques for the following: cutaneous mechanical sensitivity on the arms and legs (von-Frey filaments), radiant and contact heat sensitivity (with both threshold and qualitative assessments using the Visual Analog Scale (VAS)), and mechanical pressure sensitivity (algometer, with both threshold and the VAS). The techniques and equipment described and demonstrated here can be easily purchased, stored, and transported by most clinics and research laboratories around the world. A limitation of this approach is a lack of automation or computer control. Thus, these processes can be more labor intensive in terms of personnel training and data recording than the more sophisticated equipment. We provide a set of reliability data for the demonstrated techniques. From our description, a new laboratory should be able to set up and run these tests and to develop their own internal reliability data.

The goal of this procedure is to demonstrate a battery of quantitative techniques for sensory and pain measurement in humans. The equipment and techniques described are commonly found in pain clinics or are easy to obtain.

Numerous qualitative and quantitative techniques can be used to test sensory nerves and pain in both research and clinical settings. The current study ...

Psychophysically-anchored, Robust Thresholding in Studying Pain-related Lateralization of Oscillatory Prestimulus Activity

In perceptual studies, it is often important to objectively assess the equality of delivered stimulation across participants or to quantify the intra-individual sensation magnitude that is evoked by stimulation over multiple trials. This requires a robust mapping of stimulus magnitude to perceived intensity and is commonly achieved by psychophysical estimation methods such as the staircase procedure. Newer, more efficient procedures like the QUEST algorithm fit a psychophysical function to the data in real time while at the same time maximizing the efficiency of data collection. A robust estimate of the threshold intensity between painful and nonpainful perceptions can then be used to reduce the influence of variations in sensory input in subsequent analyses of oscillatory brain activity. By stimulating at a constant threshold intensity determined by an adaptive estimation procedure, the variance in the ratings can be directly attributed to perceptual processes. Oscillatory activity can then be contrasted between &#34;pain&#34; and &#34;no-pain&#34; trials directly, yielding activity that closely relates to perceptual classification processes in nociception.

Psychophysical methods such as the QUEST estimation procedure can efficiently yield robust estimates of the stimulation intensity at which nonpainful sensations transition into painful sensations. By stimulating repeatedly at the threshold intensity, the variability in rating responses can directly be attributed to perceptual classifications in subsequent analyses.

In perceptual studies, it is often important to objectively assess the equality of delivered stimulation across participants or to quantify the ...

Determining heat and mechanical pain threshold in inflamed skin of human subjects

In a previous article in the Journal of Visualized Experiments we have demonstrated skin microdialysis techniques for the collection of tissue-specific nociceptive and inflammatory biochemicals in humans. In this article we will show pain-testing paradigms that are often used in tandem with microdialysis procedures. Combining pain tests with microdialysis provides the critical link between behavioral and biochemical data that allows identifying key biochemicals responsible for generating and propagating pain.
Two models of evoking pain in inflamed skin of human study participants are shown. The first model evokes pain with aid of heat stimuli. Heat evoked pain as described here is predominantly mediated by small, non-myelinated peripheral nociceptive nerve fibers (C-fibers). The second model evokes pain via punctuated pressure stimuli. Punctuated pressure evoked pain is predominantly mediated by small, myelinated peripheral nociceptive nerve fibers (A-delta fibers). The two models are mechanistically distinct and independently examine nociceptive processing by the two major peripheral nerve fiber populations involved in pain signaling.
Heat pain is evoked with aid of the TSA II, a commercially available thermo-sensory analyzer (Medoc Advanced Medical Systems, Durham, NC). Stimulus configuration and delivery is handled with aid of specific software. Thermodes vary in size and shape but in principle consist of a metal plate that can be heated or cooled at various rates and for different periods of time. Algorithms assessing heat-evoked pain are manifold. In the experiments shown here, study participants are asked to indicate at what point they start experiencing pain while the thermode in contact with skin is heated at a predetermined rate starting at a temperature that does not evoke pain. The thermode temperature at which a subject starts experiencing pain constitutes the heat pain threshold.
Mechanical pain is evoked with punctuated probes. Such probes are commercially available from several manufacturers (von Frey hairs). However, the accuracy of von Frey hairs has been criticized and many investigators use custom made punctuated pressure probes. In the experiments shown here eight custom-made punctuated probes of different weights are applied in consecutive order, a procedure called up-down algorithm, to identify perceptional deflection points, i.e., a change from feeling no pain to feeling pain or vice versa. The average weight causing a perceptional deflection constitutes the mechanical pain threshold.

Algorithms assessing heat and mechanical pain thresholds in experimentally inflamed skin of human study subjects are shown. The two pain testing paradigms independently examine nociceptive processing by the two major peripheral nerve fiber populations transmitting pain, i.e., non-myelinated C fibers and small myelinated A-delta fibers.

In a previous article in the Journal of Visualized Experiments we have demonstrated skin microdialysis techniques for the collection of tissue-specific ...

Biology

Chronic Post-Ischemia Pain Model for Complex Regional Pain Syndrome Type-I in Rats

Complex regional pain syndrome type-I (CRPS-I) is a neurological disease that causes severe pain among patients and remains an unresolved medical condition. However, the underlying mechanisms of CRPS-I have yet to be revealed. It is known that ischemia/reperfusion is one of the leading factors that causes CRPS-I. By means of prolonged ischemia and reperfusion of the hind limb, the rat chronic post-ischemia pain (CPIP) model has been established to mimic CRPS-I. The CPIP model has become a well-recognized animal model for studying the mechanisms of CRPS-I. This protocol describes the detailed procedures involved in the establishment of the rat model of CPIP, including anesthesia, followed by ischemia/reperfusion of the hind limb. Characteristics of the rat CPIP model are further evaluated by measuring the mechanical and thermal hypersensitivities of the hind limb as well as the nocifensive responses to acute capsaicin injection. The rat CPIP model exhibits several CRPS-I-like manifestations, including hind limb edema and hyperemia in the early stage after establishment, persistent thermal and mechanical hypersensitivities, and increased nocifensive responses to acute capsaicin injection. These characteristics render it a suitable animal model for further investigation of the mechanisms involved in CRPS-I.

Provided here is a protocol that details steps to establish an animal model of chronic post-ischemia pain (CPIP). This is a well-recognized model mimicking human complex regional pain syndrome type-I. Mechanical and thermal hypersensitivities are further evaluated, as well as capsaicin-induced nocifensive behaviors observed in the CPIP rat model.

Complex regional pain syndrome type-I (CRPS-I) is a neurological disease that causes severe pain among patients and remains an unresolved medical ...

Back Mechanical Sensitivity Assessment in the Rat for Mechanistic Investigation of Chronic Back Pain

Low back pain is the leading cause of disability worldwide, with dramatic personal, economic, and social consequences. To develop novel therapeutics, animal models are needed to examine the mechanisms and effectiveness of novel therapies from a translational perspective. Several rodent models of back pain are used in current investigations. Surprisingly, however, no standardized behavioral test was validated to assess mechanical sensitivity in back pain models. This is critical to confirm that animals with presumed back pain present local hypersensitivity to nociceptive stimuli, and to monitor sensitivity during interventions designed to relieve back pain. The objective of this study is to lay down a simple and accessible test to assess mechanical sensitivity in the back of rats. A test cage was fabricated specifically for this method; length x width x height: 50 x 20 x 7 cm, having a stainless-steel mesh on the top. This test cage allows the application of mechanical stimuli to the back. To perform the test, the back of the animal is shaved in the region of interest, and the test area is marked to repeat the test on different days, as needed. The mechanical threshold is determined with Von Frey filaments applied to the paraspinal muscles, utilizing the up-down method described previously. The positive responses include (1) muscle twitching, (2) arching (back extension), (3) rotation of the neck (4) scratching or licking the back, and (5) escaping. This behavioral test (Back Mechanical Sensitivity (BMS) test) is useful for mechanistic research with rodent models of back pain for the development of therapeutic interventions for the prevention and management of back pain.

To develop novel therapeutic interventions for the prevention and management of back pain, animal models are required to examine the mechanisms and effectiveness of these therapies from a translational perspective. The present protocol describes the BMS test, a standardized method to assess back mechanical sensitivity in the rat.

Low back pain is the leading cause of disability worldwide, with dramatic personal, economic, and social consequences. To develop novel therapeutics, ...

Assessment of Nerve Injury-Induced Mechanical Hypersensitivity in Rats Using an Orofacial Operant Pain Assay

Pain has sensory and affective components. Unlike traditional, reflex-based pain assays, operant pain assays can produce more clinically relevant results by addressing the cognitive and motivational aspects of pain in rodents. This paper presents a protocol for assessing mechanical hypersensitivity following chronic constriction injury of the infraorbital nerves (CCI-ION) in rats using an orofacial operant pain system. Before CCI-ION surgery, rats were trained in an orofacial pain assessment device (OPAD) to drink sweetened condensed milk while making facial contact with the metal spiked bars and lick-tube.
In this assay, rats can choose between receiving milk as a positive reinforcer or escaping an aversive mechanical stimulus that is produced by a vertical row of small pyramid-shaped spikes on each side of the reward access hole. Following 2 weeks of training in the OPAD and before the CCI-ION surgery, baseline mechanical sensitivity data were recorded for 5 days for each rat during a 10 min testing session. During a session, the operant system automatically records the number of reward bottle activations (licks) and facial contacts, contact duration, and latency to the first lick, among other measures.
Following baseline measurements, rats underwent either CCI-ION or sham surgery. In this protocol, mechanical hypersensitivity was quantified by measuring the number of licks, latency to the first lick, the number of contacts, and the ratio of licks to facial contacts (L/F). The data showed that CCI-ION resulted in a significant decrease in the number of licks and the L/F ratio and an increase in the latency to the first lick, indicating mechanical hypersensitivity. These data support the use of operant-based pain assays to assess mechanical pain sensitivity in preclinical pain research.

This protocol describes the assessment of mechanical hypersensitivity in a rat model of neuropathic orofacial pain using an operant-based orofacial pain assessment device.

Pain has sensory and affective components. Unlike traditional, reflex-based pain assays, operant pain assays can produce more clinically relevant results ...

Dynamic Quantitative Sensory Testing to Characterize Central Pain Processing

Central facilitation and modulation of incoming nociceptive signals play an important role in the perception of pain. Disruption in central pain processing is present in many chronic pain conditions and can influence responses to specific therapies. Thus, the ability to precisely describe the state of central pain processing has profound clinical significance in both prognosis and prediction. Because it is not practical to record neuronal firings directly in the human spinal cord, surrogate behavior tests become an important tool to assess the state of central pain processing. Dynamic QST is one such test, and can probe both the ascending facilitation and descending modulation of incoming nociceptive signals via TS and CPM, respectively. Due to the large between-individual variability in the sensitivity to noxious signals, standardized TS and CPM tests may not yield any meaningful data in up to 50% of the population due to floor or ceiling effects. We present methodologies to individualize TS and CPM so we can capture these measures in a broader range of individuals than previously possible. We have used these methods successfully in several studies at the lab, and data from one ongoing study will be presented to demonstrate feasibility and potential applications of the methods.

By assessing pain in response to repetitive or different types of standardized stimuli, dynamic quantitative sensory testing (QST) can reveal changes in the central processing of pain. We present methods to optimize and individualize two dynamic QST measures: temporal summation (TS) and conditioned pain modulation (CPM).

Central facilitation and modulation of incoming nociceptive signals play an important role in the perception of pain. Disruption in central pain ...

Neuroscience

In Vivo Calcium Imaging of Neuronal Ensembles in Networks of Primary Sensory Neurons in Intact Dorsal Root Ganglia

Ca2+ imaging can be used as a proxy for cellular activity, including action potentials and various signaling mechanisms involving Ca2+ entry into the cytoplasm or the release of intracellular Ca2+ stores. Pirt-GCaMP3-based Ca2+ imaging of primary sensory neurons of the dorsal root ganglion (DRG) in mice offers the advantage of simultaneous measurement of a large number of cells. Up to 1,800 neurons can be monitored, allowing neuronal networks and somatosensory processes to be studied as an ensemble in their normal physiological context at a populational level in vivo. The large number of neurons monitored allows the detection of activity patterns that would be challenging to detect using other methods. Stimuli can be applied to the mouse hindpaw, allowing the direct effects of stimuli on the DRG neuron ensemble to be studied. The number of neurons producing Ca2+ transients as well as the amplitude of Ca2+ transients indicates sensitivity to specific sensory modalities. The diameter of neurons provides evidence of activated fiber types (non-noxious mechano vs. noxious pain fibers, A&#946;, A&#948;, and C fibers). Neurons expressing specific receptors can be genetically labeled with td-Tomato and specific Cre recombinases together with Pirt-GCaMP. Therefore, Pirt-GCaMP3 Ca2+ imaging of DRG provides a powerful tool and model for the analysis of specific sensory modalities and neuron subtypes acting as an ensemble at the populational level to study pain, itch, touch, and other somatosensory signals.

In Vivo Calcium Imaging of Neuronal Ensembles in Networks of Primary Sensory Neurons in Intact Dorsal Root Ganglia

This protocol describes the surgical exposure of the dorsal root ganglion (DRG) followed by GCaMP3 (genetically-encoded Ca2+ indicator; Green Fluorescent Protein-Calmodulin-M13 Protein 3) Ca2+ imaging of the neuronal ensembles using Pirt-GCaMP3 mice while applying a variety of stimuli to the ipsilateral hind paw.

Ca2+ imaging can be used as a proxy for cellular activity, including action potentials and various signaling mechanisms involving Ca2+ entry into the ...

Open-Source Real-Time Closed-Loop Electrical Threshold Tracking for Translational Pain Research

Nociceptors are a class of primary afferent neurons that signal potentially harmful noxious stimuli. An increase in nociceptor excitability occurs in acute and chronic pain conditions. This produces abnormal ongoing activity or reduced activation thresholds to noxious stimuli. Identifying the cause of this increased excitability is required for the development and validation of mechanism-based treatments. Single-neuron electrical threshold tracking can quantify nociceptor excitability. Therefore, we have developed an application to allow such measurements and demonstrate its use in humans and rodents. APTrack provides real-time data visualization and action potential identification using a temporal raster plot. Algorithms detect action potentials by threshold crossing and monitor their latency after electrical stimulation. The plugin then modulates the electrical stimulation amplitude using an up-down method to estimate the electrical threshold of the nociceptors. The software was built upon the Open Ephys system (V0.54) and coded in C++ using the JUCE framework. It runs on Windows, Linux, and Mac operating systems. The open-source code is available (<a data-saferedirecturl="https://www.google.com/url?q=https://github.com/Microneurography/APTrack&amp;source=gmail&amp;ust=1680789829274000&amp;usg=AOvVaw0nMk9J_EI2jUn8SlmC5JJm" href="https://github.com/Microneurography/APTrack" target="_blank">https://github.com/Microneurography/APTrack</a>). The electrophysiological recordings were taken from nociceptors in both a mouse skin-nerve preparation using the teased fiber method in the saphenous nerve and in healthy human volunteers using microneurography in the superficial peroneal nerve. Nociceptors were classified by their response to thermal and mechanical stimuli, as well as by monitoring the activity-dependent slowing of the conduction velocity. The software facilitated the experiment by simplifying the action potential identification through the temporal raster plot. We demonstrate real-time closed-loop electrical threshold tracking of single-neuron action potentials during&#160;in vivo&#160;human microneurography, for the first time, and during&#160;ex vivo&#160;mouse electrophysiological recordings of C-fibers and A&#948;-fibers. We establish proof of principle by showing that the electrical threshold of a human heat-sensitive C-fiber nociceptor is reduced by heating the receptive field. This plugin enables the electrical threshold tracking of single-neuron action potentials and allows the quantification of changes in nociceptor excitability.

APTrack is a software plugin developed for the Open Ephys platform that enables real-time data visualization and the closed-loop electrical threshold tracking of neuronal action potentials. We have successfully used this in microneurography for human C-fiber nociceptors and mouse C-fiber and A&#948;-fiber nociceptors.

Nociceptors are a class of primary afferent neurons that signal potentially harmful noxious stimuli. An increase in nociceptor excitability occurs in ...

Multi-Modal Signals for Analyzing Pain Responses to Thermal and Electrical Stimuli

Summary

Explore More Videos

Chapters in this video

Determining Pain Detection and Tolerance Thresholds Using an Integrated, Multi-Modal Pain Task Battery

A Protocol of Manual Tests to Measure Sensation and Pain in Humans

Psychophysically-anchored, Robust Thresholding in Studying Pain-related Lateralization of Oscillatory Prestimulus Activity

Determining heat and mechanical pain threshold in inflamed skin of human subjects

Chronic Post-Ischemia Pain Model for Complex Regional Pain Syndrome Type-I in Rats

Back Mechanical Sensitivity Assessment in the Rat for Mechanistic Investigation of Chronic Back Pain

Assessment of Nerve Injury-Induced Mechanical Hypersensitivity in Rats Using an Orofacial Operant Pain Assay

Dynamic Quantitative Sensory Testing to Characterize Central Pain Processing

In Vivo Calcium Imaging of Neuronal Ensembles in Networks of Primary Sensory Neurons in Intact Dorsal Root Ganglia

Open-Source Real-Time Closed-Loop Electrical Threshold Tracking for Translational Pain Research