Discrimination capability of linear and nonlinear gait features in group classification.

The variability of human movement can be defined as normal variations occurring in motor activity and quantified using linear statistics or nonlinear methods. In the human movement field, linear and nonlinear measures of variability have been used to discriminate groups and conditions in different contexts. Indeed, some authors support the idea that these gait features provide complementary information about movement. However, it is unclear which type of gait variability measure best discriminates different groups or conditions, as a comparison of the discrimination capacity between linear and nonlinear gait variability features in different groups has not been assessed. Therefore, the main objective of this study was to test the discrimination capacity of linear and nonlinear gait features to determine which type of feature would be the most efficient for discriminating older and younger adults and between lower limb amputees and nonamputees using classification algorithms. Data from previously published studies were used. The classification task was performed using the k-nearest neighbors and random forest algorithms. Our results showed that using a combination of linear and nonlinear features resulted in the highest mean accuracy rates (>90%) in group classification, reinforcing the idea that these features are complementary and express different aspects of movement.

Margins of stability of persons with transtibial or transfemoral amputations walking on sloped surfaces.

Gait is a complex motor skill. However, most falls in humans occur during gait, and people with lower limb amputation have an increased risk of falls. Thus, this study evaluated the stability of persons with unilateral amputation by quantifying the margin of stability (MoS) during gait, to contribute to understanding the strategies adopted by these people to reduce falls. The participants were divided into 3 groups: persons with transtibial amputations (n = 12, 32.27 ± 10.10 years, 76.9 ± 10.3 kg, 1.74 ± 0.06 m); persons with transfemoral amputations (n = 13, 32.21 ± 8.34 years, 72.55 ± 10.23 kg, 1.73 ± 0.05 m); and controls (n = 15, 32.2 ± 10.17 years, 75.4 ± 9.25 kg, 1.75 ± 0.05 m), who walked for 4 min on a level and sloped (8% down and up) treadmill. The pelvic and foot marker kinematic data were used to estimate the center of mass and base of support, and from these, the MoS was estimated. Although both groups of persons with amputations showed higher values for the ML MoS than did the control group (transtibial: 8.81 ± 1.79, 8.97 ± 1.74, 8.79 ± 1.76, transfemoral: 10.15 ± 2.03, 10.60 ± 1.98, 10.11 ± 1.75, control: 8.13 ± 1.30, 7.18 ± 1.85, 8.15 ± 1.57, level, down, and up, respectively), only the transfemoral group presented a significant higher value compared to the control group. Our findings suggest that the documented limitations in persons with amputations, especially with transfemoral amputation, are exacerbated in situations that require more skills, such as walking on sloped surfaces, triggering protective mechanisms.

Effects of triceps surae fatigue and weight training level on gait variability and local stability in young adults.

Muscle fatigue negatively affects gait, and the changes in gait pattern due to muscle fatigue is influenced by which muscles are fatigued and pre-existing physical activity levels. However, how these factors alter gait stability and variability, measures related to risk of fall, remains unclear. To explore how muscular fatigue affects linear and nonlinear gait features in young adults, the effects of triceps surae fatigue and weight training level on gait variability and local stability, as well as a 12-min recovery time of post-fatigue period, were evaluated in young adults (trained and untrained groups). Some features were estimated, i.e., (i) step length (SL) and step frequency (SF), (ii) average standard deviation of trunk acceleration along strides (VAR), and (iii) local dynamic stability (LDS; maximum Lyapunov exponent). LDS presented a significant increase in the anterior-posterior direction with recovery to trained group. SL and SF changed immediately post-fatigue and recovered for both groups, while VAR increased significantly in all directions, with a recovery in the vertical direction for both groups and in the medial-lateral direction for trained group. Localized fatigue affected the analyzed gait variables independent of the participant's training condition, and an interval of 12 min does not seem to be enough for a complete recovery, suggesting a longer recovery period after tasks involving localized triceps surae fatigue to guarantee basal levels of gait variability and local stability. Graphical abstract Flow chart of the experimental protocol. A) Pre-fatigue: 4 min walking at PWS. B) Post-fatigue: first 4 min walking after fatigue protocol. C) Post-fatigue: second 4 min walking after fatigue protocol. D) Post-fatigue: third 4 min walking after fatigue protocol (PWS, preferred walking speed; AP, anterior-posterior; V, vertical; ML, medial-lateral).

Effects of inclined surfaces on gait variability and stability in unilateral lower limb amputees.

This study aims to analyze gait variability and stability of individuals with amputation walking on upward (8%), horizontal (0%), and downward (- 8%) inclines, by using linear and nonlinear descriptors. Trunk linear variability and gait spatiotemporal parameters were evaluated. Nonlinear variability (local dynamic stability-LDS), was estimated by the maximum Lyapunov exponent (λ) computed from a trunk marker velocity. The gait descriptors were compared among three distinct groups (N participants): unilateral transtibial amputees (TTA, N = 12); unilateral transfemoral amputees (TFA, N = 13); control group (CT, N = 15). For step width and support phase, the effect of inclination was greater for TFA group, especially in the DOWN condition. Linear variability was higher for amputees (TFA and TTA) especially in the UP condition in the medial-lateral and anterior-posterior directions. TTA and TFA groups presented greater λ values than CT group in medial-lateral direction indicating decreased LDS, but TFA group presented smaller λ values than TTA and CT groups in the V direction. Our findings showed that inclination introduced significant changes in the estimated parameters for all groups, with greater changes for amputee groups. Furthermore, the level of amputation directly affects the analyzed gait parameters being the TFA group the one which presents greater changes. Graphical abstract The objective of this study was to analyze gait variability of individuals with amputation walking on (A) upward (+ 8%), (B) horizontal (0%), and (C) downward (- 8%) inclines, by using linear and nonlinear biomechanical descriptors. Linear measures of variability, such trunk variability and gait spatiotemporal parameters were evaluated. Nonlinear variability was estimated by the exponent of divergence (maximum Lyapunov exponent) of the velocity of a marker fixed in the subject's trunk while walking on inclined surfaces.

Linear and nonlinear measures of gait variability after anterior cruciate ligament reconstruction.

The objective of this study was to assess gait variability after anterior cruciate ligament reconstruction (ACLR), as an indicative of possible altered gait pattern and a measure of recovery compared to control subjects. Forty subjects (32 male), divided into 4 groups of 10 participants, were enrolled in the study: a control group (CG), and observational groups OG-I (90 days), OG-II (180 days), and OG-III (360 days) after ACLR. All subjects underwent the same rehabilitation program for six months. For kinematic recording, each subject walked on a treadmill for 4 min at a preferred walking speed. Linear gait variability was assessed using average standard deviation (VAR) and normalized root mean square of medial-lateral (ML) trunk acceleration (RMSratio). Gait stability was assessed using the margin of stability (MoS) and local dynamic stability (LDS), and nonlinear variability was assessed using sample entropy (SEn). Compared to the CG, the VAR ML increased significantly in the OG-I group and decreased incrementally in OG-II and OG-III. MoS increased significantly in the OG-I group and tends to maintain in OG-II and OG-III, while LDS was greater in the CG and decreased incrementally in the OG groups. The SEn was higher in the OG groups than in the CG and increased in OG-II and OG-III. The results indicated that ACL reconstruction was followed by a progressive increase in stability and a progressive increase in variability over the postoperative rehabilitation period. In terms of stability and gait variability, six months of physiotherapy for rehabilitation after ACL reconstruction appears to be effective, but it is insufficient for a complete recovery as compared to healthy individuals.

On the Use of Non-Contact Capacitive Sensors for the Assessment of Postural Hand Tremor of Individuals with Parkinson's Disease.

Parkinsonian tremor manifests in different types: rest, postural, and action tremors. The postural tremor occurs while a body part is held straight out from the body in a stable position against gravity. The Unified Parkinson's Disease Rating Scale (UPDRS), which is a subjective assessment performed by the qualitative judgment of neurologists, is the clinical standard for parkinsonian tremor assessment. Despite the common use of subjective methods, inertial measurement unit (IMU) sensors are largely used in many studies as a motion capture system to objective assessment of tremors. However, this kind of sensor must be attached to the patient's body, it limits the patient's movements and requires specific techniques for correct positioning in the limb. In this sense, non-contact capacitive (NCC) sensors are an alternative proposed in this research to record the motor activity of the hand and wrist during a pose against gravity. In order to assess the postural tremor and evaluate this novel sensing technology, data from ten subjects, five with Parkinson's disease (PD) and five neurologically healthy (H) matched in age and sex, were collected. We analyzed the instantaneous mean frequency (IMNF) of the signals from NCC and gyroscope sensors for both groups. The selected descriptive statistical variables allowed discrimination (p <; 0.05) among subjects from H and PD groups while using the gyroscope or the NCC sensor. The obtained results indicate that the NCC sensor can measure the postural hand tremor, and also that frequency features extracted from the collected signals can be used to discriminate subjects from both groups.

On the Use of t-Distributed Stochastic Neighbor Embedding for Data Visualization and Classification of Individuals with Parkinson's Disease.

Parkinson's disease (PD) is a neurodegenerative disorder that remains incurable. The available treatments for the disorder include pharmacologic therapies and deep brain stimulation (DBS). These approaches may cause distinct side effects and motor responses. This work presents the application of t-distributed stochastic neighbor embedding (t-SNE), which is a machine learning algorithm for nonlinear dimensionality reduction and data visualization, for the problem of discriminating neurologically healthy individuals from those suffering from PD (treated with levodopa and DBS). Furthermore, the assessment of classification methods is presented. Inertial and electromyographic data were collected while the subjects executed a sequence of four motor tasks. The results were focused on the comparison of the classification performance of a support vector machine (SVM) while discriminating two-dimensional feature sets estimated from Principal Component Analysis (PCA), Sammon's mapping, and t-SNE. The results showed visual and statistical differences for all three investigated groups. Classification accuracy for PCA, Sammon's mapping, and t-SNE was, respectively, 73.5%, 78.6%, and 96.9% for the training set and 67.8%, 74.1%, and 76.6% for the test set. The possibility of discriminating healthy individuals from those with PD treated with levodopa and DBS highlights the fact that each treatment method produces distinct motor behavior. The scatter plots resulting from t-SNE could be used in the clinical practice as an objective tool for measuring the discrepancy between normal and abnormal motor behaviors, being thus useful for the adjustment of treatments and the follow-up of the disorder.

Gait variability analysis through phase portrait estimated from the Hilbert transform.

Gait variability has been used to evaluate the ability to control gait. Several studies approached this topic by analysing the influence of different conditions on gait variability, such as different walk speeds, inclined surfaces, load carriage, or comparing characteristics of subject groups, such as age, sedentarism and impairment level. The aim of this study was to develop and assess a new method, based on the property of the Hilbert transform of easily creating a phase portrait from a single time series, capable of estimating variability within gait cycles. The obtained results were based on a comparison of the proposed method with a traditional one whilst analysing a data set related to gait evaluation on inclined surfaces. Furthermore, the influence of noise over the estimated gait variability was assessed. The results showed that the proposed method is less sensitive to the presence of noise, with the advantage of not relying on signal interpolation, being thus an alternative to the analysis of gait variability.

Effects of backpack load and positioning on nonlinear gait features in young adults.

Overloaded backpacks can cause changes in posture and gait dynamic balance. Therefore, the aim of this study was to assess gait regularity and local dynamic stability in young adults as they carried a backpack in different positions, and with different loads. Twenty-one healthy young adults participated in the study, carrying a backpack that was loaded with 10 and 20% of their body weight (BW). The participants walked on a level treadmill at their preferred walking speeds for 4 min under different conditions of backpack load and position (i.e. with backpack positioned back bilaterally, back unilaterally, frontally or without a backpack). Results indicate that backpack load and positioning significantly influence gait stability and regularity, with the exception of the 10% BW bilateral back position. Therefore, the recommended safe load for school-age children and adolescents (10% of BW) should also be considered for young adults. Practitioner summary: Increase in load results in changes in posture, muscle activity and gait parameters, so we investigated the gait adaptations related to regularity and stability. Conditions with high backpack loads significantly influenced gait stability and regularity in a position-dependent manner, except for 10% body weight bilateral back position.

Objective Assessment of Bradykinesia Estimated from the Wrist Extension in Older Adults and Patients with Parkinson's Disease.

Parkinson's disease (PD) presents several motor signs, including tremor and bradykinesia. However, these signs can also be found in other motor disorders and in neurologically healthy older adults. The incidence of bradykinesia in PD is relatively high in all stages of the disorder, even when compared to tremor. Thus, this research proposes an objective assessment of bradykinesia in patients with PD (G PD: 15 older adults with Parkinson's disease, 65.3 ± 9.1 years) and older adults (G HV: 12 healthy older adults, 60.1 ± 6.1 years). The severity of bradykinesia in the participants of G PD was assessed using the Unified Parkinson's Disease Rating Scale. Movement and muscular activity were detected by means of inertial (accelerometer, gyroscope, magnetometer) and electromyographic sensors while the participants performed wrist extension against gravity with the forearm on pronation. Mean and standard error of inertial and electromyographic signal parameters could discriminate PD patients from healthy older adults (p value <0.05). In discriminating patients with PD from healthy older adults, the mean sensitivity and specificity were respectively 86.67 and 83.33%. The discrimination between the groups, based on the objective evaluation of bradykinesia, may contribute to the accurate diagnosis of PD and to the monitoring of therapies to control parkinsonian bradykinesia, and opens the possibility for further comparative studies considering individuals suffering from other motor disorders.

Linear and Nonlinear Gait Features in Older Adults Walking on Inclined Surfaces at Different Speeds.

This study evaluated linear and nonlinear gait features in healthy older adults walking on inclined surfaces at different speeds. Thirty-seven active older adults (experimental group) and fifty young adults (control group) walked on a treadmill at 100% and ±20% of their preferred walking speed for 4 min under horizontal (0%), upward (UP) (+8%), and downward (DOWN) (-8%) conditions. Linear gait variability was assessed using the average standard deviation of trunk acceleration between strides (VAR). Gait stability was assessed using the margin of stability (MoS). Nonlinear gait features were assessed by using the maximum Lyapunov exponent, as a measure of local dynamic stability (LDS), and sample entropy (SEn), as a measure of regularity. VAR increased for all conditions, but the interaction effects between treadmill inclination and age, and speed and age were higher for young adults. DOWN conditions showed the lowest stability in the medial-lateral MoS, but not in LDS. LDS was smaller in UP conditions. However, there were no effects of age for either MoS or LDS. The values of SEn decreased almost linearly from the DOWN to the UP conditions, with significant interaction effects of age for anterior-posterior SEn. The overall results supported the hypothesis that inclined surfaces modulate nonlinear gait features and alter linear gait variability, particularly in UP conditions, but there were no significant effects of age for active older adults.

A simple, reliable method to determine the mean gait speed using heel markers on a treadmill.

Gait speed is an essential parameter of gait analysis. Our study proposed a simple and accurate method to extract a mean gait speed during walking on a treadmill using only kinematic data from markers placed on the heels of the participants' feet. This method provided an attractive, simple method that remains resistant to errors in treadmill calibration. In addition, this method required only two markers, since heel markers are essential to gait analysis, and the proposed method is robust enough to differentiate among various gait speeds (mean error <1%).

Gait stability, variability and complexity on inclined surfaces.

This study evaluated the gait stability, variability, and complexity of healthy young adults on inclined surfaces. A total of 49 individuals walked on a treadmill at their preferred speed for 4min at inclinations of 6%, 8%, and 10% in upward (UP) and downward (DOWN) conditions, and in horizontal (0%) condition. Gait variability was assessed using average standard deviation trunk acceleration between strides (VAR), gait stability was assessed using margin of stability (MoS) and maximum Lyapunov exponent (λs), and gait complexity was assessed using sample entropy (SEn). Trunk variability (VAR) increased in the medial-lateral (ML), anterior-posterior, and vertical directions for all inclined conditions. The SEn values indicated that movement complexity decreased almost linearly from DOWN to UP conditions, reflecting changes in gait pattern with longer and slower steps as inclination increased. The DOWN conditions were associated with the highest variability and lowest stability in the MoS ML, but not in λs. Stability was lower in UP conditions, which exhibited the largest λs values. The overall results support the hypothesis that inclined surfaces decrease gait stability and alter gait variability, particularly in UP conditions.

Effects of general fatigue induced by incremental maximal exercise test on gait stability and variability of healthy young subjects.

The purpose of this study was to determine whether general fatigue induced by incremental maximal exercise test (IMET) affects gait stability and variability in healthy subjects. Twenty-two young healthy male subjects walked in a treadmill at preferred walking speed for 4min prior (PreT) the test, which was followed by three series of 4min of walking with 4min of rest among them. Gait variability was assessed using walk ratio (WR), calculated as step length normalized by step frequency, root mean square (RMSratio) of trunk acceleration, standard deviation of medial-lateral trunk acceleration between strides (VARML), coefficient of variation of step frequency (SFCV), length (SLCV) and width (SWCV). Gait stability was assessed using margin of stability (MoS) and local dynamic stability (λs). VARML, SFCV, SLCV and SWCV increased after the test indicating an increase in gait variability. MoS decreased and λs increased after the test, indicating a decrease in gait stability. All variables showed a trend to return to PreT values, but the 20-min post-test interval appears not to be enough for a complete recovery. The results showed that general fatigue induced by IMET alters negatively the gait, and an interval of at least 20min should be considered for injury prevention in tasks with similar demands.

Recognition of Intensive Valence and Arousal Affective States via Facial Electromyographic Activity in Young and Senior Adults.

BACKGROUND: Research suggests that interaction between humans and digital environments characterizes a form of companionship in addition to technical convenience. To this effect, humans have attempted to design computer systems able to demonstrably empathize with the human affective experience. Facial electromyography (EMG) is one such technique enabling machines to access to human affective states. Numerous studies have investigated the effects of valence emotions on facial EMG activity captured over the corrugator supercilii (frowning muscle) and zygomaticus major (smiling muscle). The arousal emotion, specifically, has not received much research attention, however. In the present study, we sought to identify intensive valence and arousal affective states via facial EMG activity. METHODS: Ten blocks of affective pictures were separated into five categories: neutral valence/low arousal (0VLA), positive valence/high arousal (PVHA), negative valence/high arousal (NVHA), positive valence/low arousal (PVLA), and negative valence/low arousal (NVLA), and the ability of each to elicit corresponding valence and arousal affective states was investigated at length. One hundred and thirteen participants were subjected to these stimuli and provided facial EMG. A set of 16 features based on the amplitude, frequency, predictability, and variability of signals was defined and classified using a support vector machine (SVM). RESULTS: We observed highly accurate classification rates based on the combined corrugator and zygomaticus EMG, ranging from 75.69% to 100.00% for the baseline and five affective states (0VLA, PVHA, PVLA, NVHA, and NVLA) in all individuals. There were significant differences in classification rate accuracy between senior and young adults, but there was no significant difference between female and male participants. CONCLUSION: Our research provides robust evidences for recognition of intensive valence and arousal affective states in young and senior adults. These findings contribute to the successful future application of facial EMG for identifying user affective states in human machine interaction (HMI) or companion robotic systems (CRS).

Feature visualization and classification for the discrimination between individuals with Parkinson's disease under levodopa and DBS treatments.

BACKGROUND: Over the years, a number of distinct treatments have been adopted for the management of the motor symptoms of Parkinson's disease (PD), including pharmacologic therapies and deep brain stimulation (DBS). Efficacy is most often evaluated by subjective assessments, which are prone to error and dependent on the experience of the examiner. Our goal was to identify an objective means of assessing response to therapy. METHODS: In this study, we employed objective analyses in order to visualize and identify differences between three groups: healthy control (N = 10), subjects with PD treated with DBS (N = 12), and subjects with PD treated with levodopa (N = 16). Subjects were assessed during execution of three dynamic tasks (finger taps, finger to nose, supination and pronation) and a static task (extended arm with no active movement). Measurements were acquired with two pairs of inertial and electromyographic sensors. Feature extraction was applied to estimate the relevant information from the data after which the high-dimensional feature space was reduced to a two-dimensional space using the nonlinear Sammon's map. Non-parametric analysis of variance was employed for the verification of relevant statistical differences among the groups (p < 0.05). In addition, K-fold cross-validation for discriminant analysis based on Gaussian Finite Mixture Modeling was employed for data classification. RESULTS: The results showed visual and statistical differences for all groups and conditions (i.e., static and dynamic tasks). The employed methods were successful for the discrimination of the groups. Classification accuracy was 81 ± 6% (mean ± standard deviation) and 71 ± 8%, for training and test groups respectively. CONCLUSIONS: This research showed the discrimination between healthy and diseased groups conditions. The methods were also able to discriminate individuals with PD treated with DBS and levodopa. These methods enable objective characterization and visualization of features extracted from inertial and electromyographic sensors for different groups.

Estimated features from surface EMG of the lower limb correlate with the subjective sensation of pain

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.

Automatic pain quantification using autonomic parameters

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).

Automatic pain quantification using autonomic parameters

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).(AU)

Estimated features from surface EMG of the lower limb correlate with the subjective sensation of pain

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.(AU)