A randomized controlled trial investigating the impact of a single flash cupping session on patients with chronic lower back pain using multichannel surface electromyographic assessment.

BACKGROUND: Chronic lower back pain (CLBP) is one of the most common disorders worldwide. Flash cupping has the ability to relieve CLBP; nevertheless, its impact on CLBP and the likely mechanism of action have not been studied. OBJECTIVE: The goal of this study was to assess the impact of a single, brief cupping session on CLBP and low back muscle activity using multichannel surface electromyography (sEMG). METHODS: In this randomized controlled trial, 24 patients with CLBP were enrolled and randomly assigned to the control group (treated by acupuncture) and cupping group (treated by acupuncture and flash cupping). Acupuncture was applied on the shen shu (BL23), dachang shu (BL25), and wei zhong (BL40) acupoints in both the groups. A brief cupping treatment was applied to the shen shu (BL23), qihai shu (BL24), dachang shu (BL25), guanyuan shu (BL26), and xiaochang shu (BL27) acupoints on both sides of the lower back in the cupping group. The numeric rating scale (NRS) was used to assess therapy efficacy for lower back pain (LBP) before and after treatment. Surface EMG data collected during symmetrical trunk flexion-extension movements were utilized to measure lower back muscle activity and the effectiveness of LBP therapy. RESULTS: There was no statistically significant difference (P= 0.63) in pain intensity between the two groups before and after treatment. There was a statistically significant difference (P= 0.04) between the control group and the cupping group in the sEMG topographic map parameter CoGx-To-Midline. CONCLUSION: This study established a connection between the action mechanism of flash cupping and enhanced horizontal synchronization of lower back muscular activity.

Detection of volatile organic compounds in adulterated tea using Fourier transform infrared spectroscopy and Proton-transfer-reaction mass spectrometry.

Aroma is a key factor used to evaluate tea quality. Illegal traders usually add essence to expired or substandard tea to improve its aroma so as to gain more profit. Traditional physical and chemical testing methods are time-consuming and costly. Furthermore, rapid detection techniques, such as near-infrared spectroscopy and machine vision, can only be used to detect adulterated powdered solid essences in tea. In this study, proton-transfer reaction mass spectrometry (PTR-MS) and Fourier-transform infrared spectroscopy (FTIR) were employed to detect volatile organic compounds (VOCs) in samples, and rapid detection of different tea adulterated liquid essence was achieved. The prediction accuracies of PTR-MS and FTIR reached over 0.941 and 0.957, respectively, and the minimum detection limits were lower than the actual used values in both. In this study, the different application scenarios of the two technologies are discussed based on their performance characteristics.

A Transformer-Based Approach Combining Deep Learning Network and Spatial-Temporal Information for Raw EEG Classification.

The attention mechanism of the Transformer has the advantage of extracting feature correlation in the long-sequence data and visualizing the model. As time-series data, the spatial and temporal dependencies of the EEG signals between the time points and the different channels contain important information for accurate classification. So far, Transformer-based approaches have not been widely explored in motor-imagery EEG classification and visualization, especially lacking general models based on cross-individual validation. Taking advantage of the Transformer model and the spatial-temporal characteristics of the EEG signals, we designed Transformer-based models for classifications of motor imagery EEG based on the PhysioNet dataset. With 3s EEG data, our models obtained the best classification accuracy of 83.31%, 74.44%, and 64.22% on two-, three-, and four-class motor-imagery tasks in cross-individual validation, which outperformed other state-of-the-art models by 0.88%, 2.11%, and 1.06%. The inclusion of the positional embedding modules in the Transformer could improve the EEG classification performance. Furthermore, the visualization results of attention weights provided insights into the working mechanism of the Transformer-based networks during motor imagery tasks. The topography of the attention weights revealed a pattern of event-related desynchronization (ERD) which was consistent with the results from the spectral analysis of Mu and beta rhythm over the sensorimotor areas. Together, our deep learning methods not only provide novel and powerful tools for classifying and understanding EEG data but also have broad applications for brain-computer interface (BCI) systems.

Identifying oscillations under multi-site sensory stimulation for high-level peripheral nerve injured patients: a pilot study.

Objective.For high-level peripheral nerve injuryed (PNI) patients with severe sensory dysfunction of upper extremities, identifying the multi-site tactile stimulation is of great importance to provide neurorehabilitation with sensory feedback. In this pilot study, we showed the feasibility of identifying multi-site and multi-intensity tactile stimulation in terms of electroencephalography (EEG).Approach.Three high-level PNI patients and eight non-PNI participants were recruited in this study. Four different sites over the upper arm, forearm, thumb finger and little finger were randomly stimulated at two intensities (both sensory-level) based on the transcutaneous electrical nerve stimulation. Meanwhile, 64-channel EEG signals were recorded during the passive tactile sense stimulation on each side.Main results.The spatial-spectral distribution of brain oscillations underlying multi-site sensory stimulation showed dominant power attenuation over the somatosensory and prefrontal cortices in both alpha-band (8-12 Hz) and beta-band (13-30 Hz). But there was no significant difference among different stimulation sites in terms of the averaged power spectral density over the region of interest. By further identifying different stimulation sites using temporal-spectral features, we found the classification accuracies were all above 89% for the affected arm of PNI patients, comparable to that from their intact side and that from the non-PNI group. When the stimulation site-intensity combinations were treated as eight separate classes, the classification accuracies were ranging from 88.89% to 99.30% for the affected side of PNI subjects, similar to that from their non-affected side and that from the non-PNI group. Other performance metrics, including specificity, precision, and F1-score, also showed a sound identification performance for both PNI patients and non-PNI subjects.Significance.These results suggest that reliable brain oscillations could be evoked and identified well, even though induced tactile sense could not be discerned by the PNI patients. This study have implication for facilitating bidirectional neurorehabilitation systems with sensory feedback.

A Robust Extraction Approach of Auditory Brainstem Response Using Adaptive Kalman Filtering Method.

OBJECTIVE: The Auditory brainstem response (ABR) can provide valuable information on the function of the auditory pathway. However, the ABR signal has a very small amplitude, and it is easily submerged in different background noises with large amplitude. Conventional ABR extraction methods such as time-domain averaging (TDA) and Kalman filter (KF) were greatly affected by noise intensity, and the result relies on the empirical settings of parameters. ABR extraction method that can automatically adjust parameters to adapt different background noises was needed. METHODS: An adaptive Kalman filtering (AKF) based ABR signal extraction method was proposed, in which two recursive rules were introduced to constantly update the parameters according to the real-time noise properties. It was used for ABR extraction from recordings in noises with different orders of larger magnitude. RESULTS: The AKF method demonstrated the best performance in obtaining reliable ABR waveform morphologies in the presence of large EMG noises compared with traditional methods of TDA or KF. It could extract satisfactory ABR signal with fewer trials of acoustic stimulus repetition, even from noise 10000 times larger than ABR signal. The AKF results also showed smaller absolute errors and higher correlation coefficients with the target ABR signal when different types (gum chewing, mouth opening and milk drinking) or levels of noises were introduced. CONCLUSION: The proposed AKF method is a great candidate to increase the robustness of current ABR measurements. SIGNIFICANCE: It could provide reduced testing time and relaxed recording conditions for ABR and other evoked potentials extraction.

The Effects of Different Reference Methods on Decision-Making Implications of Auditory Brainstem Response.

Hearing loss is a common disease affecting public health all around the world. In clinic, auditory brainstem response (ABR) has been widely used for the detection of hearing loss based on its convenience and accuracy. The different reference methods directly influence the quality of the ABR waveform which in turn affects the ABR-based diagnosis. Therefore, in this study, a reference electrode standardization technique (REST) was adopted to systematically investigate and evaluate the effect of different reference methods on the quality of ABR waveform in comparison with the conventional average reference (AR) and mean mastoid (MM) methods. In this study, ABR signals induced by click stimulus were acquired via an EEG electrode cap arrays, and those located on the six channels along the midline were compared systemically. The results showed that, when considering the different channels, the ABR in the Cz channel showed the best morphology. Then, the ABR waveforms acquired via the REST method possessed better morphologies with large amplitude (0.06 ± 0.02 µV for wave I, 0.07 ± 0.02 µV for wave III, and 0.21 ± 0.04 µV for wave V) when compared with the traditional method. Summarily, we found that the REST and MM methods improved the quality of ABR on both amplitude and morphology under different stimulation rates and levels without changing the latencies of ABR when compared with the conventional AR method, suggesting that the REST and MM methods have the potential to help physicians with high accurate ABR-based clinical diagnosis. Moreover, this study might also provide a theoretic basis of reference methods on the acquisition of electroencephalogram over public health issues.

Robustness and accuracy evaluation of moisture prediction model for black tea withering process using hyperspectral imaging.

The rapid and non-destructive detection of moisture in withering leaves is an unsolved problem because the leaves are stacked together and have random orientation. To address this issue, this study aimed to establish more robust and accurate models. The performance of front side, back side and multi-region models were compared, and the front side model showed the worst transferability. Therefore, five effective wavelength (EW) selection algorithms were combined with a successive projection algorithm (SPA) to select EWs. It was found that the shuffled frog leaping algorithm (SFLA) combined with SPA was the best method for the front side model for moisture analyses. Based on the selected EWs, the extreme learning machine (ELM) became the model with the best self-verification result. Subsequently, moisture distribution maps of withering leaves were successfully generated. Considering the processing demand of withering leaves, local region models developed based on partial least squares and the SFLA-SPA method were applied to predict the moisture of withering leaves in the local and stacked region. The results showed that the RPD, Rcv and Rp values were above 1.6, 0.870 and 0.897, respectively. These results provide a useful reference for the non-destructive detection of moisture in withering leaves.

Effect of Electroacupuncture on Shoulder Subluxation in Poststroke Patients with Hemiplegic Shoulder Pain: A Sham-Controlled Study Using Multidimensional Musculoskeletal Ultrasound Assessment.

OBJECTIVE: This study aimed to use multidimensional musculoskeletal ultrasound imaging technique to investigate the effect of electroacupuncture (EA) on shoulder subluxation in poststroke patients with hemiplegic shoulder pain. METHODS: In this prospective single-blind, randomized, sham-controlled study, thirty-four patients with shoulder subluxation and hemiplegic shoulder pain were recruited and randomly assigned into the EA group or the sham EA (SEA) group. In the EA group, EA was applied to the Jian yu (LI15), Bi nao (LI14), Jian zhen (SI9), and Jian liao (TE14) acupoints. In the SEA group, the EA was applied 15 mm away from the Lou gu (SP7), Di ji (SP8), Jiao xin (KI8), and Zhu bin (KI9) acupoints. Both groups underwent treatment 30 minutes/day, five days a week, for two weeks using dense waves with a frequency of 2/100 Hz. A Visual Analogue Scale (VAS) was used to evaluate the effectiveness of treatment in reducing shoulder pain. Musculoskeletal ultrasound was used to evaluate the changes of measures of shoulder subluxation in multidimensions (i.e., the acromiohumeral distance, AHD; acromion-greater tuberosity, AGT; and acromion-lesser tuberosity, ALT). Both the within- and between-groups treatment effects were assessed. RESULTS: The pain intensity measured by VAS and shoulder subluxation measured by musculoskeletal ultrasound (i.e., AHD, AGT, and ALT) showed significant (p < 0.05) within-group difference in both groups. The between-group difference appeared in the pain intensity (p < 0.05), while it disappeared in the three measures of shoulder subluxation (p > 0.05). CONCLUSIONS: Using VAS for measuring pain intensity and multidimensional musculoskeletal ultrasound imaging technique for measuring shoulder subluxation, this study finds that the hemiplegic shoulder pain can be improved significantly by the EA while the shoulder subluxation cannot be. Our findings further reveal the analgesic mechanism of EA on hemiplegic shoulder pain following stroke.

Electroacupuncture and Transcutaneous Electrical Nerve Stimulation Induced Sensations in Bell's Palsy Patients: A Quantitative Current Intensity Analysis.

BACKGROUND: The intensity of electrical acupoint stimulation such as electroacupuncture (EA) and transcutaneous electrical nerve stimulation (TENS) is regulated by the observation of skin shivering or the participant's comfort response. However, the specific intensity and spatial scope following EA or TENS stimulation are unclear. OBJECTIVE: This study aimed to test the stimulatory current intensities of lower and upper sensation thresholds in TENS- and EA-based treatment of Bell's palsy patients. Also, the spatial scope of the stimulation at these current intensities was simulated and measured quantitatively. METHODS: A total of 19 Bell's palsy patients were recruited. Six acupoints on the affected side of the face were stimulated by TENS and EA successively at 30-min intervals. During the stimulation, the current intensity was regulated gradually from 0 to 20 mA, and we simultaneously measured the lower (sensory) and upper (tolerability) sensations. After the treatment by TENS and EA, the modified Chinese version of the Massachusetts General Hospital Acupuncture Sensation Scales (C-MMASS) was applied to survey the de-qi sensations during stimulation. Additionally, we analyzed the correlation between current intensities and C-MMASS and comfort scores. Finite element models were established to depict the spatial distribution of electric field gradients at the lower and upper thresholds. RESULTS: The mean sensory and tolerability thresholds of TENS were 3.91-4.37 mA and 12.33-16.35 mA, respectively. The median sensory and tolerability thresholds of EA were 0.2 mA and 2.0-3.2 mA, respectively. We found a significant correlation between total C-MMASS scores and the current intensities at the tolerability threshold of TENS. The finite element model showed that the activated depths of TENS and EA at the lower threshold were 3.8 and 7 mm, respectively, whereas those at the upper threshold were both 13.8 mm. The cross-sectional diameter of the activated area during TENS was 2.5-4 times larger than that during EA. CONCLUSION: This pilot study provided a method for exploring the current intensity at which the de-qi sensations can be elicited by TENS or EA. The finite element analysis potentially revealed the spatial scope of the electrical stimulation at a specific current intensity.

Natural products for treatment of Plasmodium falciparum malaria: An integrated computational approach.

Malaria is a life-threatening infectious disease with an estimated 229 million cases in the year 2019 worldwide. Plasmodium falciparum 1-deoxy-d-xylulose-5-phosphate reductoisomerase (PfDXR) is one of the key enzymes in the biosynthetic pathway of isoprenoid, (required for parasite growth and survival) and considered as an attractive target for designing anti-malarial drugs. Fosmidomycin is an effective DXR inhibitor and has been proven effective and safe against P. falciparum in clinical trials. However, due to low bioavailability and inappropriate drug attributes, it is not a preferred option. The present study was performed to identify PfDXR inhibitors with improved pharmacology/safety. For this purpose, an integrated computational framework, comprising of pharmacophore modeling, virtual screening, molecular docking, molecular dynamics (MD) simulation and MM/PBSA, was used. The binding free energy analysis was performed using a focused library of phytochemicals established from medicinal plants. The study identified four bioactive compounds namely, Myricetin 3-rhamnoside, 7-O-Galloyltricetiflavan, (25S)-5-beta-spirostan-3-beta-ol 3-O-beta-d-glucopyranosyl-(1->2)-beta-d-glucopyranoside, and Oleanolic acid 28-O-beta-d-glucopyranoside as potential inhibitors of PfDXR. The selection of these four compounds was based on pharmacophore mapping, docking score, binding stability, molecular interactions with the residues of PfDXR active site, binding stability and free energy estimation. In conclusion, medicinal plant-based scaffolds were predicted with enhanced efficacy and adequate physiochemical/pharmacokinetic profile that might be helpful in controlling malaria.

Promising terpenes as SARS-CoV-2 spike receptor-binding domain (RBD) attachment inhibitors to the human ACE2 receptor: Integrated computational approach.

The spike protein receptor binding domain (S-RBD) is a necessary corona-viral protein for binding and entry of coronaviruses (COVs) into the host cells. Hence, it has emerged as an attractive antiviral drug target. Therefore, present study was aimed to target severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) S-RBD with novel bioactive compounds to retrieve potential candidates that could serve as anti-coronavirus disease 2019 (COVID-19) drugs. In this paper, computational approaches were employed, especially the structure-based virtual screening followed by molecular dynamics (MD) simulation as well as binding energy analysis for the computational identification of specific terpenes from the medicinal plants, which can block SARS-CoV-2 S-RBD binding to Human angiotensin-converting enzyme 2 (H-ACE2) and can act as potent anti-COVID-19 drugs after further advancements. The screening of focused terpenes inhibitors database composed of ~1000 compounds with reported therapeutic potential resulted in the identification of three candidate compounds, NPACT01552, NPACT01557 and NPACT00631. These three compounds established conserved interactions, which were further explored through all-atom MD simulations, free energy calculations, and a residual energy contribution estimated by MM-PB(GB)SA method. All these compounds showed stable conformation and interacted well with the hot-spot residues of SARS-CoV-2 S-RBD. Conclusively, the reported SARS-CoV-2 S-RBD specific terpenes could serve as seeds for developing potent anti-COVID-19 drugs. Importantly, the experimentally tested glycyrrhizin (NPACT00631) against SARS-CoV could be used further in the fast-track drug development process to help curb COVID-19.

Bio-Inspired Algorithms for Optimal Feature Selection in Motor Imagery-Based Brain-Computer Interface.

Recently, there is an increasing recognition that sensory feedback is critical for proper motor control. With the help of BCI, people with motor disabilities can communicate with their environments or control things around them by using signals extracted directly from the brain. The widely used non-invasive EEG based BCI system require that the brain signals are first preprocessed, and then translated into significant features that could be converted into commands for external control. To determine the appropriate information from the acquired brain signals is a major challenge for a reliable classification accuracy due to high data dimensions. The feature selection approach is a feasible technique to solving this problem, however, an effective selection method for determining the best set of features that would yield a significant classification performance has not yet been established for motor imagery (MI) based BCI. This paper explored the effectiveness of bio-inspired algorithms (BIA) such as Ant Colony Optimization (ACO), Genetic Algorithm (GA), Cuckoo Search Algorithm (CSA), and Modified Particle Swarm Optimization (M-PSO) on EEG and ECoG data. The performance of SVM classifier showed that M-PSO is highly efficacious with the least selected feature (SF), and converges at an acceptable speed in low iterations.

Identification of unhealthy Panax notoginseng from different geographical origins by means of multi-label classification.

Root-knot nematode is a common plant-parasitic pest with a highly destructive that infects more than 2000 plant species. Panax notoginseng (P. notoginseng) is one of the most susceptible traditional medicine. More importantly, it is difficult to distinguish the powders of P. notoginseng infected with root-knot nematode from those of healthy P. notoginseng due to the color and shape are same after being ground into powder. In this paper, Attenuated Total Reflection-Fourier Transform Infrared (ATR-FTIR) was used to identify P. notoginseng samples. Multiplicative scatter correction (MSC) was applied to preprocess the spectral data. Competitive adaptive reweighted sampling (CARS) and successive projection algorithm (SPA) were employed to select feature variables. Density-based spatial clustering of application with noise (DBSCAN) was adopted to discover groups within the data. Also, we found that the geographical origin is a pivotal factor to consider when identifying unhealthy P. notoginseng. Therefore, we introduced a novel multi-label classification (MLC) method to identify healthy and unhealthy P. notoginseng powders from three different geographical origins. In addition, binary relevance method (BR), classifier chain (CC), ensembles of classifier chains (ECC), and multilayer perceptron classifier (MLPC) were applied to create classification models, ECC exhibits superior performance in particular.

Comparing Auditory Brainstem Responses evoked by Click and Sweep-Tone in Normal-Hearing Adults.

Auditory brainstem response (ABR) is an objective method via which hearing loss could be detected. ABR induced by click, a broadband signal, is generally considered as the gold standard. However, due to the inherent delay of the cochlear traveling wave, click cannot excite the entire cochlear basement membrane at the same time, leading to the attenuation of the induced ABR waveform. In order to resolve this limitation, a sweep-tone-based stimulus that reconstructs the arrival time of different frequency components with respect to the delay characteristics of cochlear basement membrane was designed and used to induce ABR in this study. Subsequently, we compared the performance of the proposed sweep-tone-induced ABR method and the commonly adopted click induced ABR at different test levels and different stimulus rates. And the obtained results showed that the waveform morphology of sweep-tone-induced ABR was significantly better than that of click induced ABR across different test levels and stimulus rates. Moreover, compared to the click induced ABR at different sweeps, we found that the proposed sweep-tone-induced ABR effectively induced the ABR waveform at a relatively faster rate. Hence, the proposed sweep-tone-induced ABR approach provides a new method to improve the sensitivity of ABR detection in hearing loss.

Rapid discrimination of Notoginseng powder adulteration of different grades using FT-MIR spectroscopy combined with chemometrics.

Panax Notoginseng is a kind of herb material with high medicinal value, which requires adaptive planting environment, and not can be continuously cultivated in the same ground. Those reasons lead to a large number of low-grade Notoginseng appears in the market. The objective of this study is to discriminate adulterant of Notoginseng of different grades by FT-MIR spectroscopy couple with chemometrics. In the experiment, high-grade Notoginseng was adulterated with 14 blend ratios: 0%, 1%, 3%, 5%, 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, and 100% of low-grade Notoginseng. All samples were scanned in the range of 4000-400 cm-1 by FT-MIR spectra instrument in absorption mode. Baseline, standard normal variate (SNV), multiplicative scatter correction (MSC), orthogonal signal correction (OSC), first derivative (D1) with 11-points smoothing and second derivative (D2) with 11-points smoothing were used to preprocess the spectral data, in which Baseline combined with SNV and D1 with 11-points performed best. The spectral data in the range of 1485-405 cm-1 were selected by interval partial least squares (iPLS) for modeling. Then, Support vector machine (SVM) and linear discriminant analysis (LDA) were applied for modeling analysis. The best result was achieved by SVM, as the classification accuracy was 100%, which indicated that FT-MIR spectroscopy combined with chemometrics was an effective approach to identify Notoginseng powder adulteration. It could detect the blend ratio of 5% (w/w) as well as the blend ratio of over 5%.

Towards determining the afferent sites of perception feedback on residual arms of amputees with transcutaneous electrical stimulation.

The coordination and combination of motion and sensation are critical to realize a natural and precise control of prosthetic hands. Transcutaneous electrical stimulation (TES) is one of possible methods to develop an intuitive perception feedback for limb amputees. However, the perception afferent sites would be a critical issue that is still unexplored in depth. This paper reports a preliminary study on using somatosensory evoked potentials (SEP) to determine the proper afferent sites of perceptions on residual arms of transradial amputees. In this study, two transradial amputees with phantom finger perception (PFP) were recruited and SEP for the stimulation of median nerves and ulnar nerves were recorded and analyzed. PFP distribution maps on subjects' stumps were obtained by mechanical stimulations performed manually. Electrical stimulation was then applied to some selected sites on the stumps of their residual arms with surface electrodes to evoke SEP. In the experiments, SEP were successfully recorded, which means that the proposed method might be a suitable approach for localizing the afferent sites of perceptions, and could provide technique support for possible intuitive neural feedback for limb amputees in future work.

Noninvasive localization of the site of origin of paced cardiac activation in human by means of a 3-D heart model.

A recently developed heart-model-based localization approach is experimentally evaluated in noninvasively localizing the site of origin of cardiac activation in a patient with a pacemaker. The heart-torso model of the patient was constructed from the contrast ultrafast computed tomography images. The site of initial paced activation in the patient was quantitatively localized and compared with the tip position of the pacemaker lead. The localization error of the inverse estimation was found to be 5.2 mm with respect to the true lead tip position. The promising result of this pilot experimental study suggests the feasibility of localizing the site of origin of cardiac activation in an experimental setting. The heart-model-based localization approach may become an alternative tool in localizing the site of origin of cardiac activation.

Body surface Laplacian electrocardiogram of ventricular depolarization in normal human subjects.

INTRODUCTION: The body surface Laplacian electrocardiogram (ECG) mapping provides a noninvasive means for spatiotemporal mapping of cardiac electrical events. The aim of the present study was to explore the relationship between the Laplacian ECG and the underlying cardiac activities during ventricular depolarization in healthy human subjects. METHODS AND RESULTS: A 95-channel body surface potential ECG was recorded over the anterolateral chest from 11 healthy male subjects. The surface Laplacian (SL) ECG was estimated from the recorded potentials during QRS complex by means of a novel spline SL estimator, as well as by the conventional 5-point SL estimator for comparison purpose. A simulation study was also conducted using a realistic geometry heart-torso model in an attempt to qualitatively interpret the experimental results. For all subjects, more spatial details were observed in the SL ECG maps compared with the potential ECG maps, with spline SL more robust against noise than the 5-point SL. In total, three positive activities (denoted as P1, P2, P3) and four negative activities (denoted as N1, N2, N3, N4) in the spline SL ECG maps were observed during ventricular depolarization. Initial localized P1 and N1 activities were observed in 11 and 8 subjects, respectively. Then, the initial P1 was divided into three positive activities (P1, P2, P3) in 9 subjects. After the appearance of multiple positive activities, three negative activities (N2, N3, N4) appeared in 11, 8, and 9 subjects, respectively. Similar findings were obtained in the computer simulation study. CONCLUSION: The present study demonstrates that the SL ECG provides more spatial details than the potential ECG, and multiple simultaneously active ventricular activities could be revealed in the SL ECG maps. The results suggest that the SL ECG may provide an alternative for noninvasive mapping of cardiac electrical activity.