Fast Rhythms Research Articles

Ecological and Construct Validity of a New Technical Level Cuban Dance Field Test.

The study aimed to explore the sensitivity and specificity of a new methodological approach related to the musical rhythm for discriminating a competitive Cuban dancer’s (CDCs) level. Thirty CDCs (Age 23.87 ± 1.76 years, body mass 60.33 ± 9.45 kg, stature 1.68 ± 0.07 m) were divided into three groups: beginner (BEG, n = 10), intermediate (INT, n = 10), and advanced (ADV, n = 10) according to their training experience/level. Each dancer was assessed while dancing at three different musical rhythms: fast (118 BPM), medium (96 BPM), and slow (82 BPM). The assessed variables were average heart rate (HRM), peak (HRP), and dancing time (DCT). The ADV group succeeded at all three musical combinations (317, 302, 309 s for 82, 96, 118 BPM). The INT group correctly performed only the first two combinations (304, 304 s for 82, 96 BPM), while a significant time difference was shown at the fast musical rhythm (198 ± 6.64 s) compared to the medium (p < 0.001) and slow rhythms (p < 0.001) respectively. As the speed of the musical rhythms increased, the BEG group was not able to follow the rhythm: their results were 300 ± 1.25 s for the slow musical rhythm, 94.90 ± 12.80 s for the medium musical rhythm and 34.10 ± 5.17 s for the fast musical rhythm (p < 0.001). The HRM and HRP grew along with the increase in musical rhythm for all groups (p < 0.001). The ROC analysis showed a high sensitivity and specificity in discriminating the groups for each rhythm’s condition. The BEG and INT groups showed an AUC = 0.864 (95% CI = 0.864–0.954); INT and ADV showed an AUC = 0.864 (95% CI = 0.864–0.952); BEG and ADV showed an AUC = 0.998 (95% CI = 0.993–1.000). The results of this study provided evidence to support the construct and ecological validity of the time of the musical rhythms related to competitive CDCs. Furthermore, the differences in the performances according to various musical rhythms, fast (118 BPM), medium (96 BPM), and slow (82 BPM), succeeded in discriminating a dancer’s level. Coaches and strength and conditioning professionals should include the Cuban Dance Field Test (CDFT) in their test battery when dealing with talent detection, selection, and development.

Design of a Visual Needle Searching Device in Operating Room

Objective: a visual needle searching device in operating room is designed to quickly find surgical suture needles. Method: on the basis of referring to the current needle searching method in the operating room, the magnetic strength adjustment, data recording and export, and harmless treatment of the adsorbed suture needle are added. What is more, the functions of adjusting the total length of the telescopic connecting rod as required, rotating the telescopic connecting rod at any angle, alarm prompt after finding the sewing needle and LED lighting. Result : a visual needle searching device in operating room was designed, which could solve the problems that the magnetic strength of the permanent magnet of the existing needle finder was difficult to control, the electromagnet could not directly judge whether the electric energy of the battery met the use requirements, and could not record the use times, frequency and needle searching time. Conclusion: the visual needle searching device designed in this paper can provide a more time-saving, labor-saving, easier, more convenient and safer needle searching device for suture needle searching in the operating room, and can meet the requirements of fast work rhythm and high efficiency in the operating room.

Evaluating the Territorial Impact of Built-Up Area Expansion in the Surroundings of Bucharest (Romania) through a Multilevel Approach Based on Landsat Satellite Imagery

Assessing the relentless expansion of built-up areas is one of the most important tasks for achieving sustainable planning and supporting decision-making on the regional and local level. In this context, techniques based on remote sensing can play a crucial role in monitoring the fast rhythm of urban growth, allowing the regular appraisal of territorial dynamics. The main aim of the study is to evaluate, in a multi-scalar perspective, the built-up area expansion and the spatio–temporal changes in Ilfov County, which overlaps the surroundings of Bucharest, capital of Romania. Our research focuses on processing multi-date Landsat satellite imagery from three selected time references (2000, 2008, 2018) through the supervised classification process. Further on, the types of built-up area dynamics are explored using LDTtool, a landscape metrics instrument. The results reveal massive territorial restructuring in the 18 years, as the new built-up developments occupy a larger area than the settlements’ surface in 2000. The rhythm of the transformations also changed over time, denoting a significant acceleration after 2008, when 75% of the new development occurred. At the regional level, the spatial pattern has become more and more complex, in a patchwork of spatial arrangements characterized by the proliferation of low density areas interspersed with clusters of high density developments and undeveloped land. At the local level, a comparative assessment of the administrative territorial units’ pathway was conducted based on the annual growth of built-up areas, highlighting the most attractive places and the main territorial directions of development. In terms of the specific dynamics of built-up areas, the main change patterns are “F—NP increment by gain”, followed by “G—Aggregation by gain”, both comprising around 80% of the total number of cells. The first type was prevalent in the first period (2000–2008), while the second is identified only after 2008, when it became the most represented, followed in the hierarchy by the previously dominant category. The spatial pattern differentiations were further explored in three complementary case studies investigated in correlation with socioeconomic data, revealing a heterogeneous landscape.

Early or Delayed Onset of Food Intake in Time-Restricted Eating: Associations with Markers of Obesity in a Secondary Analysis of Two Pilot Studies

Time-restricted eating (TRE) has rapidly gained interest in the public and the scientific community. One presumed mechanism of action is the adaptation of the eating–fasting rhythm to the evolutionary circadian rhythm of the metabolism. Study results regarding the suggestion that earlier beginning of food intake leads to better outcomes are heterogeneous. We conducted a secondary analysis of pooled data from two pilot studies on TRE to examine an association between the timing of onset of food intake with obesity-related outcomes. Participants (n = 99, 83 females aged 49.9 ± 10.8 years) were asked to restrict their daily eating to 8–9 h for three months. Tertiles of the onset of food intake were assessed for changes in anthropometry, blood lipid levels, and health-related quality of life. We detected no significant differences in outcomes between early (before 9:47), medium (9:47–10:50), and late onset (after 10:50) of food intake. However, the duration of the eating period was longest in the group with the earliest (8.6 ± 1.0 h) and shortest in the group with the latest onset (7.5 ± 0.8 h). Subsequently, fasting duration was longest in the last group (16.5 h). This may have compromised the results. More research is needed in this area to address this question.

Reduced Effective Connectivity in the Motor Cortex in Parkinson's Disease.

Fast rhythms excess is a hallmark of Parkinson’s Disease (PD). To implement innovative, non-pharmacological, neurostimulation interventions to restore cortical-cortical interactions, we need to understand the neurophysiological mechanisms underlying these phenomena. Here, we investigated effective connectivity on source-level resting-state electroencephalography (EEG) signals in 15 PD participants and 10 healthy controls. First, we fitted multivariate auto-regressive models to the EEG source waveforms. Second, we estimated causal connections using Granger Causality, which provide information on connections’ strength and directionality. Lastly, we sought significant differences connectivity patterns between the two populations characterizing the network graph features—i.e., global efficiency and node strength. Causal brain networks in PD show overall poorer and weaker connections compared to controls quantified as a reduction of global efficiency. Motor areas appear almost isolated, with a strongly impoverished information flow particularly from parietal and occipital cortices. This striking isolation of motor areas may reflect an impaired sensory-motor integration in PD. The identification of defective nodes/edges in PD network may be a biomarker of disease and a potential target for future interventional trials.

The influence of auditory rhythms on the speed of inferred motion.

The present research explored the influence of isochronous auditory rhythms on the timing of movement-related prediction in two experiments. In both experiments, participants observed a moving disc that was visible for a predetermined period before disappearing behind a small, medium, or large occluded area for the remainder of its movement. In Experiment 1, the disc was visible for 1 s. During this period, participants were exposed to either a fast or slow auditory rhythm, or they heard nothing. They were instructed to press a key to indicate when they believed the moving disc had reached a specified location on the other side of the occluded area. The procedure measured the (signed) error in participants' estimate of the time it would take for a moving object to contact a stationary one. The principal results of Experiment 1 were main effects of the rate of the auditory rhythm and of the size of the occlusion on participants' judgments. In Experiment 2, the period of visibility was varied with size of the occlusion area to keep the total movement time constant for all three levels of occlusion. The results replicated the main effect of rhythm found in Experiment 1 and showed a small, significant interaction, but indicated no main effect of occlusion size. Overall, the results indicate that exposure to fast isochronous auditory rhythms during an interval of inferred motion can influence the imagined rate of such motion and suggest a possible role of an internal rhythmicity in the maintenance of temporally accurate dynamic mental representations.

Cortical correlates in upright dynamic and static balance in the elderly

Falls are the second most frequent cause of injury in the elderly. Physiological processes associated with aging affect the elderly’s ability to respond to unexpected balance perturbations, leading to increased fall risk. Every year, approximately 30% of adults, 65 years and older, experiences at least one fall. Investigating the neurophysiological mechanisms underlying the control of static and dynamic balance in the elderly is an emerging research area. The study aimed to identify cortical and muscular correlates during static and dynamic balance tests in a cohort of young and old healthy adults. We recorded cortical and muscular activity in nine elderly and eight younger healthy participants during an upright stance task in static and dynamic (core board) conditions. To simulate real-life dual-task postural control conditions, the second set of experiments incorporated an oddball visual task. We observed higher electroencephalographic (EEG) delta rhythm over the anterior cortex in the elderly and more diffused fast rhythms (i.e., alpha, beta, gamma) in younger participants during the static balance tests. When adding a visual oddball, the elderly displayed an increase in theta activation over the sensorimotor and occipital cortices. During the dynamic balance tests, the elderly showed the recruitment of sensorimotor areas and increased muscle activity level, suggesting a preferential motor strategy for postural control. This strategy was even more prominent during the oddball task. Younger participants showed reduced cortical and muscular activity compared to the elderly, with the noteworthy difference of a preferential activation of occipital areas that increased during the oddball task. These results support the hypothesis that different strategies are used by the elderly compared to younger adults during postural tasks, particularly when postural and cognitive tasks are combined. The knowledge gained in this study could inform the development of age-specific rehabilitative and assistive interventions.

A novel approach to the study of spatio-temporal brain dynamics using change-based complexity

Brain complexity and neural oscillations are of vital significance for understanding brain dynamics. Although widely used in the quantification of complex behavior of the brain, standard complexity measures are hampered by some theoretical and implementation issues which limit their applicability to the study of nonlinear brain signals. Further, they have been used for spatial analysis but are insensitive to the temporal structure of data and not applicable to short EEG segments. We demonstrated the ability of a change-based complexity measure (Aksentijevic-Gibson complexity) to analyze neural activity in both spatial and temporal domains. We examined EEG recordings from a group of adolescents with schizophrenia and an age-matched group of healthy controls. AG revealed that the spatial complexity was significantly lower in the patient group across all electrodes with the lowest complexity at the frontal area of the brain. By focusing on outer frontal regions and temporal data averaged over schizophrenia adolescents, we observed periodic drops in complexity and low-delta oscillations at the left electrode F7 and numerous irregularly placed drops at the right side (F8). Periodicity was caused by zero complexity troughs in several individuals associated with large voltage declensions and connected with hypofrontality supporting left frontal pathology. Both averaged spatial and temporal complexities of healthy and schizophrenia adolescents were significantly different from the complexities of random sequences confirming that neural activity is more regular than a true random process. As a final step, we performed the analysis of short EEG segments for the two subjects (one control, one patient) in order to search for differences in neural oscillations. The examination revealed a clear 33 Hz gamma rhythm in a healthy participant and only a fast beta rhythm of 27 Hz in a patient as well as the presence of a full range of rhythms in a healthy EEG and only theta oscillations in that of a patient. The results support the large body of work which associates schizophrenia with lowered complexity, low-frequency rhythms and the scarcity of high-frequency oscillations.

PPGTempStitch: A MATLAB Toolbox for Augmenting Annotated Photoplethsmogram Signals.

An annotated photoplethysmogram (PPG) is required when evaluating PPG algorithms that have been developed to detect the onset and systolic peaks of PPG waveforms. However, few publicly accessible PPG datasets exist in which the onset and systolic peaks of the waveforms are annotated. Therefore, this study developed a MATLAB toolbox that stitches predetermined annotated PPGs in a random manner to generate a long, annotated PPG signal. With this toolbox, any combination of four annotated PPG templates that represent regular, irregular, fast rhythm, and noisy PPG waveforms can be stitched together to generate a long, annotated PPG. Furthermore, this toolbox can simulate real-life PPG signals by introducing different noise levels and PPG waveforms. The toolbox can implement two stitching methods: one based on the systolic peak and the other on the onset. Additionally, cubic spline interpolation is used to smooth the waveform around the stitching point, and a skewness index is used as a signal quality index to select the final signal output based on the stitching method used. The developed toolbox is free and open-source software, and a graphical user interface is provided. The method of synthesizing by stitching introduced in this paper is a data augmentation strategy that can help researchers significantly increase the size and diversity of annotated PPG signals available for training and testing different feature extraction algorithms.

Breathing Rhythm Variations during Wash-In Do Not Influence Exhaled Volatile Organic Compound Profile Analyzed by an Electronic Nose.

E-noses are innovative tools used for exhaled volatile organic compound (VOC) analysis, which have shown their potential in several diseases. Before obtaining a full validation of these instruments in clinical settings, a number of methodological issues still have to be established. We aimed to assess whether variations in breathing rhythm during wash-in with VOC-filtered air before exhaled air collection reflect changes in the exhaled VOC profile when analyzed by an e-nose (Cyranose 320). We enrolled 20 normal subjects and randomly collected their exhaled breath at three different breathing rhythms during wash-in: (a) normal rhythm (respiratory rate (RR) between 12 and 18/min), (b) fast rhythm (RR > 25/min) and (c) slow rhythm (RR < 10/min). Exhaled breath was collected by a previously validated method (Dragonieri et al., J. Bras. Pneumol. 2016) and analyzed by the e-nose. Using principal component analysis (PCA), no significant variations in the exhaled VOC profile were shown among the three breathing rhythms. Subsequent linear discriminant analysis (LDA) confirmed the above findings, with a cross-validated accuracy of 45% (p = ns). We concluded that the exhaled VOC profile, analyzed by an e-nose, is not influenced by variations in breathing rhythm during wash-in.

FDA warns of harms from misuse and abuse of inhalant

The over‐the‐counter (OTC) nasal decongestant propylhexedrine, safe and effective when used as directed, can cause serious harm when misused or abused, the Food and Drug Administration (FDA) warned in April. These harms include heart and mental health problems. Specific complications include fast or abnormal heart rhythm, high blood pressure and paranoia, which can all lead to hospitalization, disability or death, the FDA warned.

Mortalidade associada ao uso da digoxina no tratamento da fibrilação atrial: uma revisão integrativa

A fibrilação atrial (FA) é a arritmia mais prevalente, desencadeadora de um ritmo cardíaco irregular e acelerado. Embora nem sempre seja o fármaco de primeira escolha, a digoxina ainda é bastante usada, apesar de haver uma linha tênue entre seus efeitos terapêuticos, adversos e a mortalidade. Diante disso, o objetivo desse estudo é buscar evidências clínicas sobre a correlação entre o uso da digoxina e a mortalidade em pacientes com FA. Assim, foi realizada uma pesquisa bibliográfica, utilizando os descritores “(Digoxin) AND (Atrial fibrillation) AND (drug therapy)”, nas bases de dados PubMed, Biblioteca Virtual em Saúde (BVS), Scientific Eletronic Library Online (Scielo) e Cochrane. A busca foi realizada durante o mês de fevereiro de 2021. Após a aplicação dos critérios de inclusão definidos, foram selecionados 15 estudos. Após análise, evidenciou-se o número crescente de estudos que relacionam a mortalidade à terapêutica com digoxina em paciente com FA e em associação a comorbidades, como insuficiência cardíaca (IC). Logo, embora não haja um consenso, a mortalidade foi superior nos grupos de portadores de FA, com cardioversor desfibrilador ou não, que utilizaram a digoxina; sendo a mortalidade ainda maior em idosos, em portadores de doenças renais, em pacientes com FA sem IC e na ausência de monitorização terapêutica. Diante das evidências apresentadas nessa revisão, podemos afirmar que o uso de digoxina em pacientes com FA deve ser evitado ou feito com cautela e acompanhamento rigoroso.

Quantifying emotional differences in urban green spaces extracted from photos on social networking sites: A study of 34 parks in three cities in northern China

In rapid urbanization processes, the high density and fast rhythm of the urban living environment lead to mental tension, life pressure, anxiety, and other problems for people, which facilitates negative emotions. Studies have confirmed that an urban green space is a “restorative environment" that can effectively alleviate negative emotions and improve moods. Social media data can be objectively quantified to evaluate people's emotional responses to urban green spaces. Based on the analysis of social media data, this study examines whether there are differences in emotions linked to locations, with the data extracted from microblogs similar to Twitter in three different cities. Seven emotions (happiness, fear, surprise, anger, disgust, neutral, and sadness) were identified using online cognitive services on photos collected from microblog data. Three emotion-based indexes (emotion intensity index, emotion intensity index, emotion evenness index) were used to expand the urban green space pair from the spatial perspective of research on the influence of emotion. The results show that there are significant correlations among age, gender, emotional diversity, area, accessibility, NDVI, and emotion. The results also show that (1) the higher the NDVI of urban green space, the greater the probability and intensity of emotion in green space, and the more happiness emotion people show. (2) there is a significant positive correlation between urban green space area and EEI, and a significant negative correlation between urban green space area and EPI, EII, which is just opposite to the NDVI results. (3) Optimistic and positive emotions are widely expressed in cities, and happiness is expressed most and strongly. The negative emotions such as fear, anger, and trouble are less expressed, and the expressions of emotions in cities are highly similar. With the increase of age, happiness emotion increased, and sadness emotion decreased.These results show that the urban green space planning can be used to intervene in the expression of human emotion based on where a person lives. In the future, the planning and design of urban green spaces based on the reasonable balance and combinations of area, accessibility, and the NDVI can enhance the emotional enthusiasm for these areas. Improving the planning and design of the existing urban parks and green spaces with positive intervention methods can provide a feasible solution to meet the growing population's emotional recovery needs.

Eat, Train, Sleep—Retreat? Hormonal Interactions of Intermittent Fasting, Exercise and Circadian Rhythm

The circadian rhythmicity of endogenous metabolic and hormonal processes is controlled by a complex system of central and peripheral pacemakers, influenced by exogenous factors like light/dark-cycles, nutrition and exercise timing. There is evidence that alterations in this system may be involved in the pathogenesis of metabolic diseases. It has been shown that disruptions to normal diurnal rhythms lead to drastic changes in circadian processes, as often seen in modern society due to excessive exposure to unnatural light sources. Out of that, research has focused on time-restricted feeding and exercise, as both seem to be able to reset disruptions in circadian pacemakers. Based on these results and personal physical goals, optimal time periods for food intake and exercise have been identified. This review shows that appropriate nutrition and exercise timing are powerful tools to support, rather than not disturb, the circadian rhythm and potentially contribute to the prevention of metabolic diseases. Nevertheless, both lifestyle interventions are unable to address the real issue: the misalignment of our biological with our social time.

Bimanual coordination associated with left- and right-hand dominance: testing the limb assignment and limb dominance hypothesis

In an experiment conducted by Kennedy et al. (Exp Brain Res 233:181–195, 2016), dominant right-handed individuals were required to produce a rhythm of isometric forces in a 2:1 or 1:2 bimanual coordination pattern. In the 2:1 pattern, the left limb performed the faster rhythm, while in the 1:2 pattern, the right limb produced the faster pattern. In the 1:2 pattern, interference occurred in the limb which had to produce the slower rhythm of forces. However, in the 2:1 condition, interference occurred in both limbs. The conclusion was that interference was not only influenced by movement frequency, but also influenced by limb dominance. The present experiment was designed to replicate these findings in dynamic bimanual 1:2 and 2:1 tasks where performers had to move one wrist faster than the other, and to determine the influence of limb dominance. Dominant left-handed (N = 10; LQ = − 89.81) and dominant right-handed (N = 14; LQ = 91.25) participants were required to perform a 2:1 and a 1:2 coordination pattern using Lissajous feedback. The harmonicity value was calculated to quantify the interference in the trial-time series. The analysis demonstrated that regardless of limb dominance, harmonicity was always lower in the slower moving limb than in the faster moving limb. The present results indicated that for dominant left- and dominant right-handers the faster moving limb influenced the slower moving limb. This is in accordance with the assumption that movement frequency has a higher impact on limb control in bimanual 2:1 and 1:2 coordination tasks than handedness.

From ECG signals to images: a transformation based approach for deep learning.

Provocative heart disease is related to ventricular arrhythmias (VA). Ventricular tachyarrhythmia is an irregular and fast heart rhythm that emerges from inappropriate electrical impulses in the ventricles of the heart. Different types of arrhythmias are associated with different patterns, which can be identified. An electrocardiogram (ECG) is the major analytical tool used to interpret and record ECG signals. ECG signals are nonlinear and difficult to interpret and analyze. We propose a new deep learning approach for the detection of VA. Initially, the ECG signals are transformed into images that have not been done before. Later, these images are normalized and utilized to train the AlexNet, VGG-16 and Inception-v3 deep learning models. Transfer learning is performed to train a model and extract the deep features from different output layers. After that, the features are fused by a concatenation approach, and the best features are selected using a heuristic entropy calculation approach. Finally, supervised learning classifiers are utilized for final feature classification. The results are evaluated on the MIT-BIH dataset and achieved an accuracy of 97.6% (using Cubic Support Vector Machine as a final stage classifier).

Coupling between fast and slow oscillator circuits in Cancer borealis is temperature-compensated.

Coupled oscillatory circuits are ubiquitous in nervous systems. Given that most biological processes are temperature-sensitive, it is remarkable that the neuronal circuits of poikilothermic animals can maintain coupling across a wide range of temperatures. Within the stomatogastric ganglion (STG) of the crab, Cancer borealis, the fast pyloric rhythm (~1 Hz) and the slow gastric mill rhythm (~0.1 Hz) are precisely coordinated at ~11°C such that there is an integer number of pyloric cycles per gastric mill cycle (integer coupling). Upon increasing temperature from 7°C to 23°C, both oscillators showed similar temperature-dependent increases in cycle frequency, and integer coupling between the circuits was conserved. Thus, although both rhythms show temperature-dependent changes in rhythm frequency, the processes that couple these circuits maintain their coordination over a wide range of temperatures. Such robustness to temperature changes could be part of a toolbox of processes that enables neural circuits to maintain function despite global perturbations.

Reproducing Five Motor Behaviors in a Salamander Robot With Virtual Muscles and a Distributed CPG Controller Regulated by Drive Signals and Proprioceptive Feedback.

Diverse locomotor behaviors emerge from the interactions between the spinal central pattern generator (CPG), descending brain signals and sensory feedback. Salamander motor behaviors include swimming, struggling, forward underwater stepping, and forward and backward terrestrial stepping. Electromyographic and kinematic recordings of the trunk show that each of these five behaviors is characterized by specific patterns of muscle activation and body curvature. Electrophysiological recordings in isolated spinal cords show even more diverse patterns of activity. Using numerical modeling and robotics, we explored the mechanisms through which descending brain signals and proprioceptive feedback could take advantage of the flexibility of the spinal CPG to generate different motor patterns. Adapting a previous CPG model based on abstract oscillators, we propose a model that reproduces the features of spinal cord recordings: the diversity of motor patterns, the correlation between phase lags and cycle frequencies, and the spontaneous switches between slow and fast rhythms. The five salamander behaviors were reproduced by connecting the CPG model to a mechanical simulation of the salamander with virtual muscles and local proprioceptive feedback. The main results were validated on a robot. A distributed controller was used to obtain the fast control loops necessary for implementing the virtual muscles. The distributed control is demonstrated in an experiment where the robot splits into multiple functional parts. The five salamander behaviors were emulated by regulating the CPG with two descending drives. Reproducing the kinematics of backward stepping and struggling however required stronger muscle contractions. The passive oscillations observed in the salamander's tail during forward underwater stepping could be reproduced using a third descending drive of zero to the tail oscillators. This reduced the drag on the body in our hydrodynamic simulation. We explored the effect of local proprioceptive feedback during swimming and forward terrestrial stepping. We found that feedback could replace or reduce the need for different drives in both cases. It also reduced the variability of intersegmental phase lags toward values appropriate for locomotion. Our work suggests that different motor behaviors do not require different CPG circuits: a single circuit can produce various behaviors when modulated by descending drive and sensory feedback.

Explainable artificial intelligence for heart rate variability in ECG signal.

Electrocardiogram (ECG) signal is one of the most reliable methods to analyse the cardiovascular system. In the literature, there are different deep learning architectures proposed to detect various types of tachycardia diseases, such as atrial fibrillation, ventricular fibrillation, and sinus tachycardia. Even though all types of tachycardia diseases have fast beat rhythm as the common characteristic feature, existing deep learning architectures are trained with the corresponding disease-specific features. Most of the proposed works lack the interpretation and understanding of the results obtained. Hence, the objective of this letter is to explore the features learned by the deep learning models. For the detection of the different types of tachycardia diseases, the authors used a transfer learning approach. In this method, the model is trained with one of the tachycardia diseases called atrial fibrillation and tested with other tachycardia diseases, such as ventricular fibrillation and sinus tachycardia. The analysis was done using different deep learning models, such as RNN, LSTM, GRU, CNN, and RSCNN. RNN achieved an accuracy of 96.47% for atrial fibrillation data set, 90.88% accuracy for CU-ventricular tachycardia data set, and also achieved an accuracy of 94.71, and 94.18% for MIT-BIH malignant ventricular ectopy database for ECG lead I and lead II, respectively. The RNN model could only achieve an accuracy of 23.73% for the sinus tachycardia data set. A similar trend is shown by other models. From the analysis, it was evident that even though tachycardia diseases have fast beat rhythm as their common feature, the model was not able to detect different types of tachycardia diseases. The deep learning model could only detect atrial fibrillation and ventricular fibrillation and failed in the case of sinus tachycardia. From the analysis, they were able to interpret that, along with the fast beat rhythm, the model has learned the absence of P-wave which is a common feature for ventricular fibrillation and atrial fibrillation but sinus tachycardia disease has an upright positive P-wave. The time-based analysis is conducted to find the time complexity of the models. The analysis conveyed that RNN and RSCNN models could achieve better performance with lesser time complexity.

Effectiveness of a 3D mapping benchmark for ablation in patients with atrioventricular nodal reentrant tachycardia.

Avoiding excessively fast junctional rhythm (JR) during slow pathway (SP) modification for atrioventricular nodal reentrant tachycardia (AVNRT) helps prevent serious atrioventricular block. This study investigated the usefulness of a predictive ablation point that lies near the boundary line between appropriate and excessively fast JRs with three-dimensional (3D) electroanatomical mapping in AVNRT patients. Participants were 141 consecutive patients with common AVNRT who received anatomical ablation to an antegrade SP at our institution between August 2013 and December 2019. Patients were divided into two groups: Group A, treated using a location marker that predicts successful ablation sites in a 3D mapping system, and Group B, treated prior to the development of this marker and therefore without it. The average age was 61.9±16.9years, and 41.1% of patients were male. Excessively fast JRs appeared less frequently in Group A than in Group B, though this difference did not reach significance. The distance from the His bundle to the successful ablation point was significantly longer in Group A than in Group B (13.4±4.5 vs 10.8±4.4mm, P<.01). The number of ablations near the successful ablation point was significantly lower in Group A (6.5±5.2 vs 11.4±9.9, P<.01), and a greater number of accelerated JRs at the successful ablation point were observed in Group A (46.9±29.2 vs 32.8±19.2, P<.01). Using our benchmark for a predictive successful ablation point in 3D mapping simplifies and improves common AVNRT ablation procedures.