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Continuous Gesture Recognition from sEMG Sensor Data with Recurrent Neural Networks and Adversarial Domain Adaptation
P. 1436–1441.
Movement control of artificial limbs has made big advances in recent years. New sensor and control technology enhanced the functionality and usefulness of artificial limbs to the point that complex movements, such as grasping, can be performed to a limited extent. To date, the most successful results were achieved by applying recurrent neural networks (RNNs), However, in the domain of artificial hands, experiments so far were limited to non-mobile wrists, which significantly reduces the functionality of such prostheses. In this paper, for the first time, we present empirical results on gesture recognition with both mobile and non-mobile wrists. Furthermore, we demonstrate that recurrent neural networks with simple recurrent units (SRU) outperform regular RNNs in both cases in terms of gesture recognition accuracy, on data acquired by an arm band sensing electromagnetic signals from arm muscles (via surface electromyography or sEMG). Finally, we show that adding domain adaptation techniques to continuous gesture recognition with RNN improves the transfer ability between subjects, where a limb controller trained on data from one person is used for another person.
Pikul A. S., Безопасность информационных технологий 2024 Т. 31 № 4 С. 116–127
This article explores the potential use of modern computer vision architectures for the task of deepfake detection. The following architectures are considered: EfficientNet, Vision Transformer (ViT), VisionLSTM (ViL), Vision KAN, and Mamba Vision. The novelty of the approach lies in the application and comparison of these architectures, as well as their combination into paired ensembles ...
Added: December 12, 2025
Alexeev A., Tsoy T., Martinez-Garcia E. et al., , in: Proceedings Of The 2024 International Conference On Artificial Life And Robotics February 22 To 25, 2024 J:Com Horutohall, Oita, Japan. 29Th Arob International Meeting Series.: ALife Robotics Corporation Ltd., 2024. P. 295–299.
Visual sensors play an important role in a broad variety of robotic systems applications. Even though Kinect technology appeared over 10 years ago, Kinect sensors are still actively employed by researchers around the world. This paper presents an overview of Kinect and Kinect 2 sensors’ applications in a human gesture based control. We analyzed existing research papers to ...
Added: February 19, 2025
Sushentsev N., Abrego L., Colarieti A. et al., EUROPEAN UROLOGY OPEN SCIENCE 2023 Vol. 52 P. 36–39
The global uptake of prostate cancer (PCa) active surveillance (AS) is steadily increasing. While prostate-specific antigen density (PSAD) is an important baseline predictor of PCa progression on AS, there is a scarcity of recommendations on its use in follow-up. In particular, the best way of measuring PSAD is unclear. One approach would be to use ...
Added: February 28, 2024
Makarov I., Bakhanova M., Nikolenko S. et al., PeerJ Computer Science 2022 Vol. 8 Article e865
Depth estimation has been an essential task for many computer vision applications, especially in autonomous driving, where safety is paramount. Depth can be estimated not only with traditional supervised learning but also via a self-supervised approach that relies on camera motion and does not require ground truth depth maps. Recently, major improvements have been introduced ...
Added: February 1, 2022
Tugin S., Souza V. H., Nazarova M. et al., Plos One 2021 Vol. 16 No. 9 Article e0257554
Besides stimulus intensities and interstimulus intervals (ISI), the electric field (E-field) orientation is known to affect both short-interval intracortical inhibition (SICI) and facilitation (SICF) in paired-pulse transcranial magnetic stimulation (TMS). However, it has yet to be established how distinct orientations of the conditioning (CS) and test stimuli (TS) affect the SICI and SICF generation. With ...
Added: October 31, 2021
Chirkova N., , in: 2021 Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL 2021).: Association for Computational Linguistics, 2021. P. 2679–2689.
Source code processing heavily relies on the methods widely used in natural language processing (NLP), but involves specifics that need to be taken into account to achieve higher quality. An example of this specificity is that the semantics of a variable is defined not only by its name but also by the contexts in which ...
Added: August 31, 2021
Alexandrov Y., Feldman B., Svarnik O. et al., Journal of Analytical Psychology 2020 Vol. 65 No. 2 P. 345–365
The concept of regression is considered with an emphasis on the differences
between the positions of Freud and Jung regarding its significance. The paper discusses
the results of experimental analyses of individual experience dynamics (from gene
expression changes and impulse neuronal activity in animals to prosocial behaviour in
healthy humans at different ages, and humans in chronic pain) in ...
Added: December 28, 2020
Ugrumov M., Doklady Biochemistry and Biophysics 2020 Vol. 490 P. 34–37
One of the features of the developing suprachiasmatic nucleus (SCN), the “biological clock” of the body, is the early expression of dopamine (DA) receptors in the absence of dopaminergic neurons as a source of DA. Only recently we showed that DA in SCN is synthesized together by nerve fibers containing only tyrosine hydroxylase (TH) and ...
Added: December 6, 2020
Alieva A., Rudenok M., Filatova E. et al., Scientific Reports 2020 Vol. 10 Article 827
Valosin-containing human protein (VCP) or p97 performs enzyme functions associated with the maintenance of protein homeostasis and control of protein quality. Disruption of its normal functioning might be associated with the development of Parkinson’s disease (PD). Tissues of mice with toxininduced presymptomatic and early symptomatic stages of PD, as well as 52 treated and untreated ...
Added: December 6, 2020
Lobacheva E., Chirkova N., Markovich A. et al., , in: Thirty-Fourth AAAI Conference on Artificial IntelligenceVol. 34.: AAAI Press, 2020. Ch. 5938 P. 4989–4996.
Added: October 29, 2020
Arefyev, N.V., Gratsianova T. Y., Popov K., , in: Computational Linguistics and Intellectual Technologies. International Conference "Dialogue 2018" Proceedings.: M.: Conference Proceedings Editorial board, 2018. P. 85–95.
Morphological segmentation is an important task of natural language processing as it can significantly improve the processing of unfamiliar and rare words in different tasks that involve text data. In this paper we present datasets in English and Russian for learning and evaluating morphological segmentation algorithms, demonstrate the method based on the sequence to sequence ...
Added: October 9, 2020
Kodryan M., Grachev A., Ignatov D. I. et al., , in: Proceedings of the 4th Workshop on Representation Learning for NLP (RepL4NLP-2019)Issue W19-43.: Association for Computational Linguistics, 2019. P. 40–48.
Reduction of the number of parameters is one of the most important goals in Deep Learning. In this article we propose an adaptation of Doubly Stochastic Variational Inference for Automatic Relevance Determination (DSVI-ARD) for neural networks compression. We find this method to be especially useful in language modeling tasks, where large number of parameters in ...
Added: November 1, 2019
Grachev A., Ignatov D. I., Savchenko A., Applied Soft Computing Journal 2019 Vol. 79 P. 354–362
Recurrent neural networks have proved to be an effective method for statistical language modeling. However, in practice their memory and run-time complexity are usually too large to be implemented in real-time offline mobile applications. In this paper we consider several compression techniques for recurrent neural networks including Long–Short Term Memory models. We make particular attention ...
Added: June 12, 2019
Lobacheva E., Chirkova N., Vetrov D., , in: Workshop on Compact Deep Neural Network Representation with Industrial Applications, Thirty-second Conference on Neural Information Processing Systems.: Montréal: [б.и.], 2018. P. 1–6.
Bayesian methods have been successfully applied to sparsify weights of neural networks and to remove structure units from the networks, e. g. neurons. We apply and further develop this approach for gated recurrent architectures. Specifically, in addition to sparsification of individual weights and neurons, we propose to sparsify preactivations of gates and information flow in LSTM. ...
Added: December 5, 2018
Aleksandrov Y., Gorkin A. G., Kuzina E. A. et al., Neuroscience and Behavioral Physiology, Springer New York 2018 Vol. 48 No. 18 P. 1014–1018
Neuron spike activity was recorded in the retrosplenial area of the cortex during execution of acquired cyclic operant food-procuring behavior (COFPB) in adult (8–12 months) and elderly (20–27 months) LongEvans rats. As compared with adult rats, elderly animals showed a signifi cant decrease in the proportion of neurons specialized for COFPB. The normalized discharge frequency ...
Added: November 15, 2018
Lobacheva E., Chirkova N., Vetrov D., , in: 1st Workshop on Learning to Generate Natural Language, International Conference on Machine Learning.: [б.и.], 2017. P. 1–8.
Recurrent neural networks show state-of-the-art results in many text analysis tasks but often require a lot of memory to store their weights. Recently proposed Sparse Variational Dropout (Molchanov et al., 2017) eliminates the majority of the weights in a feed-forward neural network without significant loss of quality. We apply this technique to sparsify recurrent neural ...
Added: October 30, 2018
Leblond R., Alayrac J., Osokin A. et al., , in: Proceedings of the 6th International Conference on Learning Representations (ICLR 2018).: [б.и.], 2018. P. 1–16.
We propose SEARNN, a novel training algorithm for recurrent neural networks (RNNs) inspired by the "learning to search" (L2S) approach to structured prediction. RNNs have been widely successful in structured prediction applications such as machine translation or parsing, and are commonly trained using maximum likelihood estimation (MLE). Unfortunately, this training loss is not always an ...
Added: October 29, 2018
Kazakov A., Леванова Т. А., Коротков А. Г. et al., Известия высших учебных заведений. Прикладная нелинейная динамика 2018 Т. 26 № 5 С. 101–112
The phenomenological model of an ensemble of three neurons which are coupled by
chemical (synaptic) and electrical couplings is studies. A neuron is modeled by the oscillator of van
der Pol. The aim of work is a study of the influence of coupling’s strength and frequency detuning
between elements at regime of sequential activity that is observed in ...
Added: October 26, 2018
Zakharov D., Гуткин Б. С., Krupa M. et al., Physical Review E - Statistical, Nonlinear, and Soft Matter Physics 2018 Vol. 97 No. 6 P. 062211-1–062211-5
We analyzed a generic relaxation oscillator under moderately strong forcing at a frequency much greater that the natural intrinsic frequency of the oscillator. Additionally, the forcing is of the same sign and, thus, has a nonzero average, matching neuroscience applications. We found that, first, the transition to high-frequency synchronous oscillations occurs mostly through periodic solutions ...
Added: October 4, 2018
Александров Ю.И., Сварник О. Е., Знаменская И. И. et al., Вопросы психологии 2017 № 3 С. 80–91
Alcoholism as a cause of regression in learning and in pro-social behavior
Alexandrov Yu.I., Svarnik O.Ye., Znamenskaya I.I., Arutiunova K.R., Kolbeneva M.G., Krylov A.K., Bulava A.N.
Despite a long history of the notion of regression, its manifestations and mechanisms are still poorly researched, specific experimental studies are rare, points of view conflict. A study was conducted to discover dynamics of subjective experience and brain activity lying ...
Added: January 30, 2018
Гуткин Б. С., Chalk M., Masset P. et al., PLoS Computational Biology 2017 Vol. 13 No. 6 P. 1–16
In order to respond reliably to specific features of their environment, sensory neurons need to integrate multiple incoming noisy signals. Crucially, they also need to compete for the interpretation of those signals with other neurons representing similar features. The form that this competition should take depends critically on the noise corrupting these signals. In this ...
Added: October 17, 2017