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Generating Handwriting from Multichannel Electromyographic Activity
P. 11–23.
Handwriting is an advanced motor skill and one of the key developments in human culture. Here we show that handwriting can be decoded—offline and online—from electromyographic (EMG) signals recorded from multiple hand and forearm muscles. We convert EMGs into continuous handwriting traces and into discretely decoded font characters. For this purpose, we use Wiener and Kalman filters, and machine learning algorithms. Our approach is applicable to clinical neural prostheses for restoration of dexterous hand movements, and to medical diagnostics of neural disorders that affect handwriting. We also propose that handwriting could be decoded from cortical activity, such as the activity recorded with electrocorticography (ECoG).
Решетникова В. В., Боброва Е. В., Гришин А. А. et al., Журнал высшей нервной деятельности им. И.П. Павлова 2025 Т. 75 № 3 С. 313–326
Neurorehabilitation of motor functions using a neurointerface (BCI) with feedback is a modern promising area of research. However, there is very little data on muscle activity during the motor imagery of lower limb – an important aspect of rehabilitation. The EMG activity of the lower limb muscles was studied in 42 healthy participants which control ...
Added: March 11, 2026
Fedosov N., Medvedeva D., Shevtsov O. et al., Journal of Neural Engineering 2025 No. 22 Article 046031
Objective. Recent advances in biomagnetic sensing have led to the development of compact, wearable devices capable of detecting weak magnetic fields generated by biological activity. Optically pumped magnetometers (OPMs) have shown significant promise in functional neuroimaging. Brain rhythms play a crucial role in diagnostics, cognitive research, and neurointerfaces. Here we demonstrate that a small number of ...
Added: September 5, 2025
Voskoboynikov A., Magomed Aliverdiev, Yulia Nekrasova et al., Journal of Neural Engineering 2025 Vol. 22 No. 5 Article 056002
Objective. The precise mapping of speech-related functions is crucial for successful neurosurgical interventions in epilepsy and brain tumor cases. Traditional methods like electrocortical stimulation mapping (ESM) are effective but carry a significant risk of inducing seizures. Methods. To address this, we have prepared a comprehensive ESM + electrocorticographic mapping (ECM) dataset from 14 patients with chronically implanted stereo-EEG electrodes. Then ...
Added: September 2, 2025
Aksiotis V., Alexei Ossadtchi, , in: 2022 Fourth International Conference Neurotechnologies and Neurointerfaces (CNN) Kaliningrad, 14-16 Sept. 2022.: IEEE, 2022. P. 6–9.
In the present study, a fast and adaptive technique for the presentation of stimuli based on ongoing brain rhythm is described. Sensorimotor cortical mu rhythm (divided by two components: alpha (mu) and beta) was used as target for assessment of prestimulus rhythm’s power influence on the consequent reaction time. The final sample consisted of 15 ...
Added: December 16, 2022
Makarova A., Volkova K., Ossadtchi A. et al., , in: 2022 Fourth International Conference Neurotechnologies and Neurointerfaces (CNN) Kaliningrad, 14-16 Sept. 2022.: IEEE, 2022. P. 86–89.
Brain-computer interfaces (BCIs) based on electrocorticographic (ECoG) activity has become relatively popular due to sensitivity of ECoG to specific details of actual and imagined actions. It has been shown that significant differences in the brain activity while performing hand movements in different directions can be found in relation to cosine tuning theory. This research seeks ...
Added: December 16, 2022
Makarova A., Volkova K., Lebedev M. et al., , in: 2021 Third International Conference Neurotechnologies and Neurointerfaces (CNN).: IEEE, 2021. P. 64–66.
This study aims to identify correlations between the directions of the hand movements and the brain signals recorded from the brain surface using electrocorticography (ECoG). We suppose that the coding of the hand movement direction occurs in the motor cortex and could be detected with ECoG. Using representational similarity analysis (RSA) and the cosine tuning ...
Added: December 9, 2022
Petrosyan A., Синкин М. В., Lebedev M. et al., Journal of Neural Engineering 2021 Vol. 18 Article 026019
Abstract
Objective. Brain–computer interfaces (BCIs) decode information from neural activity and send it to external devices. The use of Deep Learning approaches for decoding allows for automatic feature engineering within the specific decoding task. Physiologically plausible interpretation of the network parameters ensures the robustness of the learned decision rules and opens the exciting opportunity for automatic knowledge ...
Added: January 24, 2022
Mohammed A., Kosonogov V., Lyusin D., Scandinavian Journal of Psychology 2022 Vol. 63 No. 3 P. 182–190
The ability to exert influence on our emotions plays a significant role in the attainment of our goals. To have control over when and how we experience emotions is thought to be impacted by higher cognitive processes such as executive functions. However, there is inadequate research to support this notion. Hence, we examined the relationship ...
Added: December 14, 2021
Fedosov N., Shevtsov O., Ossadtchi A., , in: 2021 Third International Conference Neurotechnologies and Neurointerfaces (CNN).: IEEE, 2021. P. 16–18.
Added: December 8, 2021
Vidaurre C., Jorajuría T., Ramos-Murguialday A. et al., Journal of Neural Engineering 2021 Vol. 18 No. 4 Article 0460b1
Objective.Motor imagery is the mental simulation of movements. It is a common paradigm to design brain-computer interfaces (BCIs) that elicits the modulation of brain oscillatory activity similar to real, passive and induced movements. In this study, we used peripheral stimulation to provoke movements of one limb during the performance of motor imagery tasks. Unlike other ...
Added: September 8, 2021
Kardonov Y., Инновации и инвестиции 2020 № 8 С. 191–193
Neurotechnologies are used in various areas of the real economy. The article analyzes the solutions of companies in the field of neurotechnology to identify the main areas of commercial application of such solutions. The classification of these solutions is given for such areas of application as assessment and development of skills using neurotechnology, neuromarketing, neurocontrol, ...
Added: January 9, 2021
Volkova K., Lebedev M., Kaplan A. et al., Frontiers in Neuroinformatics 2019 No. 13 P. 1–20
Electrocorticography (ECoG) holds promise to provide efficient neuroprosthetic solutions for people suffering from neurological disabilities. This recording technique combines adequate temporal and spatial resolution with the lower risks of medical complications compared to the other invasive methods. ECoG is routinely used in clinical practice for preoperative cortical mapping in epileptic patients. During the last two ...
Added: April 4, 2020
Maudrich T., Kenville R., Nikulin V. et al., Neuroscience 2019 No. 406 P. 300–313
Mirror Activity (MA) is a phenomenon that is characterized by involuntarily occurring muscular activity inhomologous contralateral limbs during unilateral movements. Even in neurologically healthy humans, MA of a smallextent has been described, which does not directly lead to visible movements, but nonetheless, it is still detectable withsurface electromyography (EMG) and therefore defined as physiological MA ...
Added: October 25, 2019
Arkhipova N., Aleksandrov M., Chukhlovin A. et al., Clinical Neurophysiology 2017 Vol. 128 No. 9 P. e288
Added: June 26, 2018
Volkova K., Dagaev N., Киселёв А. С. et al., Журнал высшей нервной деятельности им. И.П. Павлова 2017 Т. 67 № 4 С. 504–520
Brain-computer interfaces find application in a number of different areas and have the potential to be used for research as well as for practical purposes. The clinical use of BCI includes current studies on neurorehabilitation ([Frolov et al., 2013; Ang et al., 2010]), and there is the prospect of using BCI to restore movement and ...
Added: October 19, 2017