Publications

@InProceedings{10.1007/978-3-031-70058-3_36, author="Ziat, Mounia and Kabdsyhev, Nurlan and Topp, Sven and Duvernoy, Basil and Milroy, Jeraldine and Kappassov, Zhanat", editor="Kajimoto, Hiroyuki and Lopes, Pedro and Pacchierotti, Claudio and Basdogan, Cagatay and Gori, Monica and Lemaire-Semail, Betty and Marchal, Maud", title="Evaluation of HaptiComm-S for Replicating Tactile ASL Numbers: A Comparative Analysis of Direct and Mediated Modalities", booktitle="Haptics: Understanding Touch; Technology and Systems; Applications and Interaction", year="2025", publisher="Springer Nature Switzerland", address="Cham", pages="442--448", abstract="This research investigates the efficacy of HaptiComm-S, a haptic communication device designed to facilitate tactile communication for Deafblind individuals. The primary focus is on evaluating the device's capability to replicate the tactile American Sign Language (ASL) numbers 0 to 10. Participants performed under two distinct conditions: direct ASL signing and mediated ASL signing through two modalities (Tap and Tap-and-Hold). Our findings demonstrate significant differences in performance between the Direct and Mediated ASL modes. Direct ASL consistently exhibited higher accuracy compared to mediated conditions. Mediated ASL conditions were prone to perceptual errors in number identification. Notably, specific numbers, such as 4, 7, 8, and 9, posed challenges in the mediated conditions, often resulting in confusion among participants. These findings contribute valuable insights for the ongoing refinement in the design of haptic communication devices tailored to the needs of the Deafblind community.", isbn="978-3-031-70058-3" }

@ARTICLE{10509679, author={Keutayeva, Aigerim and Abibullaev, Berdakh}, journal={IEEE Access}, title={Data Constraints and Performance Optimization for Transformer-Based Models in EEG-Based Brain-Computer Interfaces: A Survey}, year={2024}, volume={12}, number={}, pages={62628-62647}, keywords={Brain modeling;Electroencephalography;Transformers;Data models;Decoding;Task analysis;Training;Brain-computer interfaces;data scarcity;survey;deep learning;transformer;EEG;self-attention mechanism;motor imagery;BCI}, doi={10.1109/ACCESS.2024.3394696}}

@Inbook{Keutayeva2024, author="Keutayeva, Aigerim and Zollanvari, Amin and Abibullaev, Berdakh", editor="Vinjamuri, Ramana", title="Evolving Trends and Future Prospects of Transformer Models in EEG-Based Motor-Imagery BCI Systems", bookTitle="Discovering the Frontiers of Human-Robot Interaction: Insights and Innovations in Collaboration, Communication, and Control", year="2024", publisher="Springer Nature Switzerland", address="Cham", pages="233--256", abstract="This chapter explores the transformative impact of transformer models on EEG-based motor imagery brain-computer interfaces (BCIs)---systems that are pushing the boundaries of human-machine interaction. Transformers, renowned for their self-attention mechanisms, excel at handling sequential data, making them uniquely suited for decoding intricate EEG patterns. We offer a comprehensive review of transformer applications in BCIs, showcasing how they significantly improve signal interpretation accuracy, efficiency, and robustness. The chapter examines the technical foundations, including the inherent complexities of EEG signals---noise, non-stationarity, and intersubject variability---and how transformers tackle them through superior feature extraction and denoising capabilities. We trace the evolution of these models from traditional machine-learning approaches to sophisticated architectures that capture both temporal and spatial dependencies in EEG data. The chapter then delves into practical applications of these models in real-world BCI systems, discussing how they translate into tangible benefits for users. We explore prospects and ongoing research aimed at overcoming limitations like computational demands and the need for personalized models. By analyzing emerging trends and envisioning future directions, this chapter provides a roadmap for the BCI research community, ultimately leading to more intuitive, versatile, and effective human-computer interactions.", isbn="978-3-031-66656-8", doi="10.1007/978-3-031-66656-8_10", url="https://doi.org/10.1007/978-3-031-66656-8_10" }

@INPROCEEDINGS{10780705, author={Mukashev, Dinmukhammed and Lach, Agnieszka and Hammill, Chet W and Kappassov, Zhanat and Sharma, Adwait and Nittala, Aditya Shekhar and Kohli, Luv and Razzaque, Sharif}, booktitle={2024 IEEE 20th International Conference on Body Sensor Networks (BSN)}, title={Initial Exploration into Electrotactile Tongue Stimulation for Providing Force Feedback for Robot-Assisted Surgery}, year={2024}, volume={}, number={}, pages={1-4}, keywords={Electric potential;Tongue;Force measurement;Force feedback;Surgery;Particle measurements;Safety;Interviews;Grippers;Robots;haptics;force feedback;robotic-assisted surgery;displays;tongue;sensory substitution;electrotactile stimulation}, doi={10.1109/BSN63547.2024.10780705}}

@INPROCEEDINGS{10417155, author={Mussin, Tleukhan and Kassym, Yermakhan and Kabdyshev, Nurlan and Kaikanov, Marat and Kappassov, Zhanat}, booktitle={2024 IEEE/SICE International Symposium on System Integration (SII)}, title={Action-Driven Tactile Object Exploration for Shape Reconstruction via Silver Nanowire Injected Sensors}, year={2024}, volume={}, number={}, pages={532-538}, keywords={Resistance;Point cloud compression;Silver;Shape;Robot kinematics;Tactile sensors;Sensors}, doi={10.1109/SII58957.2024.10417155}}

@INPROCEEDINGS{10417155, author={Mussin, Tleukhan and Kassym, Yermakhan and Kabdyshev, Nurlan and Kaikanov, Marat and Kappassov, Zhanat}, booktitle={2024 IEEE/SICE International Symposium on System Integration (SII)}, title={Action-Driven Tactile Object Exploration for Shape Reconstruction via Silver Nanowire Injected Sensors}, year={2024}, volume={}, number={}, pages={532-538}, keywords={Resistance;Point cloud compression;Silver;Shape;Robot kinematics;Tactile sensors;Sensors}, doi={10.1109/SII58957.2024.10417155}}

@INPROCEEDINGS{10780705, author={Mukashev, Dinmukhammed and Lach, Agnieszka and Hammill, Chet W and Kappassov, Zhanat and Sharma, Adwait and Nittala, Aditya Shekhar and Kohli, Luv and Razzaque, Sharif}, booktitle={2024 IEEE 20th International Conference on Body Sensor Networks (BSN)}, title={Initial Exploration into Electrotactile Tongue Stimulation for Providing Force Feedback for Robot-Assisted Surgery}, year={2024}, volume={}, number={}, pages={1-4}, keywords={Electric potential;Tongue;Force measurement;Force feedback;Surgery;Particle measurements;Safety;Interviews;Grippers;Robots;haptics;force feedback;robotic-assisted surgery;displays;tongue;sensory substitution;electrotactile stimulation}, doi={10.1109/BSN63547.2024.10780705}}

@misc{yergibay2024nusenserobustsoftoptical, title={NUSense: Robust Soft Optical Tactile Sensor}, author={Madina Yergibay and Tleukhan Mussin and Saltanat Seitzhan and Daryn Kenzhebek and Zhanat Kappassov and Harold Soh and Tasbolat Taunyazov}, year={2024}, eprint={2410.23516}, archivePrefix={arXiv}, primaryClass={cs.RO}, url={https://arxiv.org/abs/2410.23516}, }

@article{Topp11072024}, author = {Sven Topp, Shuangshuang Xiao, Basil Duvernoy, Jeraldine Milroy, Zhanat Kappassov, Nurlan Kabdyshev, Roope Raisamo, Vincent Hayward and Mounia Ziat}, title = {Mediated and non-mediated tactile fingerspelling: a comparative study}, journal = {Assistive Technology}, volume = {0}, number = {0}, pages = {1--10}, year = {2024}, publisher = {Taylor \& Francis}, doi = {10.1080/10400435.2024.2369547}, note ={PMID: 38990181}, URL = { https://doi.org/10.1080/10400435.2024.2369547 }, eprint = { https://doi.org/10.1080/10400435.2024.2369547 } }

@ARTICLE{10751786, author={Chibar, Rustam and Kostyukova, Valeriya and Khajikhanov, Soibkhon and Kenzhebek, Daryn and Zhakatayev, Altay and Orazbayev, Bakhtiyar and Kappassov, Zhanat}, journal={IEEE Sensors Journal}, title={Honeycomb-Inspired Metamaterial for Tactile Sensors with Variable Stiffness}, year={2024}, volume={}, number={}, pages={1-1}, keywords={Sensors;Robot sensing systems;Collision avoidance;Robots;Metamaterials;Tactile sensors;Dynamics;Honeycomb structures;Force;Magnetic materials;Force and tactile sensing;collision detection;compliance and impedance control;variable stiffness;tactile sensors;physical interactions;nonlinear stiffness;honeycombs;potential energy storage}, doi={10.1109/JSEN.2024.3492498}}

@ARTICLE{10758224, author={Mukashev, Dinmukhammed and Seitzhan, Saltanat and Chumakov, Jabrail and Khajikhanov, Soibkhon and Yergibay, Madina and Zhaniyar, Nurlan and Chibar, Rustam and Mazhitov, Ayan and Rubagotti, Matteo and Kappassov, Zhanat}, journal={IEEE Transactions on Robotics}, title={E-BTS: Event-Based Tactile Sensor for Haptic Teleoperation in Augmented Reality}, year={2025}, volume={41}, number={}, pages={450-463}, keywords={Robot sensing systems;Robots;Tactile sensors;Haptic interfaces;Force;Event detection;Cameras;Visualization;Robot vision systems;Three-dimensional printing;Augmented reality (AR);event-based vision;haptics;remote sensing;tactile sensors;visual force feedback (VFF)}, doi={10.1109/TRO.2024.3502215}}

@ARTICLE{10649586, author={Zholtayev, Darkhan and Dauletiya, Daniyar and Tileukulova, Aisulu and Akimbay, Dias and Nursultan, Manat and Bushanov, Yersaiyn and Kuzdeuov, Askat and Yeshmukhametov, Azamat}, journal={IEEE Access}, title={Smart Pipe Inspection Robot With In-Chassis Motor Actuation Design and Integrated AI-Powered Defect Detection System}, year={2024}, volume={12}, number={}, pages={119520-119534}, keywords={Inspection;Robots;Image edge detection;Simultaneous localization and mapping;Computational modeling;Sensors;Machine learning;Inpipe robot;robot design;machine learning;defect detection;pipe inspection;SLAM}, doi={10.1109/ACCESS.2024.3450502}}