Medical palpation autonomous robotic system modeling and simulation in ROS/Gazebo

Shafikov, Artur; Tsoy, Tatyana; Lavrenov, Roman; Magid, Evgeni; Li, Hongbing; Маслак, Е. Е.; Schiefermeier-Mach, Natalia

doi:10.1109/dese51703.2020.9450784

Cited by 6 publications

(2 citation statements)

References 16 publications

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“…The significant achievement of robotics is the direct assistance to humans, which makes this field in demand nowadays. Modern robots perform a huge range of tasks: they can provide the necessary assistance to the elderly [11], they can be used for medical procedures and examinations [12], [13] and find application as personnel in hospitals [14], and they are also used in areas of high risk for humans, in rescue operations [15]. Currently, robotics is widely used in education [16].…”

Section: Introductionmentioning

confidence: 99%

Robot-Assisted Language Learning: Scientific Data Analysis

Sadyikova,

Zhukova,

Lavrenov

2024

Proceedings of International Conference on Artificial Life and Robotics

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Robot-assisted language learning (RALL) is a direction in education that uses robots in the process of studying foreign languages. In this paper, we present the results of our research work devoted to studying trends in the quantity of publications in the field of using social robots for learning foreign languages. Additionally, we have analyzed some published paper in the field of RALL, which has allowed us to identify several popular robot models used in practical research in recent years. Among these models were the NAO, Pepper and DARWIN OP-2 robots. We have found that these robots are actively used in the educational process for learning foreign languages. In particular, these models are used to improve language and communication skills during implicit learning and interactive games.

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Section: Introductionmentioning

confidence: 99%

Robot-Assisted Language Learning: Scientific Data Analysis

Sadyikova,

Zhukova,

Lavrenov

2024

Proceedings of International Conference on Artificial Life and Robotics

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“…Computer-based palpation training simulators that utilise visual feedback include visualising the colours and texture of tumours ( Shafikov et al, 2020 ) or generating virtual patients ( Kotranza and Lok, 2008 ; Wandner et al, 2010 ; Rivera-Gutierrez et al, 2012 ; Maicher et al, 2017 ; Daher et al, 2020 ). However, virtual simulators lack the physicality that has been identified as an important aspect of medical training ( Chuah et al, 2013 ; Pan and Steed, 2016 ).…”

Section: Introductionmentioning

confidence: 99%

Vocal pain expression augmentation for a robopatient

Protpagorn,

Lalitharatne,

Costi

et al. 2023

Front. Robot. AI

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Abdominal palpation is one of the basic but important physical examination methods used by physicians. Visual, auditory, and haptic feedback from the patients are known to be the main sources of feedback they use in the diagnosis. However, learning to interpret this feedback and making accurate diagnosis require several years of training. Many abdominal palpation training simulators have been proposed to date, but very limited attempts have been reported in integrating vocal pain expressions into physical abdominal palpation simulators. Here, we present a vocal pain expression augmentation for a robopatient. The proposed robopatient is capable of providing real-time facial and vocal pain expressions based on the exerted palpation force and position on the abdominal phantom of the robopatient. A pilot study is conducted to test the proposed system, and we show the potential of integrating vocal pain expressions to the robopatient. The platform has also been tested by two clinical experts with prior experience in abdominal palpation. Their evaluations on functionality and suggestions for improvements are presented. We highlight the advantages of the proposed robopatient with real-time vocal and facial pain expressions as a controllable simulator platform for abdominal palpation training studies. Finally, we discuss the limitations of the proposed approach and suggest several future directions for improvements.

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