Development and functional demonstration of a wireless intraoral inductive tongue computer interface for severely disabled persons

Struijk, Lotte N. S. Andreasen; Lontis, Romulus; Gaihede, Michael; Caltenco, Héctor; Lund, Morten Enemark; Schioeler, Henrik; Bentsen, Bo

doi:10.1080/17483107.2016.1217084

Cited by 41 publications

(19 citation statements)

References 32 publications

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“…Recently, Mohammadi et al [23] have developed a high-resolution tongue-based joystick for the tongue control interface first proposed in [24]. The tongue interface (an adapted version of the commercially available tongue control system, iTongue © [25]) contains 18 different inductive sensors [26] and thereby has the potential to control the robot without using different modes, as has been shown in [13], [25], and [26]. Mohammadi et al have also shown that controlling an ARM using a joystick like tongue based command is more effective than using discrete buttons for control [29].…”

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confidence: 99%

A Dedicated Tool Frame Based Tongue Interface Layout Improves 2D Visual Guided Control of an Assistive Robotic Manipulator: A Design Parameter for Tele-Applications

et al. 2022

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It is crucial to increase the independence of severely disabled individuals. Assistive robotics can aid in the desired activities of daily living, including tasks requiring remote performance e.g. grasping remote objects, turning switches on/off, and opening/closing doors. The robot control is compromised by the lack of efficient interfaces for individuals with disabilities and the lack of depth perception. This paper addresses these challenges by presenting the development and evaluation of efficient tongue-based robot interfaces and low-level robot control schemes targeting telerobotic control through a 2D display. Ten able-bodied participants were successful in completing ten rounds of controlling a JACO robot to perform a pouring water task, using five different control methods, under 2D or 3D visual feedback. The tool-frame based tongue interface layout, L2_TF (with emulated joystick, mode switch button and a "GO" button) improved the 2D visual guided control of the JACO robot compared with the other tongue control methods. The mean trajectory length of completing the task using L2_TF was 3% longer compared with the standard joystick when controlling through 2D. The trajectory length for reaching and grabbing a bottle was shortest for L2_TF compared with all other control methods, including the joystick. The iTongue control layouts performed well in gripping time, showing no significant difference between 2D and 3D. The transition from 2D to 3D resulted in a mean decrease of 27.7% for task completion time across all interfaces. L2_TF and the joystick had the strongest and most similar robustness to the transition between 3D and 2D.

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confidence: 99%

A Dedicated Tool Frame Based Tongue Interface Layout Improves 2D Visual Guided Control of an Assistive Robotic Manipulator: A Design Parameter for Tele-Applications

et al. 2022

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“…6. Grand average topological plots of the Alpha [8][9][10][11][12][13] Hz and Beta [13][14][15][16][17][18][19][20][21][22][23][24][25][26][27][28][29][30] Hz bandpower at movement onset, for the four different movement types averaged across all subjects and all trials. The power was calculated as meansquare of the bandpass filtered signal, referenced to common average reference, from 0.5 seconds before until movement onset.…”

Section: ) Movement Classificationmentioning

confidence: 99%

“…While it showed a new control option, it requires physical tongue movements similar to other proposed tongue control interfaces that achieve Aalborg University, 9220 Aalborg, Denmark (e-mail: rlk@hst.aau.dk; naja@hst.aau.dk). The authors T. Warburg Johansson and M. Jochumsen are with the Department of Health Science and Technology, Aalborg University, 9220 Aalborg, Denmark (e-mail: tjohan16@student.aau.dk; mj@hst.aau.dk) Feature-and classification analysis for detection and classification of tongue movements from single-trial pre-movement EEG Rasmus L. Kaeseler, Tim Warburg Johansson, Lotte N. S. Andreasen Struijk, and Mads Jochumsen I a higher performance [16], [17], [25], [26]. Furthermore, individuals with LIS will require a different system as these individuals have limited to no tongue movement.…”

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Feature and Classification Analysis for Detection and Classification of Tongue Movements From Single-Trial Pre-Movement EEG

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Johansson

Struijk

et al. 2022

IEEE Trans. Neural Syst. Rehabil. Eng.

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Individuals with severe tetraplegia can benefit from brain-computer interfaces (BCIs). While most movement-related BCI systems focus on right/left hand and/or foot movements, very few studies have considered tongue movements to construct a multiclass BCI. The aim of this study was to decode four movement directions of the tongue (left, right, up, and down) from single-trial pre-movement EEG and provide a feature and classifier investigation. In offline analyses (from ten healthy participants) detection and classification were performed using temporal, spectral, entropy, and template features classified using either a linear discriminative analysis, support vector machine, random forest or multilayer perceptron classifiers. Besides the 4class classification scenario, all possible 3-, and 2-class scenarios were tested to find the most discriminable movement type. The linear discriminant analysis achieved on average, higher classification accuracies for both movement detection and classification. The right-and down tongue movements provided the highest and lowest detection accuracy (95.3±4.3% and 91.7±4.8%), respectively. The 4-class classification achieved an accuracy of 62.6±7.2%, while the best 3-class classification (using left, right, and up movements) and 2-class classification (using left and right movements) achieved an accuracy of 75.6±8.4% and 87.7±8.0%, respectively. Using only a combination of the temporal and template feature groups provided further classification accuracy improvements. Presumably, this is because these feature groups utilize the movement-related cortical potentials, which are noticeably different on the left-versus right brain hemisphere for the different movements. This study shows that the cortical representation of the tongue is useful for extracting control signals for multi-class movement detection BCIs.

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“…The participants controlled the EXOTIC Exo using an ITCI. The ITCI (Figure 2) consists of a mouthpiece unit (MPU), an activation unit (AU), and a central unit (CU) (Struijk et al, 2017). The MPU is a dental retainer encompassing 18 inductive sensors arranged in two printed circuit boards (PCB).…”

Section: Intraoral Tongue-computer Interfacementioning

confidence: 99%

“…The intraoral tongue-computer interface (ITCI) (Struijk et al, 2017) provides 18 input commands and has a commercially available version for individuals with tetraplegia (ITongue, TKS). An assistive robotic manipulator with seven degrees of freedom was previously interfaced with the ITCI and enabled a participant with complete tetraplegia to perform tasks with the robot (Andreasen Struijk et al, 2017b).…”

Section: Introductionmentioning

confidence: 99%

Eyes-Free Tongue Gesture and Tongue Joystick Control of a Five DOF Upper-Limb Exoskeleton for Severely Disabled Individuals

et al. 2021

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Spinal cord injury can leave the affected individual severely disabled with a low level of independence and quality of life. Assistive upper-limb exoskeletons are one of the solutions that can enable an individual with tetraplegia (paralysis in both arms and legs) to perform simple activities of daily living by mobilizing the arm. Providing an efficient user interface that can provide full continuous control of such a device—safely and intuitively—with multiple degrees of freedom (DOFs) still remains a challenge. In this study, a control interface for an assistive upper-limb exoskeleton with five DOFs based on an intraoral tongue-computer interface (ITCI) for individuals with tetraplegia was proposed. Furthermore, we evaluated eyes-free use of the ITCI for the first time and compared two tongue-operated control methods, one based on tongue gestures and the other based on dynamic virtual buttons and a joystick-like control. Ten able-bodied participants tongue controlled the exoskeleton for a drinking task with and without visual feedback on a screen in three experimental sessions. As a baseline, the participants performed the drinking task with a standard gamepad. The results showed that it was possible to control the exoskeleton with the tongue even without visual feedback and to perform the drinking task at 65.1% of the speed of the gamepad. In a clinical case study, an individual with tetraplegia further succeeded to fully control the exoskeleton and perform the drinking task only 5.6% slower than the able-bodied group. This study demonstrated the first single-modal control interface that can enable individuals with complete tetraplegia to fully and continuously control a five-DOF upper limb exoskeleton and perform a drinking task after only 2 h of training. The interface was used both with and without visual feedback.

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Development and functional demonstration of a wireless intraoral inductive tongue computer interface for severely disabled persons

Cited by 41 publications

References 32 publications

A Dedicated Tool Frame Based Tongue Interface Layout Improves 2D Visual Guided Control of an Assistive Robotic Manipulator: A Design Parameter for Tele-Applications

A Dedicated Tool Frame Based Tongue Interface Layout Improves 2D Visual Guided Control of an Assistive Robotic Manipulator: A Design Parameter for Tele-Applications

Feature and Classification Analysis for Detection and Classification of Tongue Movements From Single-Trial Pre-Movement EEG

Eyes-Free Tongue Gesture and Tongue Joystick Control of a Five DOF Upper-Limb Exoskeleton for Severely Disabled Individuals

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