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Pinheiro DJLL, Faber J, Micera S, Shokur S. Human-machine interface for two-dimensional steering control with the auricular muscles. Front Neurorobot 2023; 17:1154427. [PMID: 37342389 PMCID: PMC10277645 DOI: 10.3389/fnbot.2023.1154427] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2023] [Accepted: 05/16/2023] [Indexed: 06/22/2023] Open
Abstract
Human-machine interfaces (HMIs) can be used to decode a user's motor intention to control an external device. People that suffer from motor disabilities, such as spinal cord injury, can benefit from the uses of these interfaces. While many solutions can be found in this direction, there is still room for improvement both from a decoding, hardware, and subject-motor learning perspective. Here we show, in a series of experiments with non-disabled participants, a novel decoding and training paradigm allowing naïve participants to use their auricular muscles (AM) to control two degrees of freedom with a virtual cursor. AMs are particularly interesting because they are vestigial muscles and are often preserved after neurological diseases. Our method relies on the use of surface electromyographic records and the use of contraction levels of both AMs to modulate the velocity and direction of a cursor in a two-dimensional paradigm. We used a locking mechanism to fix the current position of each axis separately to enable the user to stop the cursor at a certain location. A five-session training procedure (20-30 min per session) with a 2D center-out task was performed by five volunteers. All participants increased their success rate (Initial: 52.78 ± 5.56%; Final: 72.22 ± 6.67%; median ± median absolute deviation) and their trajectory performances throughout the training. We implemented a dual task with visual distractors to assess the mental challenge of controlling while executing another task; our results suggest that the participants could perform the task in cognitively demanding conditions (success rate of 66.67 ± 5.56%). Finally, using the Nasa Task Load Index questionnaire, we found that participants reported lower mental demand and effort in the last two sessions. To summarize, all subjects could learn to control the movement of a cursor with two degrees of freedom using their AM, with a low impact on the cognitive load. Our study is a first step in developing AM-based decoders for HMIs for people with motor disabilities, such as spinal cord injury.
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Affiliation(s)
- Daniel J. L. L. Pinheiro
- Division of Neuroscience, Department of Neurology and Neurosurgery, Neuroengineering and Neurocognition Laboratory, Escola Paulista de Medicina, Universidade Federal de São Paulo, São Paulo, Brazil
- Translational Neural Engineering Lab, Institute Neuro X, École Polytechnique Fédérale de Lausanne, Geneva, Switzerland
| | - Jean Faber
- Division of Neuroscience, Department of Neurology and Neurosurgery, Neuroengineering and Neurocognition Laboratory, Escola Paulista de Medicina, Universidade Federal de São Paulo, São Paulo, Brazil
- Neuroengineering Laboratory, Division of Biomedical Engineering, Instituto de Ciência e Tecnologia, Universidade Federal de São Paulo, São José dos Campos, Brazil
| | - Silvestro Micera
- Translational Neural Engineering Lab, Institute Neuro X, École Polytechnique Fédérale de Lausanne, Geneva, Switzerland
- Department of Excellence in Robotics and AI, Institute of BioRobotics Interdisciplinary Health Center, Scuola Superiore Sant'Anna, Pisa, Italy
| | - Solaiman Shokur
- Translational Neural Engineering Lab, Institute Neuro X, École Polytechnique Fédérale de Lausanne, Geneva, Switzerland
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Sato W, Kochiyama T. Crosstalk in Facial EMG and Its Reduction Using ICA. SENSORS (BASEL, SWITZERLAND) 2023; 23:2720. [PMID: 36904924 PMCID: PMC10007323 DOI: 10.3390/s23052720] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Revised: 02/24/2023] [Accepted: 02/28/2023] [Indexed: 06/18/2023]
Abstract
There is ample evidence that electromyography (EMG) signals from the corrugator supercilii and zygomatic major muscles can provide valuable information for the assessment of subjective emotional experiences. Although previous research suggested that facial EMG data could be affected by crosstalk from adjacent facial muscles, it remains unproven whether such crosstalk occurs and, if so, how it can be reduced. To investigate this, we instructed participants (n = 29) to perform the facial actions of frowning, smiling, chewing, and speaking, in isolation and combination. During these actions, we measured facial EMG signals from the corrugator supercilii, zygomatic major, masseter, and suprahyoid muscles. We performed an independent component analysis (ICA) of the EMG data and removed crosstalk components. Speaking and chewing induced EMG activity in the masseter and suprahyoid muscles, as well as the zygomatic major muscle. The ICA-reconstructed EMG signals reduced the effects of speaking and chewing on zygomatic major activity, compared with the original signals. These data suggest that: (1) mouth actions could induce crosstalk in zygomatic major EMG signals, and (2) ICA can reduce the effects of such crosstalk.
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Affiliation(s)
- Wataru Sato
- Psychological Process Research Team, Guardian Robot Project, RIKEN, 2-2-2 Hikaridai, Seika-cho, Soraku-gun, Kyoto 619-0288, Japan
- Field Science Education and Research Center, Kyoto University, Oiwake-cho, Kitashirakawa, Kyoto 606-8502, Japan
| | - Takanori Kochiyama
- Brain Activity Imaging Center, ATR-Promotions, 2-2-2 Hikaridai, Seika-cho, Soraku-gun, Kyoto 619-0288, Japan
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Mitchell CL, Cler GJ, Fager SK, Contessa P, Roy SH, De Luca G, Kline JC, Vojtech JM. Ability-Based Methods for Personalized Keyboard Generation. MULTIMODAL TECHNOLOGIES AND INTERACTION 2022; 6:67. [PMID: 36313956 PMCID: PMC9608338 DOI: 10.3390/mti6080067] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
Abstract
This study introduces an ability-based method for personalized keyboard generation, wherein an individual's own movement and human-computer interaction data are used to automatically compute a personalized virtual keyboard layout. Our approach integrates a multidirectional point-select task to characterize cursor control over time, distance, and direction. The characterization is automatically employed to develop a computationally efficient keyboard layout that prioritizes each user's movement abilities through capturing directional constraints and preferences. We evaluated our approach in a study involving 16 participants using inertial sensing and facial electromyography as an access method, resulting in significantly increased communication rates using the personalized keyboard (52.0 bits/min) when compared to a generically optimized keyboard (47.9 bits/min). Our results demonstrate the ability to effectively characterize an individual's movement abilities to design a personalized keyboard for improved communication. This work underscores the importance of integrating a user's motor abilities when designing virtual interfaces.
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Affiliation(s)
| | - Gabriel J. Cler
- Department of Speech and Hearing Sciences, University of Washington, Seattle, WA 98105, USA
| | - Susan K. Fager
- Institute of Rehabilitation Science and Engineering, Madonna Rehabilitation Hospital, Lincoln, NE 68506, USA
| | - Paola Contessa
- Delsys, Inc., Natick, MA 01760, USA
- Altec, Inc., Natick, MA 01760, USA
| | - Serge H. Roy
- Delsys, Inc., Natick, MA 01760, USA
- Altec, Inc., Natick, MA 01760, USA
| | - Gianluca De Luca
- Delsys, Inc., Natick, MA 01760, USA
- Altec, Inc., Natick, MA 01760, USA
| | - Joshua C. Kline
- Delsys, Inc., Natick, MA 01760, USA
- Altec, Inc., Natick, MA 01760, USA
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Vojtech JM, Chan MD, Shiwani B, Roy SH, Heaton JT, Meltzner GS, Contessa P, De Luca G, Patel R, Kline JC. Surface Electromyography-Based Recognition, Synthesis, and Perception of Prosodic Subvocal Speech. JOURNAL OF SPEECH, LANGUAGE, AND HEARING RESEARCH : JSLHR 2021; 64:2134-2153. [PMID: 33979177 PMCID: PMC8740708 DOI: 10.1044/2021_jslhr-20-00257] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/12/2023]
Abstract
Purpose This study aimed to evaluate a novel communication system designed to translate surface electromyographic (sEMG) signals from articulatory muscles into speech using a personalized, digital voice. The system was evaluated for word recognition, prosodic classification, and listener perception of synthesized speech. Method sEMG signals were recorded from the face and neck as speakers with (n = 4) and without (n = 4) laryngectomy subvocally recited (silently mouthed) a speech corpus comprising 750 phrases (150 phrases with variable phrase-level stress). Corpus tokens were then translated into speech via personalized voice synthesis (n = 8 synthetic voices) and compared against phrases produced by each speaker when using their typical mode of communication (n = 4 natural voices, n = 4 electrolaryngeal [EL] voices). Naïve listeners (n = 12) evaluated synthetic, natural, and EL speech for acceptability and intelligibility in a visual sort-and-rate task, as well as phrasal stress discriminability via a classification mechanism. Results Recorded sEMG signals were processed to translate sEMG muscle activity into lexical content and categorize variations in phrase-level stress, achieving a mean accuracy of 96.3% (SD = 3.10%) and 91.2% (SD = 4.46%), respectively. Synthetic speech was significantly higher in acceptability and intelligibility than EL speech, also leading to greater phrasal stress classification accuracy, whereas natural speech was rated as the most acceptable and intelligible, with the greatest phrasal stress classification accuracy. Conclusion This proof-of-concept study establishes the feasibility of using subvocal sEMG-based alternative communication not only for lexical recognition but also for prosodic communication in healthy individuals, as well as those living with vocal impairments and residual articulatory function. Supplemental Material https://doi.org/10.23641/asha.14558481.
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Affiliation(s)
| | | | | | | | - James T. Heaton
- Massachusetts General Hospital Department of Surgery, Boston
| | | | | | | | - Rupal Patel
- VocaliD, Inc., Belmont, MA
- Northeastern University, Boston, MA
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Quantitative analysis of movements in facial nerve palsy with surface electromyography and kinematic analysis. J Electromyogr Kinesiol 2020; 56:102485. [PMID: 33186835 DOI: 10.1016/j.jelekin.2020.102485] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2020] [Revised: 10/14/2020] [Accepted: 10/14/2020] [Indexed: 01/19/2023] Open
Abstract
Facial nerve paralysis (FNP) has a significant effect on a person's quality of life. In individuals with FNP undergoing facial rehabilitation, methods to analyze the loss of function are useful in diagnosis, treatment and follow up. To propose a protocol with kinematic analysis coupled with sEMG to evaluate the outcomes of FNP, quantifying the excursion degrees of the facial muscles and symmetry of voluntary movements. 10 patients (Group A) were followed by diagnosis until the end of the rehabilitation program. Kinematic analysis of 20 healthy adults (group B) was performed as a starting point to have a normality range and to test intra-subject and inter- intra rater reliability. An optoelectronic system and sEMG wireless electrodes were used. In Group A, a significant improvement in the movement of frontalis muscle (P = 0.0118) after 4-week treatment from the beginning (T0) 9.8 ± 4.5 mm to the end of rehabilitation (T1) 16.3 ± 5.8 mm and orbicularis oris (P = 0.0143) from T0 14.8 ± 5.5 mm to T1 20.3 ± 3.3 mm and, a reduction of % of maximum voluntary contractions (MVC) at T1 for frontalis and orbicularis compared to T0. This protocol provides meaningful data in a simple, reliable and objective way for the functional assessment of patients with PNF.
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Groll MD, Hablani S, Vojtech JM, Stepp CE. Cursor Click Modality in an Accelerometer-Based Computer Access Device. IEEE Trans Neural Syst Rehabil Eng 2020; 28:1566-1572. [PMID: 32634095 DOI: 10.1109/tnsre.2020.2996820] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
The purpose of this study is to investigate the effects of different cursor click modalities in an alternative computer access device using accelerometry from head tilt to control cursor movement. Eighteen healthy adults performed a target acquisition task using the device with five different cursor click modalities, while maintaining cursor movement control via accelerometry. Three dwell-based click modalities with dwell times of 0.5 s, 1.0 s, and 1.5 s were tested. Two surface electromyography-based click modalities - with the sensor placed next to the eye for a blink and above the eyebrow for a brow raise - were tested. Performance was evaluated using metrics of target selection accuracy, path efficiency, target selection time, and user effort. Surface electromyography-based click modalities were as fast as the shortest dwell time and as accurate as the longest dwell time, and also minimized user effort. Three of the four performance metrics were not affected by sensor location. Future studies will investigate if these results are similar in individuals with neuromuscular disorders.
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