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Cervera-Negueruela M, Chee L, Cimolato A, Valle G, Tschopp M, Menke M, Papazoglou A, Raspopovic S. Bionic blink improves real-time eye closure in unilateral facial paralysis. J Neural Eng 2024; 21:026020. [PMID: 38507808 DOI: 10.1088/1741-2552/ad35e7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2023] [Accepted: 03/20/2024] [Indexed: 03/22/2024]
Abstract
Facial paralysis is the inability to move facial muscles thereby impairing the ability to blink and make facial expressions. Depending on the localization of the nerve malfunction it is subcategorised into central or peripheral and is usually unilateral. This leads to health deficits stemming from corneal dryness and social ostracization.Objective: Electrical stimulation shows promise as a method through which to restore the blink function and as a result improve eye health. However, it is unknown whether a real-time, myoelectrically controlled, neurostimulating device can be used as assistance to this pathological condition.Approach: We developed NEURO-BLINK, a wearable robotic system, that can detect the volitional healthy contralateral blink through electromyography and electrically stimulate the impaired subcutaneous facial nerve and orbicularis oculi muscle to compensate for lost blink function. Alongside the system, we developed a method to evaluate optimal electrode placement through the relationship between blink amplitude and injected charge.Main results: Ten patients with unilateral facial palsy were enrolled in the NEURO-BLINK study, with eight completing testing under two conditions. (1) where the stimulation was cued with an auditory signal (i.e. paced controlled) and (2) synchronized with the natural blink (i.e. myoelectrically controlled). In both scenarios, overall eye closure (distance between eyelids) and cornea coverage measured with high FPS video were found to significantly improve when measured in real-time, while no significant clinical changes were found immediately after use.Significance: This work takes steps towards the development of a portable medical device for blink restoration and facial stimulation which has the potential to improve long-term ocular health.
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Affiliation(s)
- Mar Cervera-Negueruela
- Department of Health Sciences and Technology, Neuroengineering Laboratory, ETH Zürich, Tannenstrasse 1, 8092 Zürich, Switzerland
| | - Lauren Chee
- Department of Health Sciences and Technology, Neuroengineering Laboratory, ETH Zürich, Tannenstrasse 1, 8092 Zürich, Switzerland
| | - Andrea Cimolato
- Department of Health Sciences and Technology, Neuroengineering Laboratory, ETH Zürich, Tannenstrasse 1, 8092 Zürich, Switzerland
| | - Giacomo Valle
- Department of Health Sciences and Technology, Neuroengineering Laboratory, ETH Zürich, Tannenstrasse 1, 8092 Zürich, Switzerland
| | - Markus Tschopp
- Department of Ophthalmology, Cantonal Hospital Aarau, Aarau, Switzerland
- Department of Ophthalmology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Marcel Menke
- Department of Ophthalmology, Cantonal Hospital Aarau, Aarau, Switzerland
- Department of Ophthalmology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Anthia Papazoglou
- Department of Ophthalmology, Cantonal Hospital Aarau, Aarau, Switzerland
- Medical Faculty, University of Zurich, Zurich, Switzerland
| | - Stanisa Raspopovic
- Department of Health Sciences and Technology, Neuroengineering Laboratory, ETH Zürich, Tannenstrasse 1, 8092 Zürich, Switzerland
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Moon B, Park KY, Mun HG, Kim YS, Kim YJ. The significance of split-face studies and electromyography in forehead rejuvenation. Arch Craniofac Surg 2023; 24:218-222. [PMID: 37919908 PMCID: PMC10622953 DOI: 10.7181/acfs.2023.00451] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2023] [Revised: 09/27/2023] [Accepted: 10/09/2023] [Indexed: 11/04/2023] Open
Abstract
BACKGROUND Botulinum toxin is a neurotoxic substance with a wide range of uses, from the treatment of musculoskeletal spasms to antiaging regimens by improving wrinkles. Split-face studies in which drugs are injected in the right and left sides of the faces have been actively conducted in botulinum toxin studies. In this study, we aimed to investigate the reliability of a split-face study for determining the effectiveness of botulinum toxin based on eyebrow height and movement, and electromyography results. METHODS Thirty-one women aged 35 to 55 years were included in the study. Eyebrow height was measured as the distance from the eyebrows to the upper eyelid margin on the primary gaze, and eyebrow movement was measured as the distance when the forehead was wrinkled for 5 seconds. A noninvasive method was used for electromyography of the frontalis muscles. RESULTS No statistically significant differences in right and left eyebrow heights and movements, and electromyography findings (p= 0.256, p= 1.000, and p= 0.978, respectively) were found. Pearson correlation analysis showed that electromyography muscle activity is positively associated with eyebrow movement, respectively (p< 0.001). CONCLUSION We advocate the reliability of split-face study and the usefulness of electromyography of frontalis muscle in forehead rejuvenation research.
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Affiliation(s)
- Bomin Moon
- Department of Plastic and Reconstructive Surgery, Gachon University Gil Medical Center, Gachon University College of Medicine, Incheon, Korea
| | - Ki Young Park
- Gachon University College of Medicine, Incheon, Korea
| | - Hye Gwang Mun
- Department of Plastic and Reconstructive Surgery, Gachon University Gil Medical Center, Gachon University College of Medicine, Incheon, Korea
| | - Yun Sang Kim
- Department of Plastic and Reconstructive Surgery, Gachon University Gil Medical Center, Gachon University College of Medicine, Incheon, Korea
| | - Yu Jin Kim
- Department of Plastic and Reconstructive Surgery, Gachon University Gil Medical Center, Gachon University College of Medicine, Incheon, Korea
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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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Hochreiter J, Hoche E, Janik L, Volk GF, Leistritz L, Anders C, Guntinas-Lichius O. Machine-Learning-Based Detecting of Eyelid Closure and Smiling Using Surface Electromyography of Auricular Muscles in Patients with Postparalytic Facial Synkinesis: A Feasibility Study. Diagnostics (Basel) 2023; 13:diagnostics13030554. [PMID: 36766657 PMCID: PMC9914547 DOI: 10.3390/diagnostics13030554] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2022] [Revised: 01/27/2023] [Accepted: 01/31/2023] [Indexed: 02/05/2023] Open
Abstract
Surface electromyography (EMG) allows reliable detection of muscle activity in all nine intrinsic and extrinsic ear muscles during facial muscle movements. The ear muscles are affected by synkinetic EMG activity in patients with postparalytic facial synkinesis (PFS). The aim of the present work was to establish a machine-learning-based algorithm to detect eyelid closure and smiling in patients with PFS by recording sEMG using surface electromyography of the auricular muscles. Sixteen patients (10 female, 6 male) with PFS were included. EMG acquisition of the anterior auricular muscle, superior auricular muscle, posterior auricular muscle, tragicus muscle, orbicularis oculi muscle, and orbicularis oris muscle was performed on both sides of the face during standardized eye closure and smiling tasks. Machine-learning EMG classification with a support vector machine allowed for the reliable detection of eye closure or smiling from the ear muscle recordings with clear distinction to other mimic expressions. These results show that the EMG of the auricular muscles in patients with PFS may contain enough information to detect facial expressions to trigger a future implant in a closed-loop system for electrostimulation to improve insufficient eye closure and smiling in patients with PFS.
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Affiliation(s)
- Jakob Hochreiter
- Department of Medical Engineering, University of Applied Sciences Upper Austria, 4020 Linz, Austria
- MED-EL Elektromedizinische Geräte GmbH, 6020 Innsbruck, Austria
| | - Eric Hoche
- Department of Otorhinolaryngology, Jena University Hospital, 07743 Jena, Germany
| | - Luisa Janik
- Department of Otorhinolaryngology, Jena University Hospital, 07743 Jena, Germany
| | - Gerd Fabian Volk
- Department of Otorhinolaryngology, Jena University Hospital, 07743 Jena, Germany
- Facial-Nerve-Center, Jena University Hospital, 07747 Jena, Germany
- Center for Rare Diseases, Jena University Hospital, 07747 Jena, Germany
| | - Lutz Leistritz
- Institute of Medical Statistics, Computer and Data Sciences, Jena University Hospital, 07743 Jena, Germany
| | - Christoph Anders
- Division for Motor Research, Pathophysiology and Biomechanics, Department for Trauma-, Hand- and Reconstructive Surgery, Jena University Hospital, 07743 Jena, Germany
| | - Orlando Guntinas-Lichius
- Department of Otorhinolaryngology, Jena University Hospital, 07743 Jena, Germany
- Facial-Nerve-Center, Jena University Hospital, 07747 Jena, Germany
- Center for Rare Diseases, Jena University Hospital, 07747 Jena, Germany
- Correspondence: ; Tel.: +49-3641-9329301; Fax: +49-3641-9329302
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Zhang H, Zhao M, Wei C, Mantini D, Li Z, Liu Q. EEGdenoiseNet: a benchmark dataset for deep learning solutions of EEG denoising. J Neural Eng 2021; 18. [PMID: 34596046 DOI: 10.1088/1741-2552/ac2bf8] [Citation(s) in RCA: 35] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2021] [Accepted: 09/29/2021] [Indexed: 12/21/2022]
Abstract
Objective.Deep learning (DL) networks are increasingly attracting attention across various fields, including electroencephalography (EEG) signal processing. These models provide comparable performance to that of traditional techniques. At present, however, there is a lack of well-structured and standardized datasets with specific benchmark limit the development of DL solutions for EEG denoising.Approach.Here, we present EEGdenoiseNet, a benchmark EEG dataset that is suited for training and testing DL-based denoising models, as well as for performance comparisons across models. EEGdenoiseNet contains 4514 clean EEG segments, 3400 ocular artifact segments and 5598 muscular artifact segments, allowing users to synthesize contaminated EEG segments with the ground-truth clean EEG.Main results.We used EEGdenoiseNet to evaluate denoising performance of four classical networks (a fully-connected network, a simple and a complex convolution network, and a recurrent neural network). Our results suggested that DL methods have great potential for EEG denoising even under high noise contamination.Significance.Through EEGdenoiseNet, we hope to accelerate the development of the emerging field of DL-based EEG denoising. The dataset and code are available athttps://github.com/ncclabsustech/EEGdenoiseNet.
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Affiliation(s)
- Haoming Zhang
- Shenzhen Key Laboratory of Smart Healthcare Engineering, Department of Biomedical Engineering, Southern University of Science and Technology, Shenzhen 518055, People's Republic of China
| | - Mingqi Zhao
- Shenzhen Key Laboratory of Smart Healthcare Engineering, Department of Biomedical Engineering, Southern University of Science and Technology, Shenzhen 518055, People's Republic of China.,Movement Control and Neuroplasticity Research Group, KU Leuven, Leuven 3001, Belgium
| | - Chen Wei
- Shenzhen Key Laboratory of Smart Healthcare Engineering, Department of Biomedical Engineering, Southern University of Science and Technology, Shenzhen 518055, People's Republic of China
| | - Dante Mantini
- Movement Control and Neuroplasticity Research Group, KU Leuven, Leuven 3001, Belgium.,Brain Imaging and Neural Dynamics Research Group, IRCCS San Camillo Hospital, Venice 30126, Italy
| | - Zherui Li
- Shenzhen Key Laboratory of Smart Healthcare Engineering, Department of Biomedical Engineering, Southern University of Science and Technology, Shenzhen 518055, People's Republic of China
| | - Quanying Liu
- Shenzhen Key Laboratory of Smart Healthcare Engineering, Department of Biomedical Engineering, Southern University of Science and Technology, Shenzhen 518055, People's Republic of China
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Activity Evaluation of Facial Muscles by Surface Electromyography. PLASTIC AND RECONSTRUCTIVE SURGERY-GLOBAL OPEN 2020; 8:e3081. [PMID: 33173663 PMCID: PMC7647650 DOI: 10.1097/gox.0000000000003081] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2020] [Accepted: 07/13/2020] [Indexed: 11/25/2022]
Abstract
Surface electromyography (sEMG) is an easy, noninvasive, and reproducible way to assess spontaneous electrical activity of muscles in real time. In this study, we report data on the correlation between sEMG and mimetic muscle activity during specific tasks so as to create a case–control reference for future studies on acute, chronic, and congenital facial palsy.
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Talib I, Sundaraj K, Lam CK, Hussain J, Ali MA. A review on crosstalk in myographic signals. Eur J Appl Physiol 2018; 119:9-28. [PMID: 30242464 DOI: 10.1007/s00421-018-3994-9] [Citation(s) in RCA: 33] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2018] [Accepted: 09/14/2018] [Indexed: 12/21/2022]
Abstract
PURPOSE Crosstalk in myographic signals is a major hindrance to the understanding of local information related to individual muscle function. This review aims to analyse the problem of crosstalk in electromyography and mechanomyography. METHODS An initial search of the SCOPUS database using an appropriate set of keywords yielded 290 studies, and 59 potential studies were selected after all the records were screened using the eligibility criteria. This review on crosstalk revealed that signal contamination due to crosstalk remains a major challenge in the application of surface myography techniques. Various methods have been employed in previous studies to identify, quantify and reduce crosstalk in surface myographic signals. RESULTS Although correlation-based methods for crosstalk quantification are easy to use, there is a possibility that co-contraction could be interpreted as crosstalk. High-definition EMG has emerged as a new technique that has been successfully applied to reduce crosstalk. CONCLUSIONS The phenomenon of crosstalk needs to be investigated carefully because it depends on many factors related to muscle task and physiology. This review article not only provides a good summary of the literature on crosstalk in myographic signals but also discusses new directions related to techniques for crosstalk identification, quantification and reduction. The review also provides insights into muscle-related issues that impact crosstalk in myographic signals.
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Affiliation(s)
- Irsa Talib
- School of Mechatronic Engineering, Universiti Malaysia Perlis (UniMAP), 02600, Arau, Perlis, Malaysia.
| | - Kenneth Sundaraj
- Centre for Telecommunication Research and Innovation (CeTRI), Fakulti Kejuruteraan Elektronik & Kejuruteraan Komputer (FKEKK), Universiti Teknikal Malaysia Melaka (UTeM), Durian Tunggal, Malaysia
| | - Chee Kiang Lam
- School of Mechatronic Engineering, Universiti Malaysia Perlis (UniMAP), 02600, Arau, Perlis, Malaysia
| | - Jawad Hussain
- Centre for Telecommunication Research and Innovation (CeTRI), Fakulti Kejuruteraan Elektronik & Kejuruteraan Komputer (FKEKK), Universiti Teknikal Malaysia Melaka (UTeM), Durian Tunggal, Malaysia
| | - Md Asraf Ali
- Daffodil International University, Dhaka, Bangladesh
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Isezaki T, Watanabe T, Yamada T, Kadone H, Suzuki K. Estimating the lower leg muscle activity from distal biosignals around the ankles. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2017; 2017:4102-4105. [PMID: 29060799 DOI: 10.1109/embc.2017.8037758] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/07/2023]
Abstract
Electromyogram signals (EMG) can be used not only to measure motions, but also to control devices such as exoskeleton robots. Sensor electrodes need to be placed on each muscle based on kinematics and anatomical characteristics. Wearable EMG measurement approach is also investigated in recent years. Electrodes are fixed to the clothes. In this paper, we propose a motion measurement method based on propagation characteristics of biopotential signal. An experiment with walking and plantar flexion motion as tasks. The results showed that the signals calculated from proposed method were comparable with that of conventional method. We confirmed that there were few individual differences for calculating the signals of tibialis anterior, gastrocnemius and peroneal muscles.
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