Dataset Information

Machine-Learning-Based Detecting of Eyelid Closure and Smiling Using Surface Electromyography of Auricular Muscles in Patients with Postparalytic Facial Synkinesis: A Feasibility Study.

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.

SUBMITTER: Hochreiter J

PROVIDER: S-EPMC9914547 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Machine-Learning-Based Detecting of Eyelid Closure and Smiling Using Surface Electromyography of Auricular Muscles in Patients with Postparalytic Facial Synkinesis: A Feasibility Study.

Hochreiter Jakob J Hoche Eric E Janik Luisa L Volk Gerd Fabian GF Leistritz Lutz L Anders Christoph C Guntinas-Lichius Orlando O

Diagnostics (Basel, Switzerland) 20230202 3

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 (1 ...[more]

PMID: 36766657

Similar Datasets

Project description:Background: There is no current standard for facial synkinesis rehabilitation programs. The benefit and stability of effect of an intensified 10-day facial training combining electromyography and visual biofeedback training was evaluated. Methods: Fifty-four patients (77.8% female; median age: 49.5 years) with post-paralytic facial synkinesis (median time to onset of paralysis: 31.1 months) were included in retrospective longitudinal study between January 2013 and June 2016. Facial function was assesses at baseline (T0), first days of training (T1), last day of training (T2), and follow-up visit (T3) at a median time of 6 months later using the House-Brackmann (HB) facial nerve grading system, Stennert index (SI), Facial Nerve Grading System 2.0 (FNGS 2.0), and Sunnybrook Facial Grading System (SFGS). Pairwise comparisons between the time points with post-hoc Bonferroni correction were performed. Results: No significant changes of the gradings and subscores were seen between T0 and T1 (all p > 0.01). The 10-day combined and intensified feedback training between T1 and T2 improved facial symmetry and decreased synkinetic activity. Facial grading with the FNGS 2.0 or the SFGS were most suited to depict the training effect. FNGS 2.0, regional score, FNGS 2.0, synkinesis score, and FNGS 2.0 total score improved significantly (all p ≤ 0.0001). Both, the FNGS 2.0 and the SFGS showed the strongest improvement in the nasolabial fold/zygomatic and the oral region. Neither the age of the patient (r = 0.168; p = 0.224), the gender (r = 0.126; p = 0.363) nor the length of the interval between onset of the palsy and training start (r = 0.011; p = 0.886) correlated with the changes of the SFGS between T1 and T2. The results remained stable between T2 and T3 without any further significant change. Conclusion: Intensified daily combined electromyography and visual biofeedback training over 10 days was effective in patients with facial synkinesis and benefits were stable 6 months after therapy.

Project description:BackgroundSpinal cord injury (SCI) can lead to severe and permanent functional deficits. In humans, peri-auricular muscles (PAMs) do not serve any physiological function, though their innervation is preserved in even high level SCI. Auricular control systems provide a good example of leveraging contemporary technologies (e.g., sEMG controlled computer games) to enable those with disabilities. Our primary objective is to develop and test the effectiveness of an auricular muscle training protocol to facilitate isolated and coordinated, bilateral voluntary control that could be used in individuals without volitional control of the vestigial PAMs.MethodsSeventeen non-disabled persons were screened; 13 were eligible and 10 completed the entire protocol. The facilitation phase, included one session of sub-motor threshold, sensory electrical stimulation followed by neuromuscular electrical stimulation paired with ear movement feedback for up to 8 additional sessions. Participants progressed to the skill acquisition phase where they dawned an auricular control device that used sEMG signals to control movements of a cursor through three levels of computer games, each requiring increasingly more complex PAM coordination.ResultsThe 10 who completed the protocol, finished the facilitation phase in 3 to 9 sessions and achieved some level of voluntary auricle movement that ranged between 1 and 5 mm. Qualitative analysis of longitudinal post-session auricular movement, revealed two subgroups of learners. Six successfully completed all 3 games-the "Learners". Two were partially successful in game completion and two were unable to complete a single game--"Poor/Non-Learners". Quantitative analysis revealed a significant group difference in auricular amplitude for both facilitation and skill phases (p < .05), and a significant relationship between performance in the two phases (R2 = 0.84, p = 0.004).ConclusionSixty percent of those who completed the facilitation phase were able to learn and demonstrate functional voluntary control of the vestigial PAMs. Those who progressed the fastest through facilitation were also those who were most proficient in skill acquisition with the device. There was considerable variability in progression through the two-phase protocol, with 20% deemed Poor/Non-Learners and unable to complete even the most basic game following training. There were no serious adverse events.Trial registrationClinicalTrials.gov Identifier: NCT02358915 , first posted February 9, 2015.

Dataset Information

Machine-Learning-Based Detecting of Eyelid Closure and Smiling Using Surface Electromyography of Auricular Muscles in Patients with Postparalytic Facial Synkinesis: A Feasibility Study.

Publications

Machine-Learning-Based Detecting of Eyelid Closure and Smiling Using Surface Electromyography of Auricular Muscles in Patients with Postparalytic Facial Synkinesis: A Feasibility Study.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets