Neuromechanical Modelling of Articulatory Movements from Surface Electromyography and Speech Formants
| Authors | |
|---|---|
| Year of publication | 2019 |
| Type | Article in Periodical |
| Magazine / Source | INTERNATIONAL JOURNAL OF NEURAL SYSTEMS |
| MU Faculty or unit | |
| Citation | |
| Web | https://www.worldscientific.com/doi/abs/10.1142/S0129065718500399 |
| Doi | http://dx.doi.org/10.1142/S0129065718500399 |
| Keywords | Speech neuromotor activity; facial myoelectric activity; dysfluency; dysarthria; Parkinson's Disease |
| Description | Speech articulation is produced by the movements of muscles in the larynx, pharynx, mouth and face. Therefore speech shows acoustic features as formants which are directly related with neuromotor actions of these muscles. The first two formants are strongly related with jaw and tongue muscular activity. Speech can be used as a simple and ubiquitous signal, easy to record and process, either locally or on e-Health platforms. This fact may open a wide set of applications in the study of functional grading and monitoring neurodegenerative diseases. A relevant question, in this sense, is how far speech correlates and neuromotor actions are related. This preliminary study is intended to find answers to this question by using surface electromyographic recordings on the masseter and the acoustic kinematics related with the first formant. It is shown in the study that relevant correlations can be found among the surface electromyographic activity (dynamic muscle behavior) and the positions and first derivatives of the first formant (kinematic variables related to vertical velocity and acceleration of the joint jaw and tongue biomechanical system). As an application example, it is shown that the probability density function associated to these kinematic variables is more sensitive than classical features as Vowel Space Area (VSA) or Formant Centralization Ratio (FCR) in characterizing neuromotor degeneration in Parkinson's Disease. |
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