A Pilot Study for a Novel and Personalized Voice Restoration Device for Patients With Laryngectomy
Weill Medical College of Cornell University
Summary
The investigators will conduct a pilot experiment for a novel and personalized method for voice restoration using machine learning applied to surface EMG (sEMG) signal from articulatory muscles of the face and the neck allowing recognition of silent speech. The investigators predict that the use novel personalized method for voice restoration will be feasible and successful for patients.
Description
This is a prospective pilot study evaluating the feasibility of a personalized voice restoration device and patients' experience with it. Study participation will include a one-time visit where subjects will read passages and phrases. Acoustic and signal data will be captured. Machine learning will be applied to the data to classify words. Subjects will also participate in a qualitative interview about their experience with voice restoration devices.
Eligibility
- Age range
- 18–110 years
- Sex
- All
- Healthy volunteers
- Yes
Inclusion Criteria: Group A: Healthy Volunteers 1. Adult subjects, 18 or older 2. Without any voice impairments Group B: Subjects with Aphonia or Dysphonia 1. Adult subjects, 18 or older 2. Documentation of severe dysphonia and/or aphonia, or a GRBAS score \> 0 (GRBAS is a scale that can be used to assess voice quality of subjects who do not have a recorded history of dysphonia or aphonia. The GRBAS scale evaluates for grade, roughness, breathiness, asthenia, and strain). Exclusion Criteria: \- Group A: Healthy Volunteers 1\. Voice impairment Group B: Subjects with Aphonia or Dysphonia…
Interventions
- DeviceSurface Electromyography
Surface ElectroMyoGraphy (SEMG) is a non-invasive technique for measuring muscle electrical activity that occurs during muscle contraction and relaxation cycles. Electrodes will be attached with a AgCl gel to muscles used for articulation.
Location
- Weill Cornell MedicineNew York, New York