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Updated: Apr 11, 2026
Study Design for Navigated Repetitive Transcranial Magnetic Stimulation for Speech Cortical Mapping
Published on: March 24, 2023
Accelerometer-based automatic voice onset detection in speech mapping with navigated repetitive transcranial magnetic
Anne-Mari Vitikainen1, Elina Mäkelä2, Pantelis Lioumis3
1BioMag Laboratory, HUS Medical Imaging Center, University of Helsinki and Helsinki University Hospital, P.O. Box 340, FI-00029 HUS, Helsinki, Finland; Department of Physics, University of Helsinki, P.O. Box 64, FI-00014 University of Helsinki, Helsinki, Finland.
This study introduces an accelerometer-based system for detecting voice onsets during navigated repetitive transcranial magnetic stimulation (rTMS) speech mapping. The new method enhances the reliability and repeatability of rTMS results in preoperative planning.
Area of Science:
- Neuroscience
- Medical Engineering
- Speech Science
Background:
- Navigated repetitive transcranial magnetic stimulation (rTMS) is valuable for preoperative mapping of speech areas in epilepsy and tumor patients.
- Current rTMS speech mapping lacks quantitative monitoring, leading to variability and poor replicability.
- Existing methods for motor cortex mapping use electromyography, but a similar setup for speech mapping is unavailable.
Purpose of the Study:
- To develop and evaluate an accelerometer-based setup for objective voice onset detection in rTMS speech mapping.
- To improve the reliability, repeatability, and stratification of rTMS results for preoperative planning.
Main Methods:
- An accelerometer setup was developed to detect larynx vibrations associated with vocalization.
- An automatic routine for voice onset detection was created for rTMS speech mapping during naming tasks.
- The automatic routine's performance was compared against manual review of video recordings.
Main Results:
- The new method was applied to 12 patients undergoing preoperative workup for epilepsy or tumor surgery.
- The automatic routine achieved 96% sensitivity and 71% specificity in detecting voice onsets.
- Misdetections (37%) were primarily due to throat movements, pre-response vocalizations, or delayed naming; 88% of no-response errors were correctly identified.
Conclusions:
- The proposed accelerometer-based setup provides quantitative data for analyzing rTMS-induced speech responses.
- Objective voice onset detection and defined speech response latencies enhance the repeatability and reliability of rTMS outcomes.
- This technology offers a more robust approach to rTMS speech mapping for improved clinical application.
