Effects of Recording Condition and Number of Monitored Days on the Discriminative Power of the Daily Phonotrauma Index.

Abstract

Purpose: The Daily Phonotrauma Index (DPI) can quantify pathophysiological mechanisms associated with daily voice use in individuals with phonotraumatic vocal hyperfunction (PVH). Since DPI was developed based on weeklong ambulatory voice monitoring, this study investigated if DPI can achieve comparable performance using (a) short laboratory speech tasks and (b) fewer than 7 days of ambulatory data.

Method: An ambulatory voice monitoring system recorded the vocal function/behavior of 134 females with PVH and vocally healthy matched controls in two different conditions. In the laboratory, the participants read the first paragraph of the Rainbow Passage and produced spontaneous speech (in-lab data). They were then monitored for 7 days (in-field data). Separate DPI models were trained from the in-lab and in-field data using the standard deviation of the difference between the magnitude of the first two harmonics (H1-H2) and the skewness of neck-surface acceleration magnitude. First, 10-fold cross-validation evaluated the classification performance of the in-lab and in-field DPIs. Second, the effect of the number of ambulatory monitoring days on the accuracy of in-field DPI classification was quantified.

Results: The average in-lab DPI accuracy computed from the Rainbow Passage and spontaneous speech were 57.9% and 48.9%, respectively, which are close to chance performance. The average classification accuracy of the in-field DPI was significantly higher with a very large effect size (73.4%, Cohen's d = 1.8). Next, the average in-field DPI accuracy increased from 66.5% for 1 day to 75.0% for 7 days, with the gain of including an additional day on accuracy dropping below 1 percentage point after 4 days.

Conclusions: The DPI requires ambulatory monitoring data as its discriminative power diminished significantly once computed from short in-lab recordings. Additionally, ambulatory monitoring should sample multiple days to achieve robust performance. The result of this research note can be used to make an informed decision about the trade-off between classification accuracy and cost of data collection.