1. Objectives
Vocal characteristics are commonly considered as an important factor in determining the Sasang constitution and the health condition. We have tried to find out the classification procedure to distinguish the constitution objectively and quantitatively by analyzing the characteristics of subject’s voice without noise and error.
2. Methods
In this study, we extract the vocal features from voice selected with prior information, remove outliers, minimize the correlated features, correct the features with normalization according to gender and age, and make the discriminant functions that are adaptive to gender and age from the features for improving diagnostic accuracy.
3. Results
Finally, the discriminant functions produced about 45% accuracy to classify the constitution for every age interval and every gender, and the diagnostic accuracy was meaningful as the result from only the voice.
4. Conclusions
We needed to find out more effective vocal features for the classification, and thus suggested the discriminant method to distinguish the health condition as well as the constitution. Especially, the voice analysis method can play a critical and essential role, leading to the system for u-Healthcare and a smart phone. |
