Literature Review - 3

 Here I just wrap-up, in a table, the different machine learning algorithms used in some papers I read. I selected only the experiments relatively closed to ours and where the machine learning analysis was described. 

Table

Notation

ANN: Artificial Neural Network

BN: Bayesian Network

FP: False Positive (rate)

GMM: Gaussian Mixture Models

GP: Gaussian Process
KNN: K Nearest Neighbors
HMM: Hidden Markov Model
SVM: Support Vector Machine
TP: True Positive (rate)

References

[1] Analysis and detection of cognitive load and frustration in drivers’ speech, H. Bořil, S. O. Sadjadi, T. Kleinschmidt, J. H. L. Hansen

[2] Analysis of real-world driver’s frustration, L. Malta, C. Miyajima, N. Kitaoka, K. Takeda

[3] Automatic prediction of frustration, A. Kapoor, W. Burleson, R. W. Picard, 2006

[4] Affective Intelligent Car Interfaces with Emotion Recognition, C. L. Lisetti, F.Nasoz, 2005

[5] Sitting posture analysis by pressure sensors, K. Kamiya, M. Kudo, H. Nonaka, J. Toyama

[6] Automated Posture Analysis for Detecting Learner’s Interest Level, S. Mota, R. W. Picard