Download presentation
Presentation is loading. Please wait.
Published byCarissa Thedford Modified over 9 years ago
1
A man-machine human interface for a special device of the pervasive computing world B. Apolloni, S. Bassis, A. Brega, S. Gaito, D. Malchiodi, A.M. Zanaboni DSI - University of Milano (I)
2
Outline A procedure detecting attention states in car driving Fed by biologic input supplied through non invasive sensors Explains its output through a possibly interpretable rule
3
The data One subject using a car driver simulator Subjected to alternate attention demanding manoeuvres (fast lane exchange, pedestrian avoidance) and relaxed driving 4 signals traced by a Biopac device (SKT, GSR, ECG, RSP) Collected by the School of Psychology, Queen’s University Belfast.
4
Preprocessing Extracted features 8 conventional (from medical knowledge) FFT processing for ECG Drift of the ECG signal from a neural prediction SKT not considered (constant)
5
Feature processing I 15 Boolean values are extracted from a time-window of width 3 t-1t+1t Result of a Boolean ICA through minimization of empirical entropy 253 connections (after pruning)
6
Feature processing II Boolean values interpreted as propositional variables Minimal DNF and DNF on variables interpreted as symbolic wavelets Begin DNF= ø ; for each positive example u ; DNF = DNF {m} ; return DNF; End
7
An obtained CNF (x1+x3+x6+x8+x10+x14)(x1+x2+x5+x6+x7+x9+x11+x12+x13)(x1+x2+x6+x7+x9+x10+x12+ x14)(x1+x2+x5+x7+x8+x12+x13+x15)(x1+x3+x5+x11+x13+x15)(x3+x8+x10+x11+x13+x14+ x15)(x1+x2+x4+x6+x7+x11+x12+x13+x14+x15)(x1+x2+x4+x8+x12+x13+x14+x15)(x1+x2+x 3+x7+x8+x10+x13+x14+x15)(x3+x4+x8+x10+x13+x14+x15)(x1+x3+x6+x7+x8+x13+x14)(x3 +x5+x7+x8+x13)(x2+x3+x6+x7+x10+x11+x12+x13+x14)(x1+x5+x6+x8+x9+x11+x12+x15)(x 1+x5+x6+x8+x9+x11+x14+x15)(x3+x5+x7+x9+x10+x11)(x1+x3+x4+x7+x13+x14+x15)(x1+x 2+x3+x8+x11+x13+x14+x15)(x2+x5+x6+x7+x9+x11+x12+x15)(x2+x3+x4+x6+x9+x10+x11+ x12+x14)(x2+x4+x5+x7+x8+x13+x15)(x3+x4+x6+x7+x10+x13)(x3+x4+x6+x8+x10+x14)(x1+ x4+x7+x8+x13+x15)(x1+x4+x5+x7+x8+x9+x15)(x4+x7+x8+x10+x15)(x4+x7+x8+x10+x14)(x 2+x4+x5+x6+x7+x9+x10+x12+x13+x15)(x1+x3+x5+x8+x13+x15)(x1+x3+x6+x9+x10+x11+x 14)(x1+x6+x9+x10+x11+x12+x14)(x1+x6+x8+x9+x11+x12+x14)(x1+x2+x4+x6+x7+x10+x11 +x12+x13+x14)(x2+x4+x5+x8+x9+x10+x12+x13+x15)(x2+x4+x5+x7+x9+x10+x11+x12)(x1+ x3+x6+x7+x8+x10+x13)(x3+x4+x5+x6+x8+x9+x10+x11)(x2+x5+x6+x8+x9+x10+x11+x12)(x 2+x5+x6+x7+x8+x9+x11+x12)(x1+x2+x4+x5+x6+x7+x9+x12+x13)(x3+x4+x5+x7+x10+x11)( x1+x2+x5+x8+x10+x12+x13+x15)(x1+x2+x6+x7+x9+x10+x11)(x1+x2+x5+x7+x8+x9+x14)(x 3+x4+x5+x8+x9+x10+x13+x15)(x3+x8+x9+x10+x11+x13)(x3+x9+x10+x11+x13+x14)(x1+x6 +x7+x8+x9+x10+x12)(x1+x2+x3+x6+x11+x13+x14+x15)(x2+x4+x5+x6+x9+x11+x12+x14+x 15)(x2+x6+x7+x10+x11+x12+x13+x15)(x2+x4+x6+x10+x11+x12+x14+x15)(x2+x5+x6+x9+x 10+x11+x12+x14+x15)(x3+x4+x6+x8+x11+x14+x15)
8
Post processing Simplification of the learnt rules through stochastic optimization of the cost L: rule length, :rule radius, :disregarded points
9
A simplified CNF (x6+x11+x1+x13)(x10+x12+x9+x6)(x1+x13+x11+x5)(x3+x8+x6)(x4+x1+x13)(x12+x6+x 7+x13)(x13+x8+x9+x4)(x1+x6+x8)(x12+x6+x7+x8)(x1+x8+x5+x7)(x4+x6+x7+x13)(x7+ x9+x10+x11+x3)(x1+x8+x13+x15)(x3+x8+x13+x15)(x4+x7+x8)(x1+x6+x9+x10+x11)(x2 +x6+x11+x12+x15)(x3+x5+x8+x13)(x4+x5+x7+x10+x11)(x3+x9+x10+x11+x13) From 403 to 81 literals
10
Performance I DNFCNF LengthFPFNLengthFPFN AVG44.4222.9127.6271.0622.4128.22 STDV7.355.368.7920.377.495.44 50 cross-validation test FP: false positives; FN: false negatives
11
Performance II LengthTPFPFN DNF44.4272.3822.9127.62 LengthTNFNFPCNF71.0671.7822.4228.22
12
Performance III
Similar presentations
© 2025 SlidePlayer.com. Inc.
All rights reserved.