1. Presenter: Prof.Dr.-Eng. Gheorghe-Daniel Andreescu
Automation and Applied Informatics
Modelling and Simulation of Hearing with Cochlear Implants: A Proposed Method for Better Auralization A.M. Kuczapski, G.-D. Andreescu
Artur Kuczapski
Am absolvit faculatatea de AC in 2005,
SOFA 2014
Presenter: Prof.Dr.-Eng. Gheorghe-Daniel Andreescu

2. Content Natural Hearing Cochlear Implant Existing Auralization Methods
Proposed Auralization Method
Auditory Model
Nerve Impulse Patterns

3. Natural Hearing

4. Cochlear Implant Electrically stimulated hearing nerves
Sound is converted to stimulation patterns (coding strategy)
Place coding
Rate coding

5. Auralization
Synthetize sound from electric stimulation patterns reproducing the patient’s hearing experience
Motivation
Compare hearing quality with existing sound coding strategies
Test bench for development of new coding strategies
Improve fitting procedures
Help speech therapists to understand hearing through CI
Important Factors
Stimulation strategy,
electrode – nerve interface,
nerve impulse pattern to sound mapping

6. Auralization method based on channel envelope detection
*Dr. Qian-Jie Fu - AngelSIM/TigerCIS software

7. Auralization method based on channel envelope and frequency detection
*Hartzos et al. – Frauenhoffer Institute

8. Proposed auralization concept - Neural firing pattern recognition -

9. Proposed auralization method
Basilar Membrane Model
IHC Model
Sound
Synapse model
Artificial neural network
FFT CI
Coding strategy
Cochlea current flow/conductivity model
Sunet

10. Auditory Model (Simplified)

11. Polarization patterns of inner hair cells - Natural Hearing -
300Hz
600Hz
Dbasal
8000Hz
mix t

12. Polarization patterns of inner hair cells - Natural Hearing -
Sound
Low Fq.
0.3 KHz
0.6 KHz
Dbasal
8 KHz
High Fq.
XBM
Time
Basilar membrane displacement
IHC Membrane potential

13. Auditory Nerve Impulse - Natural Hearing -
IHC Potentials
Dbasal t

14. Neural firing pattern recognition Concept
Neural network

15. Conclusions Motivation Existing auralization approaches
Compare hearing quality with existing sound coding strategies
Test bench for development of new coding strategies
Improve fitting procedures
Help speech therapists to understand hearing through CI
Existing auralization approaches
Typically consider place coding only (spatial cue)
Rate coding information is considered seldom (temporal cue)
Learning and adaptation is not considered at all

16. Conclusions
Both learning abilities and temporal cues are important for hearing
Neural firing patterns can be treated as images and interpreted using artificial networks
Natural hearing model is necessary for initial training of the artificial neural network
Proposed model considers:
Place coding (spatial cues)
Rate coding (temporal cues)
Learning and adaptation
Intra cochlear current spread
Neural fiber model
The proposed model is independent of the analyzed coding strategy
Before adaptation hearing experience
After adaptation hearing experience

17. Thank You

18. Stimulation patterns (1)
Source: Harczos et al. [HCH12]
ACE
SAM

19. Stimulation patterns (3)