Abstract: There are approximately 45 million blind & visually impaired people world-wide according to the World Health Report. Vision loss limits the access of these individuals to the educational opportunities, social events, public transportation and leads to a higher rate of unemployment.
Many efforts have been invested in the last years, based on sensor technology and signal processing, to develop electronic travel aids (ETA) capable to improve the mobility of blind users in unknown or dynamically changing environment. In spite of these efforts, the already proposed ETAs do not meet the requirements of the blind community and the traditional tools (white cane and guiding dogs) are still the only used by visually impaired to navigate in their working and living environment.
In this paper, research efforts to improve the main two components of an ETA tool: the Obstacles Detection System (ODS) and the Man-machine Interface (MMI) are presented. Now, for the first time, the ODS under development is bioinspired from the visual system of insects, particularly from the Lobula Giant Motion Detector (LGMD) found in locusts. LGMD is a large neuron found in optical lobule of the locust, which mainly responds at the approaching objects. Starting from the mathematical model of the LGMD, known in the literature, it has been developed an ODS that can be used by visually impaired to navigate autonomously with obstacles avoidance. The already obtained results are very promising, but some improvements are also possible. We are developing now preprocessing algorithms for the visual information applied to the input of the LGMD neuron, in order to improve the response of the ODS. In the proposed solution, the position of the detected obstacles is correlated with the attitude parameters of the subject's head. In this way, the visually impaired person detects obstacles in a similar way as a subject with normal sight is looking for obstacles in front of him.
The man-machine interface developed in the present research exploits the remarkable abilities of the human hearing system in identifying sound source positions in 3D space. The proposed solution relies on the Acoustic Virtual Reality (AVR) concept, which can be considered as a substitute for the lost sight of blind and visually impaired individuals. According to the AVR concept, the presence of obstacles in the surrounding environment and the path to the target will be signalized to the subject by burst of sounds, whose virtual source position suggests the position of the real obstacles and the direction of movement, respectively. The practical implementation of this method encounters some difficulties due to the Head Related Transfer Functions (HRTF) which should be known for each individual and for a limited number of points in the 3D space. These functions can be determined using a quite complex procedure, which requires many experimental measurements. The proposed solution in our research avoids these difficulties by generating the HRTF's coefficients using an Artificial Neural Network (ANN). The ANN has been trained using a public data base, available for the whole scientific community and which contains HRTF's coefficients for a limited number of individuals and a limited number of points in 3D space for each individual.
The ODS and the MMI presented in the above have been implemented on a specific hardware build around an ARM-based microcontroller system. The obtained results and some conclusions are also presented.

Brief Biography of the Speaker:
Prof. Virgil TIPONUT received the M.Sc. in 1968, in Electrical Engineering/Computer Science, and the Ph.D. degree in Electronic Engineering and Telecommunications, in 1981, both at the POLITEHNICA University of Timisoara, Romania. Since graduation he is with POLITEHNICA University of Timisoara and curently he is a professor at Electronic and Telecommunication Faculty, responsable for teaching in embedded systems, smart transducers and neural networks.
His research interests include bioinspired systems, with application in mobile and rehabilitation robotics and some closed related areas: smart transducers, neural networks and fuzzy logic, biomedical engineering, embedded systems. He has published more than 100 papers in national and international Journals and Conference Proceedings, authored 10 books and 10 text books, and holds 21 patents. He conducted more than 25 research and development projects, grants and contracts in the field of embedded systems, robotics and smart transducers.
Prof. Tiponut has been involved in setting up national and international conferences as a reviewer and/or member of organizing committee or board of sections. He was a visiting professor at universities from USA, Germany, Ireland and Schotland.
He is a member of the IEEE Society (CAS, EMB, RA), WSEAS Society, member of the Society of Electronic Engineers from Romania and corresponding member of the Academy of Technical Science from Romania.