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Hearing loss may disqualify many people from leading a normal life, though the majority do not make use of hearing aids. This is because most hearing aids on the market cannot automatically adapt to the changing acoustical environment the user faces daily. This paper focuses on the development of an automatic sound classifier for digital hearing aids that(More)
Determining the stress level of a subject in real time could be of special interest in certain professional activities to allow the monitoring of soldiers, pilots, emergency personnel and other professionals responsible for human lives. Assessment of current mental fitness for executing a task at hand might avoid unnecessary risks. To obtain this knowledge,(More)
Recommended by Hugo Fastl The feasible implementation of signal processing techniques on hearing aids is constrained by the finite precision required to represent numbers and by the limited number of instructions per second to implement the algorithms on the digital signal processor the hearing aid is based on. This adversely limits the design of a neural(More)
This paper centers on exploring proper training algorithms for multilayer perceptrons (MLPs) to be used within digital hearing aids. One argument usually considered against the feasibility of neural networks on hearing aids consists in both their computational complexity and the hardware constraints the hearing aids suffer from. Within this framework, this(More)
The overall aim of our research is to develop methods for a monitoring system to be used at neonatal intensive care units. When monitoring a baby, a range of different types of background activity needs to be considered. In this work, we have developed a scheme for automatic classification of background EEG activity in newborn babies. EEG from six full-term(More)