Interpretation of psychophysical data from impaired-hearing individuals on intensity discrimination tasks has been confounded by the fact that some impaired individuals' performance is near-normal in quiet, whereas for others, the difference limen is elevated. It has been observed that a subject's discrimination abilities may be related to the underlying audiogram configuration, which is often dependent on the type of physiological damage that has occurred. This suggests that data be grouped and analyzed according to the type of hearing loss. An experimental study by Schroder et al. (1994) tested the hypothesis that the near-normal performance of some impaired subjects was the result of a normal spread of excitation, rather than greater intensity resolution due to loudness recruitment. In this paper, we replicate the trends observed in Schroder et al.'s experimental data using a combination of signal detection theory and a computational auditory model. By linking simulated psychophysical predictions with the corresponding simulated physiological responses, this theoretical analysis provides further qualitative support for the hypothesis that the observed performance is due to the spread of excitation.

Signal processing algorithms for hand-held mine detection sensors are described. The goals of the algorithms are to provide alarms to a human operator indicating the likelihood of the presence of a buried mine. Two modes of operations are considered: search mode and discrimination mode. Search mode generates an initial detection at a suspected location and discrimination mode confirms that the suspected location contains a land mine. Search mode requires that the signal processing algorithm generate a detection confidence value immediately at the current sample location and no delay in producing an alarm confidence is tolerable. Search mode detection has a high false-alarm rate. Discrimination mode allows the operator to interrogate the entire suspected location to eliminate false alarms. It does not require that the signal processing algorithm produce an alarm confidence immediately for the current sample location, but rather allows the system to process all the data acquired over the region before producing an alarm. This paper proposes discrimination mode processing algorithms for metal detectors (MDs), or electromagnetic induction sensors (EMIs), ground-penetrating radars (GPRs), and their fusion. The MD discrimination mode algorithm employs a model-based approach and uses the target model parameters to discriminate between mines and clutter objects. The GPR discrimination mode algorithm uses the consistency of detection as well as the shape of the detection peaks over several sweeps to improve the discrimination accuracy. The performances of the proposed algorithms were examined on a dataset collected at a government test site, and performance was compared with baseline techniques. Experimental results showed that the proposed method can reduce the probability of false alarm by as much as 70% at a 100% correct detection rate and performed comparable to the best human operator on a blind test with data collected at approximately 1000 locations.

The effect of cochlear hearing loss on intensity discrimination has been experimentally investigated and reported in the literature. It has been observed that the impairment configuration has a significant effect on a subject's discrimination abilities. In some cases, intensity discrimination for an impaired individual is near-normal at equal SPLs, whereas in other cases, the difference limen is elevated. It has been hypothesized that the near-normal performance of some impaired individuals may be due to either greater intensity resolution (resulting from loudness recruitment) or to the normal spread of excitation. In this paper, we simulate an experiment conducted by Schroder et al. (1994) devised to test these hypotheses. Using a signal detection theory-based approach in combination with a computational auditory model, we are able to replicate their experimental results. Additionally, by manipulating the model, we are able to demonstrate theoretically that the observed behavior results from the spread of excitation.

We have investigated the differences between normal and impaired auditory processing for a frequency discrimination task by analyzing the responses of a computational auditory model using signal detection theory. Two detectors, one using all of the information in the signal, the other using only the number of neural responses, were implemented. An evaluation of the performance differences between the two theoretical detectors and experimental data may provide insight into quantifying the type of information present in the auditory system as well as whether the human auditory system uses this information efficiently. Results support previous hypotheses that, for lowand mid-range frequencies, the auditory system is able to use temporal information to perform frequency discrimination (see Moore, B.C.J., J. Acoust. Soc. Am., vol.54, p.610-19, 1973). The results also suggest that some temporal information is represented in the neural spike train, even at high frequencies However, the ability of the auditory system to use this information deteriorates at higher frequencies.