Automated Analysis of the Auditory Brainstem Response Using Derivative Estimation Wavelets

In this paper, we describe an algorithm that automatically detects and labels peaks I - VII of the normal, suprathreshold auditory brainstem response (ABR). The algorithm proceeds in three stages, with the option of a fourth: ( 1) all candidate peaks and troughs in the ABR waveform are identified using zero crossings of the first derivative, ( 2) peaks I - VII are identified from these candidate peaks based on their latency and morphology, ( 3) if required, peaks II and IV are identified as points of inflection using zero crossings of the second derivative and ( 4) interpeak troughs are identified before peak latencies and amplitudes are measured. The performance of the algorithm was estimated on a set of 240 normal ABR waveforms recorded using a stimulus intensity of 90 dBnHL. When compared to an expert audiologist, the algorithm correctly identified the major ABR peaks ( I, III and V) in 96 - 98% of the waveforms and the minor ABR peaks ( II, IV, VI and VII) in 45 - 83% of waveforms. Whilst peak II was correctly identified in only 83% and peak IV in 77% of waveforms, it was shown that 5% of the peak II identifications and 31% of the peak IV identifications came as a direct result of allowing these peaks to be found as points of inflection. Copyright (C) 2005 S. Karger AG, Basel.

Remotely sensed data for ecosystem analyses: Combining hierarchy and scene models

Remotely sensed data have been used extensively for environmental monitoring and modeling at a number of spatial scales; however, a limited range of satellite imaging systems often. constrained the scales of these analyses. A wider variety of data sets is now available, allowing image data to be selected to match the scale of environmental structure(s) or process(es) being examined. A framework is presented for use by environmental scientists and managers, enabling their spatial data collection needs to be linked to a suitable form of remotely sensed data. A six-step approach is used, combining image spatial analysis and scaling tools, within the context of hierarchy theory. The main steps involved are: (1) identification of information requirements for the monitoring or management problem; (2) development of ideal image dimensions (scene model), (3) exploratory analysis of existing remotely sensed data using scaling techniques, (4) selection and evaluation of suitable remotely sensed data based on the scene model, (5) selection of suitable spatial analytic techniques to meet information requirements, and (6) cost-benefit analysis. Results from a case study show that the framework provided an objective mechanism to identify relevant aspects of the monitoring problem and environmental characteristics for selecting remotely sensed data and analysis techniques.

The relationship between the auditory brain-stem response and its reconstructed waveforms following discrete wavelet transformation

Objective: To examine the relationship between the auditory brain-stem response (ABR) and its reconstructed waveforms following discrete wavelet transformation (DWT), and to comment on the resulting implications for ABR DWT time-frequency analysis. Methods: ABR waveforms were recorded from 120 normal hearing subjects at 90, 70, 50, 30, 10 and 0 dBnHL, decomposed using a 6 level discrete wavelet transformation (DWT), and reconstructed at individual wavelet scales (frequency ranges) A6, D6, D5 and D4. These waveforms were then compared for general correlations, and for patterns of change due to stimulus level, and subject age, gender and test ear. Results: The reconstructed ABR DWT waveforms showed 3 primary components: a large-amplitude waveform in the low-frequency A6 scale (0-266.6 Hz) with its single peak corresponding in latency with ABR waves III and V; a mid-amplitude waveform in the mid-frequency D6 scale (266.6-533.3 Hz) with its first 5 waves corresponding in latency to ABR waves 1, 111, V, VI and VII; and a small-amplitude, multiple-peaked waveform in the high-frequency D5 scale (533.3-1066.6 Hz) with its first 7 waves corresponding in latency to ABR waves 1, 11, 111, IV, V, VI and VII. Comparisons between ABR waves 1, 111 and V and their corresponding reconstructed ABR DWT waves showed strong correlations and similar, reliable, and statistically robust changes due to stimulus level and subject age, gender and test ear groupings. Limiting these findings, however, was the unexplained absence of a small number (2%, or 117/6720) of reconstructed ABR DWT waves, despite their corresponding ABR waves being present. Conclusions: Reconstructed ABR DWT waveforms can be used as valid time-frequency representations of the normal ABR, but with some limitations. In particular, the unexplained absence of a small number of reconstructed ABR DWT waves in some subjects, probably resulting from 'shift invariance' inherent to the DWT process, needs to be addressed. Significance: This is the first report of the relationship between the ABR and its reconstructed ABR DWT waveforms in a large normative sample. (C) 2004 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

On the dual structure of the auditory brainstem response in dogs

Objective: To use the over-complete discrete wavelet transform (OCDWT) to further examine the dual structure of auditory brainstem response (ABR) in the dog. Methods: ABR waveforms recorded from 20 adult dogs at supra-threshold (90 and 70 dBnHL) and threshold (0-15 dBSL) levels were decomposed using a six level OCDWT and reconstructed at individual scales (frequency ranges) A6 (0-391 Hz), D6 (391-781 Hz), and D5 (781-1563 Hz). Results: At supra-threshold stimulus levels, the A6 scale (0-391 Hz) showed a large amplitude waveform with its prominent wave corresponding in latency with ABR waves II/III; the D6 scale (391-781 Hz) showed a small amplitude waveform with its first four waves corresponding in latency to ABR waves I, II/III, V, and VI; and the D5 scale (781-1563 Hz) showed a large amplitude, multiple peaked waveform with its first six waves corresponding in latency to ABR waves I, II, III, IV, V, and VI. At threshold stimulus levels (0-15 dBSL), the A6 scale (0-391 Hz) continued to show a relatively large amplitude waveform, but both the D6 and D5 scales (391781 and 781-1563 Hz, respectively) now showed relatively small amplitude waveforms. Conclusions: A dual structure exists within the ABR of the dog, but its relative structure changes with stimulus level. Significance: The ABR in the dog differs from that in the human both in the relative contributions made by its different frequency components, and the way these components change with stimulus level. (c) 2006 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Development of a measure to assess coping for auditory hallucinations

This paper describes the development of an instrument to assess coping strategies for auditory hallucinations. An inventory of coping strategies was obtained by conducting semi-structured interviews with 17 male participants. This inventory was then used to develop a 27-item questionnaire, the Responses to Auditory Hallucinations Questionnaire (RAHQ). The RAHQ was administered to 125 respondents. Measures of symptom severity, appraisal, anxiety, depression and coping dissatisfaction were also administered. Factor Analysis of the RAHQ yielded three coping subscales, Active coping, Passive coping and Suppression coping. The subscales were shown to be empirically distinct and to possess satisfactory internal reliability. For a small subgroup of participants, two of the three subscales demonstrated satisfactory test-retest reliability. Construct validity was assessed within a stress and coping framework. The RAHQ will facilitate the investigation of the efficacy of coping strategies for the management of auditory hallucinations.