Study on Interaction Between Temporal and Spatial Information in Classification of EMG Signals for Myoelectric Prostheses.

Advanced forearm prosthetic devices employ classifiers to recognize different electromyography (EMG) signal patterns, in order to identify the user's intended motion gesture. The classification accuracy is one of the main determinants of real-time controllability of a prosthetic limb and hence the necessity to achieve as high an accuracy as possible. In this paper, we study the effects of the temporal and spatial information provided to the classifier on its off-line performance and analyze their inter-dependencies.

Automatic misclassification rejection for LDA classifier using ROC curves.

This paper presents a technique to improve the performance of an LDA classifier by determining if the predicted classification output is a misclassification and thereby rejecting it. This is achieved by automatically computing a class specific threshold with the help of ROC curves. If the posterior probability of a prediction is below the threshold, the classification result is discarded.

Biomimetic direction of arrival estimation for resolving front-back confusions in hearing aids.

Sound sources at the same angle in front or behind a two-microphone array (e.g., bilateral hearing aids) produce the same time delay and two estimates for the direction of arrival: A front-back confusion.

Lower arm electromyography (EMG) activity detection using local binary patterns.

This paper presents a new electromyography activity detection technique in which 1-D local binary pattern histograms are used to distinguish between periods of activity and inactivity in myoelectric signals. The algorithm is tested on forearm surface myoelectric signals occurring due to hand gestures. The novel features of the presented method are that: 1) activity detection is performed across multiple channels using few parameters and without the need for majority vote mechanisms, 2) there are no per-channel thresholds to be tuned, which makes the process of activity detection easier and simpler to implement and less prone to errors, 3) it is not necessary to measure the properties of the signal during a quiescent period before using the algorithm.

Identification of contaminant type in surface electromyography (EMG) signals.

The ability to recognize various forms of contaminants in surface electromyography (EMG) signals and to ascertain the overall quality of such signals is important in many EMG-enabled rehabilitation systems. In this paper, new methods for the automatic identification of commonly occurring contaminant types in surface EMG signals are presented. Such methods are advantageous because the contaminant type is typically not known in advance.

Auditory externalization in hearing-impaired listeners: the effect of pinna cues and number of talkers.

Hearing-aid wearers have reported sound source locations as being perceptually internalized (i.e., inside their head).

Objective method of assessing and presenting the House-Brackmann and regional grades of facial palsy by production of a facogram.

Objective: To produce a reliable objective method of assessing the House-Brackmann (H-B) and regional grades of facial palsy with the results produced and presented in a time and manner suitable for a routine clinical setting.

Study Design: Analysis of video pixel data using artificial neural networks (ANNs).

Setting: Tertiary-referral neuro-otologic center.

Quantitative analysis of facial paralysis using local binary patterns in biomedical videos.

Facial paralysis is the loss of voluntary muscle movement of one side of the face. A quantitative, objective, and reliable assessment system would be an invaluable tool for clinicians treating patients with this condition. This paper presents a novel framework for objective measurement of facial paralysis.

Objective grading of facial paralysis using Local Binary Patterns in video processing.

This paper presents a novel framework for objective measurement of facial paralysis in biomedial videos. The motion information in the horizontal and vertical directions and the appearance features on the apex frames are extracted based on the Local Binary Patterns (LBP) on the temporal-spatial domain in each facial region. These features are temporally and spatially enhanced by the application of block schemes.

Compression defects in different reconstructions from phase-shifting digital holographic data.

Three principal strategies for the compression of phase-shifting digital holograms (interferogram domain-, hologram domain-, and reconstruction domain-based strategies) are reviewed and their effects in the reconstruction domain are investigated. Images of the reconstructions are provided to visually compare the performances of the methods. In addition to single reconstructions the compression effects on different depth reconstructions and reconstructions corresponding to different viewing angles are investigated so that a range of the 3D aspects of the holograms may be considered.

Reconstruction domain compression of phase-shifting digital holograms.

Phase-shifting digital hologram compression has been mainly studied in the recording domain, where data possess a rather randomlike appearance, yielding reduced compression efficiency. We carry out the compression of such data in the reconstruction domain, which benefits from the spatial correlation of the data yielding, increased efficiency. Real holographic data are used to demonstrate the performance of the new approach.

Use of Fresnelets for phase-shifting digital hologram compression.

Fresnelets are wavelet-like base functions specially tailored for digital holography applications. We introduce their use in phase-shifting interferometry (PSI) digital holography for the compression of such holographic data. Two compression methods are investigated.

Compression of interference patterns with application to phase-shifting digital holography.

A compression method of phase-shifting digital holographic data is presented. Three interference patterns are recorded, and holographic information is extracted from them by phase-shifting interferometry. The scheme uses standard baseline Joint Photographic Experts Group (JPEG) or standard JPEG-2000 image compression techniques on the recorded interference patterns to reduce the amount of data to be stored.

Efficient implementation of accurate geometric transformations for 2-D and 3-D image processing.

This paper proposes the use of a polynomial interpolator structure (based on Horner's scheme) which is efficiently realizable in hardware, for high-quality geometric transformation of two- and three-dimensional images. Polynomial-based interpolators such as cubic B-splines and optimal interpolators of shortest support are shown to be exactly implementable in the Horner structure framework. This structure suggests a hardware/software partition which can lead to efficient implementations for multidimensional interpolation.