Dataset Information

A New Semi-Automatic Approach to Find Suitable Virtual Electrodes in Arrays Using an Interpolation Strategy.

ABSTRACT: Functional Electrical Stimulation via electrode arrays enables the user to form virtual electrodes (VEs) of dynamic shape, size, and position. We developed a feedback-control-assisted manual search strategy which allows the therapist to conveniently and continuously modify VEs to find a good stimulation area. This works for applications in which the desired movement consists of at least two degrees of freedom. The virtual electrode can be moved to arbitrary locations within the array, and each involved element is stimulated with an individual intensity. Meanwhile, the applied global stimulation intensity is controlled automatically to meet a predefined angle for one degree of freedom. This enables the therapist to concentrate on the remaining degree(s) of freedom while changing the VE position. This feedback-control-assisted approach aims to integrate the user's opinion and the patient's sensation. Therefore, our method bridges the gap between manual search and fully automatic identification procedures for array electrodes. Measurements in four healthy volunteers were performed to demonstrate the usefulness of our concept, using a 24-element array to generate wrist and hand extension.

SUBMITTER: Salchow C

PROVIDER: S-EPMC4942710 | biostudies-other | 2016 Jun

REPOSITORIES: biostudies-other

ACCESS DATA

Publications

A New Semi-Automatic Approach to Find Suitable Virtual Electrodes in Arrays Using an Interpolation Strategy.

Salchow Christina C Valtin Markus M Seel Thomas T Schauer Thomas T

European journal of translational myology 20160613 2

Functional Electrical Stimulation via electrode arrays enables the user to form virtual electrodes (VEs) of dynamic shape, size, and position. We developed a feedback-control-assisted manual search strategy which allows the therapist to conveniently and continuously modify VEs to find a good stimulation area. This works for applications in which the desired movement consists of at least two degrees of freedom. The virtual electrode can be moved to arbitrary locations within the array, and each i ...[more]

PMID: 27478567

Similar Datasets

Project description:High-density microelectrode arrays can be used to record extracellular action potentials from hundreds to thousands of neurons simultaneously. Efficient spike sorters must be developed to cope with such large data volumes. Most existing spike sorting methods for single electrodes or small multielectrodes, however, suffer from the "curse of dimensionality" and cannot be directly applied to recordings with hundreds of electrodes. This holds particularly true for the standard reference spike sorting algorithm, principal component analysis-based feature extraction, followed by k-means or expectation maximization clustering, against which most spike sorters are evaluated. We present a spike sorting algorithm that circumvents the dimensionality problem by sorting local groups of electrodes independently with classical spike sorting approaches. It is scalable to any number of recording electrodes and well suited for parallel computing. The combination of data prewhitening before the principal component analysis-based extraction and a parameter-free clustering algorithm obviated the need for parameter adjustments. We evaluated its performance using surrogate data in which we systematically varied spike amplitudes and spike rates and that were generated by inserting template spikes into the voltage traces of real recordings. In a direct comparison, our algorithm could compete with existing state-of-the-art spike sorters in terms of sensitivity and precision, while parameter adjustment or manual cluster curation was not required. NEW & NOTEWORTHY We present an automatic spike sorting algorithm that combines three strategies to scale classical spike sorting techniques for high-density microelectrode arrays: 1) splitting the recording electrodes into small groups and sorting them independently; 2) clustering a subset of spikes and classifying the rest to limit computation time; and 3) prewhitening the spike waveforms to enable the use of parameter-free clustering. Finally, we combined these strategies into an automatic spike sorter that is competitive with state-of-the-art spike sorters.

Project description:BackgroundMalaria parasitemia is commonly used as a measurement of the amount of parasites in the patient's blood and a crucial indicator for the degree of infection. Manual evaluation of Giemsa-stained thin blood smears under the microscope is onerous, time consuming and subject to human error. Although automatic assessments can overcome some of these problems the available methods are currently limited by their inability to evaluate cases that deviate from a chosen "standard" model.ResultsIn this study reliable parasitemia counts were achieved even for sub-standard smear and image quality. The outcome was assessed through comparisons with manual evaluations of more than 200 sample smears and related to the complexity of cell overlaps. On average an estimation error of less than 1% with respect to the average of manually obtained parasitemia counts was achieved. In particular the results from the proposed approach are generally within one standard deviation of the counts provided by a comparison group of malariologists yielding a correlation of 0.97. Variations occur mainly for blurred out-of-focus imagery exhibiting larger degrees of cell overlaps in clusters of erythrocytes. The assessment was also carried out in terms of precision and recall and combined in the F-measure providing results generally in the range of 92% to 97% for a variety of smears. In this context the observed trade-off relation between precision and recall guaranteed stable results. Finally, relating the F-measure with the degree of cell overlaps, showed that up to 50% total cell overlap can be tolerated if the smear image is well-focused and the smear itself adequately stained.ConclusionThe automatic analysis has proven to be comparable with manual evaluations in terms of accuracy. Moreover, the test results have shown that the proposed comparison-based approach, by exploiting the interrelation between different images and color channels, has successfully overcome most of the inherent limitations possibly occurring during the sample preparation and image acquisition phase. Eventually, this can be seen as an opportunity for developing low-cost solutions for mass screening.

Dataset Information

A New Semi-Automatic Approach to Find Suitable Virtual Electrodes in Arrays Using an Interpolation Strategy.

Publications

A New Semi-Automatic Approach to Find Suitable Virtual Electrodes in Arrays Using an Interpolation Strategy.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets