Preprocessing surface EMG data removes voluntary muscle activity and enhances SPiQE fasciculation analysis

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A novel preprocessing step removes the need for manual selection of relaxed surface EMG data.

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SPiQE provides reliable fasciculation analysis from raw thirty-minute recordings in ALS.

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This paves the way for clinical calibration of a potential novel biomarker of disease progression.

Objectives

Fasciculations are a clinical hallmark of amyotrophic lateral sclerosis (ALS). The Surface Potential Quantification Engine (SPiQE) is a novel analytical tool to identify fasciculation potentials from high-density surface electromyography (HDSEMG). This method was accurate on relaxed recordings amidst fluctuating noise levels. To avoid time-consuming manual exclusion of voluntary muscle activity, we developed a method capable of rapidly excluding voluntary potentials and integrating with the established SPiQE pipeline.

Methods

Six ALS patients, one patient with benign fasciculation syndrome and one patient with multifocal motor neuropathy underwent monthly thirty-minute HDSEMG from biceps and gastrocnemius. In MATLAB, we developed and compared the performance of four Active Voluntary IDentification (AVID) strategies, producing a decision aid for optimal selection.

Results

Assessment of 601 one-minute recordings permitted the development of sensitive, specific and screening strategies to exclude voluntary potentials. Exclusion times (0.2–13.1 minutes), processing times (10.7–49.5 seconds) and fasciculation frequencies (27.4–71.1 per minute) for 165 thirty-minute recordings were compared. The overall median fasciculation frequency was 40.5 per minute (10.6–79.4 IQR).

Conclusion

We hereby introduce AVID as a flexible, targeted approach to exclude voluntary muscle activity from HDSEMG recordings.

Significance

Longitudinal quantification of fasciculations in ALS could provide unique insight into motor neuron health.

SPiQE: An automated analytical tool for detecting and characterising fasciculations in amyotrophic lateral sclerosis

OBJECTIVES

Fasciculations are a clinical hallmark of amyotrophic lateral sclerosis (ALS). Compared to concentric needle EMG, high-density surface EMG (HDSEMG) is non-invasive and records fasciculation potentials (FPs) from greater muscle volumes over longer durations. To detect and characterise FPs from vast data sets generated by serial HDSEMG, we developed an automated analytical tool.

METHODS

Six ALS patients and two control patients (one with benign fasciculation syndrome and one with multifocal motor neuropathy) underwent 30-minute HDSEMG from biceps and gastrocnemius monthly. In MATLAB we developed a novel, innovative method to identify FPs amidst fluctuating noise levels. One hundred repeats of 5-fold cross validation estimated the model's predictive ability.

RESULTS

By applying this method, we identified 5,318 FPs from 80 minutes of recordings with a sensitivity of 83.6% (+/- 0.2 SEM), specificity of 91.6% (+/- 0.1 SEM) and classification accuracy of 87.9% (+/- 0.1 SEM). An amplitude exclusion threshold (100 μV) removed excessively noisy data without compromising sensitivity. The resulting automated FP counts were not significantly different to the manual counts (p = 0.394).

CONCLUSION

We have devised and internally validated an automated method to accurately identify FPs from HDSEMG, a technique we have named Surface Potential Quantification Engine (SPiQE).

SIGNIFICANCE

Longitudinal quantification of fasciculations in ALS could provide unique insight into motor neuron health.

A New Individually Addressable Micro-LED Array for Photogenetic Neural Stimulation

Here, we demonstrate the use of a micro light emitting diode (LED) array as a powerful tool for complex spatiotemporal control of photosensitized neurons. The array can generate arbitrary, 2-D, excitation patterns with millisecond and micrometer resolution. In particular, we describe an active matrix control address system to allow simultaneous control of 256 individual micro LEDs. We present the system optically integrated into a microscope environment and patch clamp electrophysiology. The results show that the emitters have sufficient radiance at the required wavelength to stimulate neurons expressing channelrhodopsin-2 (ChR2).

A non-invasive retinal prosthesis - testing the concept

We have developed a testing platform for a novel type of retinal prosthesis. Our system uses an array of light sources as non-contact stimulators. The platform consists of an imaging system based on a CMOS camera, PC based image processing, and a stimulation address system carried out on a Field Programmable Gated Array which addresses a matrix array of LEDs. Special optics are used to focus the light from the LED array onto light sensitized cells.