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Journal ArticleDOI

Automatic Decomposition of the Clinical Electromyogram

TL;DR: A new, automatic signal-processing method (ADEMG) for extracting motor-unit action potentials (MUAP's) from the electromyographic interference pattern for clinical diagnostic purposes and measures their amplitudes, durations, rise rates, numbers of phases, and firing rates.
Abstract: We describe a new, automatic signal-processing method (ADEMG) for extracting motor-unit action potentials (MUAP's) from the electromyographic interference pattern for clinical diagnostic purposes. The method employs digital filtering to select the spike components of the MUAP's from the background activity, identifies the spikes by template matching, averages the MUAP waveforms from the raw signal using the identified spikes as triggers, and measures their amplitudes, durations, rise rates, numbers of phases, and firing rates. Efficient new algorithms are used to align and compare spikes and to eliminate interference from the MUAP averages. In a typical 10-s signal recorded from the biceps brachii muscle using a needle electrode during a 20 percent-maximal isometric contraction, the method identifies 8-15 simultaneously active MUAP's and detects 30-70 percent of their occurrences. The analysis time is 90 s on a PDP-11/34A.
Citations
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Journal ArticleDOI
TL;DR: The inverse relationship between the recruitment threshold and the firing rate previously reported for muscles innervated by spinal nerves is also present in the orbicularis oculi and the platysma, which are innervate by cranial nerves.
Abstract: This report describes an early version of a technique for decomposing surface electromyographic (sEMG) signals into the constituent motor unit (MU) action potential trains. A surface sensor array is used to collect four channels of differentially amplified EMG signals. The decomposition is achieved by a set of algorithms that uses a specially developed knowledge-based Artificial Intelligence framework. In the automatic mode the accuracy ranges from 75 to 91%. An Interactive Editor is used to increase the accuracy to >97% in signal epochs of about 30-s duration. The accuracy was verified by comparing the firings of action potentials from the EMG signals detected simultaneously by the surface sensor array and by a needle sensor. We have decomposed up to six MU action potential trains from the sEMG signal detected from the orbicularis oculi, platysma, and tibialis anterior muscles. However, the yield is generally low, with typically ≤5 MUs per contraction. Both the accuracy and the yield should increase as the algorithms are developed further. With this technique it is possible to investigate the behavior of MUs in muscles that are not easily studied by needle sensors. We found that the inverse relationship between the recruitment threshold and the firing rate previously reported for muscles innervated by spinal nerves is also present in the orbicularis oculi and the platysma, which are innervated by cranial nerves. However, these two muscles were found to have greater and more widespread values of firing rates than those of large limb muscles.

426 citations


Cites background from "Automatic Decomposition of the Clin..."

  • ...Applications to separate the EMG signals did not appear until a full decade later (Andreassen 1983; De Figueiredo and Gerber 1983; De Luca and Forrest 1972; De Luca et al. 1982a,b; Guiheneuc et al. 1989; LeFever and De Luca 1978; Mambrito and De Luca 1984; McGill et al. 1985)....

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Journal ArticleDOI
TL;DR: An interactive computer program for decomposing EMG signals into their component motor-unit potential (MUP) trains and for averaging MUP waveforms and which shows that 100% accuracy can be achieved for MUPs with peak-to-peak amplitudes greater than 2.5 times the rms signal amplitude.

293 citations


Cites background or methods from "Automatic Decomposition of the Clin..."

  • ...McGill et al., 1985; Haas and Meyer, 1989; De Luca, 19 Stashuk, 2001; Zennaro et al., 2003)....

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  • ...…heir uum disitute that ount lso o or UPs lve islete unit nd rge 0 d esults show that 100% accuracy can be achieved for MUPs with peak-to-peak amplitudes greater than 2.5 times the rms signa xamples are presented to show how decomposition can be used to investigate motor-unit recruitment and…...

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  • ...The two wires had been inserted together using a single hypodermic needle, and their recording surfaces were separated by about 2 mm due to different barb lengths....

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  • ...…ubtracts out the effect of the interference from the o UPs to achieve signal-to-noise ratios much higher hose obtained using simple averaging (McGill et al., 1985). n this way, EMGLAB is able to obtain MUP averages acc ble for architectural analysis from 10 or 20 s long epo ven in fairly…...

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Journal ArticleDOI
TL;DR: Techniques exist for the decomposition of an EMG signal into its constituent components and the fundamental composition of EMG signals is explained and after, potential sources of information from and various uses of decomposed EMg signals are described.

252 citations


Cites background or methods from "Automatic Decomposition of the Clin..."

  • ...Several modelling approaches have been reported [9,23,26,43]....

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  • ...Others have used partitioning methods such as a modified K-means technique [71] and the leader-based approach [36,41,43,48,65]....

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  • ...One consistent method of selecting segments that contain MUAPs that can be consistently correctly assigned is to consider the slope of the micro-EMG signal [23,38,40] or the micro-EMG signal after it has been passed through a low pass differentiator [27,28,36,43,46,75]....

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  • ...[43] instead adjust acceptance thresholds based on MUAP size....

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  • ...All of these techniques are similar in that they reduce the space required to be searched by first selecting a subset of possibly contributing MUAPs, limit the number of assumed contributing MUAPs to 2 or 3, initially align the MUAPs using either peak values [43] or maximal correlation [9] and use optimization techniques to solve for the model parameters....

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Journal ArticleDOI
TL;DR: Different aspects of quantitation, such as motor unit action potential parameters, automatic analysis methods, reference values, and findings in abnormal conditions, are discussed.
Abstract: A review of quantitative methods for electromyography is given. Background information about motor unit anatomy, physiology, and pathology is provided to explain some of the presented electrophysiological phenomena. Different aspects of quantitation, such as motor unit action potential parameters, automatic analysis methods, reference values, and findings in abnormal conditions, are discussed.

214 citations

Journal ArticleDOI
TL;DR: The procedures first involve the decomposition of the micro signals and then the quantitative analysis of the resulting motor unit action potential trains (MUAPTs) in conjunction with the associated macro signal.

198 citations


Cites background or methods from "Automatic Decomposition of the Clin..."

  • ...[10]....

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  • ...Recently however, several clinical EMG signal decomposition systems have been introduced [7–12] and at least three are currently available on commercial clinical EMG systems and have published reference values [10–15]....

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  • ...Mean, median [11], mode [30], statistical [12] and interference cancelling [10] averaging techniques have been used to reduce the interfering activity of other motor units when estimating the prototypical MUAP....

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References
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Journal ArticleDOI
TL;DR: The myoelectric signal is the electrical manifestation of the neuromuscular activation associated with a contracting muscle and the lack of a proper description of the ME signal is probably the greatest single factor which has hampered the development of electromyography (EMG) into a precise discipline.
Abstract: The myoelectric (ME) signal is the electrical manifestation of the neuromuscular activation associated with a contracting muscle. It is an exceedingly complicated signal which is affected by the anatomical and physiological properties of muscles, the control scheme of the peripheral nervous system, as well as the characteristics of the instrumentation that is used to detect and observe it. Most of the relationships between the ME signal and the properties of a contracting muscle which are presently employed have evolved serendipitously. The lack of a proper description of the ME signal is probably the greatest single factor which has hampered the development of electromyography (EMG) into a precise discipline.

631 citations


"Automatic Decomposition of the Clin..." refers background in this paper

  • ...Their interspike intervals (ISI's) have an approximately Gaussian distribution whose standard deviation is 10-20 percent of the mean [13], [35]....

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Journal ArticleDOI
TL;DR: A technique has been developed which enables the decomposition (separation) of a myoelectric signal into its constituent motor unit action potential trains using a-sophisticated template matching routine and details of the firing statistics of the motor units.
Abstract: A technique has been developed which enables the decomposition (separation) of a myoelectric signal into its constituent motor unit action potential trains. It consists of a multichannel (via one electrode) myoelectric signal recording procedure, a data compression algorithm, a digital filtering algorithm, and a hybrid visual-computer decomposition scheme. The algorithms have been implemented on a PDP 11/34 computer. Of the four major segments of the technique, the decomposition scheme is by far the most involved. The decomposition algorithm uses a-sophisticated template matching routine and details of the firing statistics of the motor units to identify motor unit action potentials in the myoelectric signal, even when they are super-imposed with other motor unit action potentials. In general, the algorithms of the decomposition scheme do not run automatically. They require input from the human operator to maintain reliability and accuracy during a decomposition.

317 citations


"Automatic Decomposition of the Clin..." refers background or methods in this paper

  • ...This alignment is sufficiently accurate-since the spikes are so narrow-that spikes and templates can be compared directly, without first having to be aligned explicitly as in other template-matching schemes [13], [31]....

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  • ...As a result, high-pass filtering [13], [28] or differentation [29] is effective in selecting the spikes from the background activity....

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  • ...The method of LeFever and De Luca [13] can analyze EMG's recorded during strong contractions, but it is too time consuming for clinical use....

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  • ...Their interspike intervals (ISI's) have an approximately Gaussian distribution whose standard deviation is 10-20 percent of the mean [13], [35]....

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  • ...duce misalignment errors resulting from time quantization [13], [31]....

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Journal Article

305 citations


"Automatic Decomposition of the Clin..." refers background in this paper

  • ...MUAP spikes originating from muscle fibers close to the electrode have sharp rising edges while MUAP's originating farther away are broadened due to the low-passfiltering character of the muscle tissue [27]....

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Journal ArticleDOI
TL;DR: This study investigates here the low-pass first- and second-order digital differentiation from both theoretical and practical points of view, in order to achieve good and simple algorithms.
Abstract: Digital low-pass differentiation is often required in processing various biological or biomechanical data. However, both the nature of biological signals and the use of micro-or minicomputers in such applications imply the need for simple, low-order, and fast differentiation methods, rather than sophisticated high-order algorithms. Responding to this need, we investigate here the low-pass first- and second-order digital differentiation from both theoretical and practical points of view, in order to achieve good and simple algorithms. In contrast with most of the research works previously done in this field, whose main aim was to achieve better accuracy even in the cost of using quite high-order algorithms, we restrict ourselves in this study only to low orders, being interested not only in the accuracy achieved, but also in the simplicity of the algorithm. After discussing the theoretical considerations concerning our optimum low-pass differentiation filters, we present our simple low-order filters and show them to be not only very convenient for use, but also almost optimum.

217 citations


"Automatic Decomposition of the Clin..." refers background in this paper

  • ...frequency noise, but it can be performed safely on highSNR signals with band-limited derivatives by restricting the operation to the frequencies of interest [30]....

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  • ...These filters belong to a class of so-called "low-pass differentiators" [30] and have the following properties: 1) they are designed for efficient "Nyquistrate" sampling, 2) they have excellent temporal resolution resulting from their wide bandwidths, and 3) they are very fast, requiring only a few additions and subtractions per sample....

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Book
01 Jan 1957

204 citations


"Automatic Decomposition of the Clin..." refers background or methods in this paper

  • ...Several methods have been developed for quantitatively measuring MUAP properties [1], [6]-[12], but they...

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  • ...Some care is needed in selecting a recording site, but not the precise optimization needed in classical MUAP analysis [1]....

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  • ..." Diagnosis is based on the properties (amplitude, durations, and complexity) of the individual MUAP's-small, fragmented MUAP's indicating muscle-fiber loss in myopathies; large, long-duration MUAP's indicating collateral reinnervation accompanying motoneuron dysfunction in neuropathies [1]-and on the intensity and complexity of the interference pattern-which reflect the pattern of motor-unit recruitment....

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