1 Introduction FIRST DESCRIBED at the end of the last century, Duchenne muscular dystrophy (DMD) is a sex-linked degenerative muscle disease which affects 1 in 3500 male births (DEN DUNNEN, 1987). It follows a rapid development that leads to death during the third decade. This disease remains incurable. Treatments only aim to slow down the development of the illness and to provide more comfort to D M D children. In the case of a progressive disease, and especially when treatment efficacy needs to be proved, qualitative data are insufficient and quantitative data are required. This has been well discussed by VIGNOS et al. (1963) who used muscular testing and motor and functionality ability quantification. BROOKE et al. (1981) introduced a quantitative trial of D M D which takes into account family and clinical parameters. BROOKE et al. (1983) studied 114 subjects aged 3 16 for 1 year, They noticed a linear decrease of strength related to age, as other authors also reported (ZITERet al., 1977; STERN et al., 1981; SCOTT et al., 1982). However, the course of an illness greatly depends on the patient. Measuring the strength by testing 12 D M D s aged 11-20, LEGRAND-PERSOZ et al. (1977) noticed an exponential decrease with age (strength being supposed normal at birth). The difference between results may come from the diversity of the populations considered, from the muscles studied or even from the quantification method. Indeed, even though all these studies were based on the use of the French Medical Research Council recommendations, each of them proposed their own adaptation. Results are influenced by modification of the protocol, by subject selection criteria, by the order in which different muscular groups are assessed or by the different exercises which are perFirst received 9th April 1990 and in final form 29th May 1991

9 IFMBE: 1992

Medical & Biological Engineering & Computing

formed (MENDELL et al., 1987). However, many authors indicate that the final scores of their tests do not differ by more than 5 per cent, when the test is repeated with the same subject, using the same conditions, by the same examiner or not. But in as much as several muscles are measured, the averaging effect must not be forgotten (LILENFIELDet al., 1954; IDDINGS et al., 1961; GOLDSTEINet al., 1974; ZITER et al., 1977; FLORENCEet al., 1982). A major restriction in muscular and functional testing comes from the difficulty in obtaining sufficient collaboration from boys younger than 5, and making observations becomes delicate if the patient is older than 15 (BROOKE et al., 1983; 1987; MENDELLet al., 1987). So, it seems interesting to investigate an objective way of characterising the course of D M D , where quantification is observer independent and suitable for patients of any age. Surface electromyography (EMG) seems particularly attractive for this purpose, considering the noninvasive way it is recorded and its well known information content. This signal has already been used for the quantification of muscular diseases. MILNER-BROWN et al. (1986) proposed a method based on surface E M G parameters. However, this study concerned only one patient with facioscapulohumeral muscular dystrophy and another with Becker muscular dystrophy, others being considered as healthy control subjects. In the present paper, surface E M G is studied in normal and D M D subjects. The rationale is to elaborate an objective way of quantifying the level of 'sickness' of a particular muscle. The first step must consist of defining relevant E M G parameters to discriminate properly between D M D and controls. In a second step, D M D patients must be characterised with respect to each other depending on their level of sickness assessed by means of E M G parameters. This study proposes an examination protocol and the corresponding quantification methods. As a demonstration, two muscles are examined.

May 1 992

283

2 Material

and methods

The choices in terms of experimental protocol, signal recording and analysis methods are guided by the fact that nonclinician examiners (e,g. physiotherapists or occupational therapists) have to be able to perform the tests on their own. That excludes recordings by means of internal electrodes (classically needles), which de facto excludes the measurement of related parameters such as zero-crossing rate) which are classicially used in clinical investigations. As far as the surface E M G is concerned, this signal is not characterised by single parameters but mostly by a comprehensive parameter set extracted from spectral analysis. In addition, the scatter induced by the electrode location or the electrical properties of the skin/electrode interfaces decreases the relevance of single parameter values as a proper evaluation test (LINDSTROMand PETERSEN,1983). On the other hand, the course of signal features during sustained contractions is widely used as an index of muscle fatigue (LINDSTR6M et al., 1977; DE LUCA, 1984). Provided that a relationship exists between muscular fatigue and the distribution of muscle fibre type (BURKE et al., 1973), one can expect a significant discrimination between DMDs and controls from a fatigue test. Indeed, it has already been demonstrated that fast fibres are preferentially affected in D M D (DuBowITZ and BROOKE,1973; WEBSTER et al., 1988). Changes in the E M G signal were studied during isometric-isotonic elbow flexion. To induce localised muscular fatigue, a long-term exercise (7 min) at 40 per cent of the maximum voluntary contraction (MVC) was used. 33 boys with D M D aged 7-22 years participated in this part of the study and five children aged 9-13 years were used as controls. The biceps brachii and the brachioradialis (both elbow flexors) were studied because they presented easy access and were very likely to differ in their level of sickness. E M G signals were collected from each muscle through two surface Ag/AgC1 electrodes (diameter 8 mm) stuck on the skin. The interelectrode distance was 2cm. Interelectrode impedance never exceeded 10k~ and typically was lower than 5 kf~. Preamplification and safety were both achieved by a differential isolation amplifier ECEM. Then an instrumentation amplifier was used to adjust the gain, and signals were bandpass filtered (3 Hz-2kHz). Signals were recorded using an eight-channel FM recorder (T18 Transamerica) and displayed on a digital oscilloscope to control the recording quality. The signals were then transferred to an IBM-compatible microcomputer for further processing. A specific ergometer was developed (Fig. 1). This

Fig. 1 Experimentalsetup 284

ensured correct position of the subject and was easy to approach from any kind of wheelchair. It accommodated large differences in size and strength, and abnormal postures. The subjects were required to perform isometric flexions of the right forearm, in a sitting position, the arm and forearm being maintained in the same horizontal plane. A bracelet was fixed around the wrist. This bracelet was guided in a slide bar by a set of needle roller pads allowing short range motions without any friction. In most cases the hand was held in a position of scmi-pronation. But, to make it suitable for possible articular retractions, it was possible to adjust the bracelet into a slightly prone or supine position. The right shoulder was fixed firmly by means of an adapted support. The elbow sat on a moss cushion to help the subject to maintain the arm and forearm in a resting position without any muscular effort. MVC was evaluated using a piezoelectric gauge Enertec Schlumberger CD7400/0 (range _+50 dN; resolution better than 0-1 N) connected to the ergometer. For the other tests, the gauge was replaced by a load, hung to the wrist bracelet by means of a cable mounted on a guide pulley (Fig. 1). This ergometer was able to function with as little as a 30 g strength requirement. Each test began with the MVC evaluation. Subjects were asked to pull the gauge as strongly as possible three times, and mean value was taken as the MVC. Then, patients were asked to maintain a load corresponding to 40 per cent of their MVC for 7 rain. Percentage and duration were defined experimentally and corresponded to the strongest effort that both healthy and dystrophic children were able to manage for the same time. Furthermore, these conditions were supposed to be sufficient to induce classical E M G changes due to localised muscular fatigue, at least for normal children. 3 Data processing 3.1 Acquisition The length of the test produced too large a number of sampled data to enable the computation of the power spectral density function (PSDF) to be achieved by an IBM PC compatible in a reasonable period of time. The E M G parameters were therefore computed by the microcomputer linked to a spectrum analyser (HP 3582A) by means of a GP-IB interface. The analyser performed the acquisition of 1024 points of the E M G signal and the online calculation of the PSDF, through a Hanning window. The spectrum analyser sampling rate of 2 k H z corresponded to twice the Nyquist frequency, so the spectral range was 0-500 Hz. Sixteen elementary PSDFs were averaged, providing a mean spectrum corresponding to an 8s signal. This average spectrum was transferred to the microcomputer and spectral parameters were calculated. The spectral range was thus divided into 20 frequency bands for which relative power was calculated. Global parameters such as total power (TP), mean power frequency (MPF), median frequency, skewness and kurtosis were computed at the same time, leading to a total of 25 parameters for each spectrum. To simulate online processing, the analogue recorder was never stopped when reviewing an experiment, so that any test can also be performed and evaluated without any previous recording. The only part of the signal which was not considered during the computation was the duration of the data transfer between the spectral analyser and the microcomputer. Results were stored on floppy disks for further use. Each muscle was studied separately.

Medical & Biological Engineering & Computing

May 1992

Each experiment k is described by a 25 x Nk array for each muscle. Each of the 25 columns estimates the evolution of a particular parameter for Nk successive times. The discrimination between D M D s and controls now corresponds to a comparison between 25 x Nk arrays. As acquired signals do not have the same number of points N k from one experiment to another, a specific transformation is needed to provide arrays of the same dimensions for every experiment. This is a necessary condition for all data-processing methods which rely on matrix or vector combinations.

with y~ -y~" = N = P =

one measured point one estimated point number of points model order

In that case, the reduced difference follows a Student law of N - P degrees of freedom. Then, a point is considered as aberrant when outside the confidence interval defined by

P ( Y ~ - YP-----~) t o " ) ~

Duchenne muscular dystrophy quantification: a multivariate analysis of surface EMG.

The paper describes a method of quantifying Duchenne muscular dystrophy which is examiner independent and uses surface electromyographic signals (EMG)...
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