An Automatic Procedure For The Determination Of F-Wave Latency And End Intervals During FES M.Freschi, R.Thorsen, S.Viganò, and M.Ferrarin
Abstract The F-wave is a recurrent discharge of an antidromically activated motor neurone and has received little attention in the FES literature. It though may have important influence on the design of neural prosthesis. It is found in the myoelectric signal from the 16Hz stimulated tibialis anterior muscle with a mean latency (tFstart) of 35ms and an end interval (tFend) of 55ms. Since the F-wave is normally used for diagnostics it is measured at very low frequency and latency is evaluated manually. The elevated frequency used for FES purpose together with the need to analyse long term effects has created a need for an automatically method to characterise F-wave. Such a method to determine latency and end interval has been developed and tested in 5*20 trials on five neurological normal male subjects. Results show a low intra-subject standard deviation (SD). Hypothesising that latency do not change for a subject during and between experimental sessions, the low SD is proof of robustness of this method. Higher inter-subject SD values imply that an F-wave latency period has to be calculated for each subject.
1. Introduction F-waves are a recurrent discharge of an antidromically activated motor neurone. They follow the M wave and occur in 0-5% of the stimuli in each motor unit [1]. The F-waves are present in all the muscles of the legs, with a percentage of 60 % in TA, where H-reflex is absent [2]. It has been demonstrated that F-waves registered after stimulation were preferentially generated by the fastest conducting axons [3]. These findings suggest that the F-waves may be elicited in motor-neurones with different depolarisation threshold, but primarily in larger and faster nerve fibres, with a lower threshold of depolarisation. [4]. The variability of the configuration and the low amplitude of F waves are the consequence of the infrequent backfiring and of the fact that the potential is composed by a few motor units only [5,6]. The myoelectrical signal from a stimulated muscle is thus strongly influenced by the F-waves in a manner that is difficult to distinguish from volitional contraction
Centro di Bioingegneria Fond. Don Gnocchi Milano, Italy
[email protected] except that the F-waves will occur in a limited interval after the stimulation only. This study regards electrical stimulation on the anterior tibial muscle (TA). Many clinical studies on F-wave have been done, but in literature there has only been found one articles regarding the F-wave during FES of TA [7]. This is the first of two papers [8] regarding Fwave registration during FES of TA aimed for the application of a neuroprosthesis using a stimulation interval of 60ms with automatic classification where Fwaves start (tFstart) and where the F-waves end (tFend).
2. Methods A system for Myo-electrical Controlled Functional Electrical Stimulation (MeCFES), which is capable of recording myoelectrical signals (MES) from the same muscle as it stimulates, has been used [9,10]. The signal is sampled at 2.5 kHz and divided into blocks of 60ms, such that block starts after each stimulation impulse. The first 10ms of each block is saturated by the M-wave and thus discarded. Each block of comprise the 125 remaining samples (50ms) of MES. In the Figure 1 it is possible to see two of the registered signals. 300
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Dep. of Bioengineering Politecnico di Milano Milano, Italy
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Figure 1. The MES contains three components: 1) End of M-wave (first 10ms of the muscle contraction signal are not registered). This can be reduced by applying a comb filter to the signal. 2) Randomly occurring F-wave 3) Volitional signal components (registered together with the stimulation, shown as dashed).
the trial and N=1 the filter order (b0=1, b1=-1 and a1=0). Block standard deviation (BSD) has been calculated as: BSD =
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where and i is the sample number in the block. Mean value Y is zero due to the comb filter. The BSD is having high values in time intervals with randomly occurring signal components such as the Fwave and thus reflecting the F-probability/amplitude distribution. From literature [11] it is known that Fwave presence can be expected after 30ms. Due to the noise and variations in the M-wave the tFstart - tFend interval is not clearly defined and the curve has several local minima (fig. 3). 60
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Voluntary component shown is not usually present during tests where the subject is relaxing the TA. It is difficult to reduce the F-wave by filtering, because it is similar in frequency to the volitional component and since they are generated by the same motor units. The difference between them is that F-wave has a delay and could be characterised by its latency period. The F-wave is considered as noise to the control of a myoelectrical controlled prosthesis, and it cannot be distinguished by the control system with a voluntary signal and cause unwanted stimulation. Five male healthy subjects have been tested. Characteristics of subjects: • age = from 22 to 34 years • height = from 178 to 198 cm • weight = from 65 to 90 kg Five sessions have been done on every subject. An experimental protocol with twenty trials of constant stimulation has been adopted. Subjects were asked to relax their leg during stimulation and they were helped by a visual feedback of the F-wave level. The stimulation parameters were: • current intensity = from 17 to 24 mA • pulse rate = 16.6 Hz • pulse shape = biphasic with interpulse interval • pulse width = 300 µs Between each trial of 30s there were a pause of 30s. Electrode configuration is depicted in Figure 2.
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Figure 3. STD curve. Local minima are shown by a (*) Reference electrode
Stimulation electrodes MES electrodes
Figure 2. Electrode placement on the TA F-wave latency period for each trial has been calculated using algorithms implemented in MATLAB™. First the signal has been filtered by a comb filter to reduce periodic components such as the M-wave: N
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Two of these minimum values, plotted in Figure 3 on the BSD curve, identify the starting and the end of the F-wave latency period. To smoothen the BSD curve It has been resampled at 16/125 of the original sampling rate. On this new curve only two minima can be individuated where the extremes of the F-wave interval fall. Starting from them, the program searches the original BSD curve for first mimimum closer to the centre of the two extremes (Fig. 4). Sometimes the algorithm will fail in the calculation of the extremes, represented by the circles. In this case the method is “semi-automatic”, because the operator has to manually choose one or two of the minimum values on the original BSD curve, but the program automatically does the identification of minimum values on this curve.
Acknowledgments
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This work has been sponsored by the EU-project NeuralPro. R.Thorsen has developed equipment & software during his visits to Centro di BioingegneriaItalty, University Twente-The Netherlands and University College London-England with support from the EU-project NEUROS2. Data acquisition and processing has been done at Bioengineering Centre, Fond. Don C.Gnocchi & Politecnico di Milano as part of the graduation project of M.Freschi and S.Viganò.
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Figure 4. Solid curve is the filtered block. The two circles are the two minimum values found on it and the dot curve is the original STD curve, with its minimum values.
3. Results and discussion The data processing gives results reported in Table 1. tFstart tFend Subj Mean STD Min Max Mean STD Min Max 38.6 0.6 34.8 41.2 56.0 0.7 53.2 58.0 A 35.2 0.8 32.8 37.2 52.2 1.4 48.8 57.2 B 35.4 0.8 32.8 38.0 53.4 0.4 51.6 57.2 C D 35.0 0.5 33.2 39.6 54.9 0.9 52.4 58.0 32.6 0.4 31.2 34.0 50.2 1.0 47.2 54.4 E Mean 35.3 2.1 31.2 41.2 53.3 2.3 47.2 58.0 Table 1. Start intervals for the F-wave and the end intervals where F is decayed. Mean, standard deviation and extreme values are given. In the four columns are reported the Mean, STD, Minimum and Maximum values of all trials done on each subject and, in TOT row, on all the subjects. Automatic identification of tFstart and tFend were successful in 48% of the trials. These numerical results are in accordance with reported findings [10] on F-Wave of TA muscle, where latencies in the range 34-50 ms were reported, although with another electrode configuration. We assume that latency values do not change for a subject during the five sessions. Effort has been put into maintaining electrode positions between sessions. The STD values found for each subject are low indicating good robustness of the procedure to identify F-wave latencies. On the contrary, the inter-subject STD values are higher. Therefore, with the aim to use latency values to control a neuroprosthesis, an F-wave latency period has to be identified for each patient.
4. Conclusion We have developed an automatic method for the determination of the signal interval where F-waves are present after each stimulation pulse. This is useful for automatic analysis of myoelectric signals with the scope of characterisation of the F-wave level.
References [1] E. Stålberg and B. Falck, “Clinical Motor Nerve Conduction Studies,” Methods in Clinical Neurophysiology, vol. 4, pp. 61-80, 1993. [2] A. Jusic, R. Baraba, and A. Bogunovic, “H-reflex and F-wave potentials in leg and arm muscles,” Electromyogr Clin Neurophysiol, vol. 35, pp. 471-8, 1995. [3] Maciel Nobrega J.A., Mastrocola Manzano G., Ferreira Novo N., Monteagudo P.T. “F waves and condution velocities range”. Electromyogr. Clin. Neurophysiol., 40: 327-329, 2000. [4] J. J. Vatine and B. Gonen, “Behavior of F-response and determination of actively involved motoneurons,” Electromyogr Clin Neurophysiol, vol. 36, pp. 349-55, 1996. [5] Feasby T.E. and Brown W.F. “Variation of motor unit size in the human extensor digitorum brevis and thenar muscles”. J. Neurol. Neurosurg. Psychiat., 37: 916-926, 1974. [6] Yates S.K. and Brown W.F. “Charateristics of the F-response: a single motor unit study”. J. Neurol. Neurosurg. Psychiat., 42: 161-170, 1979 [7] P. Mela, R. Thorsen, et al., “Volitional And Reflex Contributions To Force During Isometric Contractions Elicited By Electrical Stimulation,” Medical & Biological Engineering and Computing., Submitted 2001. [8] R.Thorsen, M. Freschi, S. Viganò, and M.Ferrarin “Can The High Repetition Rate Induced F-Wave Be Volitionally Controlled? “ Proc. 7 th. Ann. Conf. of IFESS, submitted2002 [9] R. Thorsen, “Restoration of Hand Function in Tetraplegics Using Myoelectrically Controlled Functional Electrical Stimulation of the Controlling Muscle,” Ph.D Thesis, Electronics Institute, The Technical University of Denmark, Lyngby, 1997. [10] Thorsen R., Spadone R., Ferrarin M. “A pilot study of myoelectrically controlled FES of upper extremity”. IEEE Trans. Neural. Syst. Rehabil. Eng. 9(2): 161-8, Jun 2001. [11] M. R. Alavian Ghavanini, S. Samadzadeh, and A. Alavian Ghavanini, “Normal values of F wave in upper extremities of 50 healthy individuals in Iran,” Electromyogr Clin Neurophysiol, vol. 38, pp. 305-8, 1998.
