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Decomposition of surface electromyograms, recorded during slow dynamic contractions of biceps brachii muscle
36
Abstracts of the 2007 SIAMOC congress / Gait & Posture xxx (2008) xxx–xxx
parameter, allows to get insight on the level of muscular fatigue during the repetitive task.
Reference [1] Farina D, et al., Noninvasive estimation of motor unit conduction velocity distribution using linear electrode arrays. IEEE Trans Biomed Eng 2000;47(March (3)):380–8. doi:10.1016/j.gaitpost.2007.12.064 Decomposition of surface electromyograms, recorded during slow dynamic contractions of biceps brachii muscle A. Holobar 1,∗ , M. Gazzoni 1 , D. Zazula 2 , R. Merletti 1 1 2
LISiN, Politecnico di Torino, Torino, Italy FEECS, University of Maribor, Maribor, Slovenia
Introduction: Dynamic surface electromyograms (sEMG) are important, but complex source of information. During the muscle contraction distances between the detection system and the motor units (MUs) change causing substantial changes in the detected MU action potentials (MUAPs). Recently, highly efficient Convolution Kernel Compensation (CKC) method was proposed for decomposition of high-density sEMG in isometric condition [1]. The aim of this study was to test the CKC ability to decompose dynamic sEMG signals, recorded during slow contractions of biceps brachii muscle. Methods: Two young male subjects participated to the experiment. Surface EMG signals were recorded with an adhesive two-dimensional array of 64 circular electrodes (radius of 1 mm) arranged in five columns and 13 lines. Inter-electrode distance was 8 mm. Recordings were performed in single differential configuration during isokinetic flexions and extensions of elbow joint in the sagittal plane. The elbow joint angle was measured by a potentiometric goniometer and ranged form 0◦ to 150◦ with angular velocities vγ of 15◦ /s, 7◦ /s and 5◦ /s. A weight of 1 kg was fixed at the wrist of the tested arm. Acquired sEMG signals were band-pass filtered (20–450 Hz, 3 dB), sampled at 2048 samples/s, and divided into 2.5 s long non-overlapping epochs. In order to limit the nonstationarity of MUAP shapes, each signal epoch was decomposed independently. Results: On average 8 ± 1 concurrently active MUs were identified per contraction with the coefficient of variability (CoV) of inter-pulse interval below 0.15. At the start of the elbow flexion, MUs were discharging at approx. 9 ± 2 pulses per second (pps) (νγ = 15◦ /s), and 8 ± 1 pps (νγ = 7◦ /s). Their firing rates increased with the increasing flexion angle (up to 14 ± 2 pps). Slightly before the end of the flexion, a significant decrease of discharge rates was observed (from 14 ± 2 to 11 ± 3 pps). In the case of νγ = 5◦ /s, MU control strategies employed by both subjects differed substantially. Subject 1 demonstrated gradual decrease of discharge rates throughout the contraction (from 15 ± 3 to 11 ± 2 pps), accompanied with gradual, but substantial increase in the number of identified MUs (from 2 to 7). In Subject 2, the number of the identified MUs remained relatively constant throughout the contraction (7 ± 1 MUs), whereas their mean discharge rates decreased from initial 12 ± 2 to 10 ± 2 pps. Finally, MUAP shapes were reconstructed by the spike triggered averaging of different sEMG epochs. Significant innervation zone shift due to muscle contraction was observed in all the cases (Fig. 1) and was about 10 mm. Discussion: Although preliminary, the results of this study demonstrated the CKC method can readily be employed to reconstruct MU discharge patterns from sEMG in slow dynamic contractions. There are several open problems left for the future work. Firstly, tracking of small MUs over long time intervals proved to be difficult, especially in the presence of strong MUs or MUs with similar MUAP shapes. Secondly, MU reconstruction is still limited to contractions with angular velocities below 207 s. Finally, further experiments on a larger group of subjects are required to verify physiological results of this study.
Fig. 1. MUAPs of the MU 1, as detected by the central electrode column and reconstructed by the spike triggered averaging from different 2.5 s long signal epochs at different angles (γ) of the elbow joint (vγ = 15◦ /s).
Reference [1] Holobar A, Zazula D. Correlation-based approach to separation of surface electromyograms at low contraction forces. Med Biol Eng Comput 2004;42:487–96. doi:10.1016/j.gaitpost.2007.12.065 Functional reach and touch to evalutate perceptive impairment in diplegic infantile cerebral palsy L. Tersi 1,∗ , A. Ferrari 1 , A. Sghedoni 2 , E. Pedroni 2 , A. Ferrari 2 1
Department of Electronics, Computer Science and Systems (DEIS), Bologna University, Italy 2 U.O.C. Riabilitazione delle Gravi Disabilit` a dell’Et`a Evolutiva, Az. ASMN, Reggio Emilia, Italy
Introduction: In 30% of children with Diplegic Cerebral Palsy (CP), disability depends not only on motor aspects, but most of all on perceptual impairments. The central nervous system (CNS) cannot collect, elaborate and integrate redundant sensitive and sensorial information in order to obtain coherent representations of reality [1]. Clinical signs that are characteristic of the perceptive impairment consequent to movement and empty spaces intolerance seem to be correlated with a visual-kinestesic conflict because of the incoherence between visual and proprioceptive information [1]. We suggest an experimental set up of Functional Reach and Touch (FRT) to establish the presence and to measure the intensity of the perceptive disease by varying the exposition of patients to the empty space. Methods: Fourteen patients affected by Spastic Diplegia (SD) (aged 6–15 years) and five control subjects (aged 6–14 years) executed FRT while sitting on a height-adjustable chair (0.6 m—low; 1.0 m—high). Subjects were asked to stand steady for 10 s, and then, after hearing a whistle, to reach and touch a target (a ball with an accelerometer to sample the touching instant). A force plate under the chair acquired the centre of pressure (COP) trajectory. FRT was registered in 18 different positions/conditions, resulting from the combinations of: (i) distance to target equal to 120% (near) and 150% (far) of the arm-length (from the acromion to the tip of the medium finger); (ii) postero-omolateral (PO), antero-omolateral (AO) or antero-controlateral (AC) directions; (iii) high or low chair; (iv) presence/absence of perceptive facilitation ‘raised floor’ (highFAC): white sheet stretched at knee level (2.3 × 2.3 m2 ) hiding the empty space. Results: All control subjects but one (who failed at high far AC) managed to have a positive outcome (target reached). Patients with SD had a positive outcome in 79% of the near, and in 48% of the far trials. Out of the 14 SD, 8 clinically showed the perceptive impairment [1] (perceptual). Only the 17% of these latter obtained a positive outcome far versus the 87% of the remaining 6 (motor). The estimate of the movement smoothness (Normalized Jerk Score—NJS [2]) applied to COP trajectory showed that the highFAC
GAIPOS 2534 1–38
Abstracts of the 2007 SIAMOC congress / Gait & Posture xxx (2008) xxx–xxx
parameter, allows to get insight on the level of muscular fatigue during the repetitive task.
Reference [1] Farina D, et al., Noninvasive estimation of motor unit conduction velocity distribution using linear electrode arrays. IEEE Trans Biomed Eng 2000;47(March (3)):380–8. doi:10.1016/j.gaitpost.2007.12.064 Decomposition of surface electromyograms, recorded during slow dynamic contractions of biceps brachii muscle A. Holobar 1,∗ , M. Gazzoni 1 , D. Zazula 2 , R. Merletti 1 1 2
LISiN, Politecnico di Torino, Torino, Italy FEECS, University of Maribor, Maribor, Slovenia
Introduction: Dynamic surface electromyograms (sEMG) are important, but complex source of information. During the muscle contraction distances between the detection system and the motor units (MUs) change causing substantial changes in the detected MU action potentials (MUAPs). Recently, highly efficient Convolution Kernel Compensation (CKC) method was proposed for decomposition of high-density sEMG in isometric condition [1]. The aim of this study was to test the CKC ability to decompose dynamic sEMG signals, recorded during slow contractions of biceps brachii muscle. Methods: Two young male subjects participated to the experiment. Surface EMG signals were recorded with an adhesive two-dimensional array of 64 circular electrodes (radius of 1 mm) arranged in five columns and 13 lines. Inter-electrode distance was 8 mm. Recordings were performed in single differential configuration during isokinetic flexions and extensions of elbow joint in the sagittal plane. The elbow joint angle was measured by a potentiometric goniometer and ranged form 0◦ to 150◦ with angular velocities vγ of 15◦ /s, 7◦ /s and 5◦ /s. A weight of 1 kg was fixed at the wrist of the tested arm. Acquired sEMG signals were band-pass filtered (20–450 Hz, 3 dB), sampled at 2048 samples/s, and divided into 2.5 s long non-overlapping epochs. In order to limit the nonstationarity of MUAP shapes, each signal epoch was decomposed independently. Results: On average 8 ± 1 concurrently active MUs were identified per contraction with the coefficient of variability (CoV) of inter-pulse interval below 0.15. At the start of the elbow flexion, MUs were discharging at approx. 9 ± 2 pulses per second (pps) (νγ = 15◦ /s), and 8 ± 1 pps (νγ = 7◦ /s). Their firing rates increased with the increasing flexion angle (up to 14 ± 2 pps). Slightly before the end of the flexion, a significant decrease of discharge rates was observed (from 14 ± 2 to 11 ± 3 pps). In the case of νγ = 5◦ /s, MU control strategies employed by both subjects differed substantially. Subject 1 demonstrated gradual decrease of discharge rates throughout the contraction (from 15 ± 3 to 11 ± 2 pps), accompanied with gradual, but substantial increase in the number of identified MUs (from 2 to 7). In Subject 2, the number of the identified MUs remained relatively constant throughout the contraction (7 ± 1 MUs), whereas their mean discharge rates decreased from initial 12 ± 2 to 10 ± 2 pps. Finally, MUAP shapes were reconstructed by the spike triggered averaging of different sEMG epochs. Significant innervation zone shift due to muscle contraction was observed in all the cases (Fig. 1) and was about 10 mm. Discussion: Although preliminary, the results of this study demonstrated the CKC method can readily be employed to reconstruct MU discharge patterns from sEMG in slow dynamic contractions. There are several open problems left for the future work. Firstly, tracking of small MUs over long time intervals proved to be difficult, especially in the presence of strong MUs or MUs with similar MUAP shapes. Secondly, MU reconstruction is still limited to contractions with angular velocities below 207 s. Finally, further experiments on a larger group of subjects are required to verify physiological results of this study.
Fig. 1. MUAPs of the MU 1, as detected by the central electrode column and reconstructed by the spike triggered averaging from different 2.5 s long signal epochs at different angles (γ) of the elbow joint (vγ = 15◦ /s).
Reference [1] Holobar A, Zazula D. Correlation-based approach to separation of surface electromyograms at low contraction forces. Med Biol Eng Comput 2004;42:487–96. doi:10.1016/j.gaitpost.2007.12.065 Functional reach and touch to evalutate perceptive impairment in diplegic infantile cerebral palsy L. Tersi 1,∗ , A. Ferrari 1 , A. Sghedoni 2 , E. Pedroni 2 , A. Ferrari 2 1
Department of Electronics, Computer Science and Systems (DEIS), Bologna University, Italy 2 U.O.C. Riabilitazione delle Gravi Disabilit` a dell’Et`a Evolutiva, Az. ASMN, Reggio Emilia, Italy
Introduction: In 30% of children with Diplegic Cerebral Palsy (CP), disability depends not only on motor aspects, but most of all on perceptual impairments. The central nervous system (CNS) cannot collect, elaborate and integrate redundant sensitive and sensorial information in order to obtain coherent representations of reality [1]. Clinical signs that are characteristic of the perceptive impairment consequent to movement and empty spaces intolerance seem to be correlated with a visual-kinestesic conflict because of the incoherence between visual and proprioceptive information [1]. We suggest an experimental set up of Functional Reach and Touch (FRT) to establish the presence and to measure the intensity of the perceptive disease by varying the exposition of patients to the empty space. Methods: Fourteen patients affected by Spastic Diplegia (SD) (aged 6–15 years) and five control subjects (aged 6–14 years) executed FRT while sitting on a height-adjustable chair (0.6 m—low; 1.0 m—high). Subjects were asked to stand steady for 10 s, and then, after hearing a whistle, to reach and touch a target (a ball with an accelerometer to sample the touching instant). A force plate under the chair acquired the centre of pressure (COP) trajectory. FRT was registered in 18 different positions/conditions, resulting from the combinations of: (i) distance to target equal to 120% (near) and 150% (far) of the arm-length (from the acromion to the tip of the medium finger); (ii) postero-omolateral (PO), antero-omolateral (AO) or antero-controlateral (AC) directions; (iii) high or low chair; (iv) presence/absence of perceptive facilitation ‘raised floor’ (highFAC): white sheet stretched at knee level (2.3 × 2.3 m2 ) hiding the empty space. Results: All control subjects but one (who failed at high far AC) managed to have a positive outcome (target reached). Patients with SD had a positive outcome in 79% of the near, and in 48% of the far trials. Out of the 14 SD, 8 clinically showed the perceptive impairment [1] (perceptual). Only the 17% of these latter obtained a positive outcome far versus the 87% of the remaining 6 (motor). The estimate of the movement smoothness (Normalized Jerk Score—NJS [2]) applied to COP trajectory showed that the highFAC
GAIPOS 2534 1–38