Sensorimotor Time Delay Estimation by EMG Signal Processing in People Living with Spinal Cord Injury
Neuro mechanical time delay is inevitable in the sensorimotor control of the body due to sensory, transmission, signal processing and muscle activation delays. In essence, time delay reduces stabilization efficiency, leading to system instability (e.g., falls). For this reason, estimation of time de...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-01-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/23/3/1132 |
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| author | Seyed Mohammadreza Shokouhyan Mathias Blandeau Laura Wallard Thierry Marie Guerra Philippe Pudlo Dany H. Gagnon Franck Barbier |
| author_facet | Seyed Mohammadreza Shokouhyan Mathias Blandeau Laura Wallard Thierry Marie Guerra Philippe Pudlo Dany H. Gagnon Franck Barbier |
| author_sort | Seyed Mohammadreza Shokouhyan |
| collection | DOAJ |
| description | Neuro mechanical time delay is inevitable in the sensorimotor control of the body due to sensory, transmission, signal processing and muscle activation delays. In essence, time delay reduces stabilization efficiency, leading to system instability (e.g., falls). For this reason, estimation of time delay in patients such as people living with spinal cord injury (SCI) can help therapists and biomechanics to design more appropriate exercise or assistive technologies in the rehabilitation procedure. In this study, we aim to estimate the muscle onset activation in SCI people by four strategies on EMG data. Seven complete SCI individuals participated in this study, and they maintained their stability during seated balance after a mechanical perturbation exerting at the level of the third thoracic vertebra between the scapulas. EMG activity of eight upper limb muscles were recorded during the stability. Two strategies based on the simple filtering (first strategy) approach and TKEO technique (second strategy) in the time domain and two other approaches of cepstral analysis (third strategy) and power spectrum (fourth strategy) in the time–frequency domain were performed in order to estimate the muscle onset. The results demonstrated that the TKEO technique could efficiently remove the electrocardiogram (ECG) and motion artifacts compared with the simple classical filtering approach. However, the first and second strategies failed to find muscle onset in several trials, which shows the weakness of these two strategies. The time–frequency techniques (cepstral analysis and power spectrum) estimated longer activation onset compared with the other two strategies in the time domain, which we associate with lower-frequency movement in the maintaining of sitting stability. In addition, no correlation was found for the muscle activation sequence nor for the estimated delay value, which is most likely caused by motion redundancy and different stabilization strategies in each participant. The estimated time delay can be used in developing a sensory motor control model of the body. It not only can help therapists and biomechanics to understand the underlying mechanisms of body, but also can be useful in developing assistive technologies based on their stability mechanism. |
| first_indexed | 2024-03-11T09:26:30Z |
| format | Article |
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| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-11T09:26:30Z |
| publishDate | 2023-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-c8cbea49519a429e97bc98da80c88a3e2023-11-16T17:56:36ZengMDPI AGSensors1424-82202023-01-01233113210.3390/s23031132Sensorimotor Time Delay Estimation by EMG Signal Processing in People Living with Spinal Cord InjurySeyed Mohammadreza Shokouhyan0Mathias Blandeau1Laura Wallard2Thierry Marie Guerra3Philippe Pudlo4Dany H. Gagnon5Franck Barbier6University Polytechnique Hauts-de-France, CNRS, UMR 8201-LAMIH, F-59313 Valenciennes, FranceUniversity Polytechnique Hauts-de-France, CNRS, UMR 8201-LAMIH, F-59313 Valenciennes, FranceUniversity Polytechnique Hauts-de-France, CNRS, UMR 8201-LAMIH, F-59313 Valenciennes, FranceUniversity Polytechnique Hauts-de-France, CNRS, UMR 8201-LAMIH, F-59313 Valenciennes, FranceUniversity Polytechnique Hauts-de-France, CNRS, UMR 8201-LAMIH, F-59313 Valenciennes, FrancePathokinesiology Laboratory, Center for Interdisciplinary Research in Rehabilitation of Greater Montréal (CRIR), Montréal, QC H3S 1M9, CanadaUniversity Polytechnique Hauts-de-France, CNRS, UMR 8201-LAMIH, F-59313 Valenciennes, FranceNeuro mechanical time delay is inevitable in the sensorimotor control of the body due to sensory, transmission, signal processing and muscle activation delays. In essence, time delay reduces stabilization efficiency, leading to system instability (e.g., falls). For this reason, estimation of time delay in patients such as people living with spinal cord injury (SCI) can help therapists and biomechanics to design more appropriate exercise or assistive technologies in the rehabilitation procedure. In this study, we aim to estimate the muscle onset activation in SCI people by four strategies on EMG data. Seven complete SCI individuals participated in this study, and they maintained their stability during seated balance after a mechanical perturbation exerting at the level of the third thoracic vertebra between the scapulas. EMG activity of eight upper limb muscles were recorded during the stability. Two strategies based on the simple filtering (first strategy) approach and TKEO technique (second strategy) in the time domain and two other approaches of cepstral analysis (third strategy) and power spectrum (fourth strategy) in the time–frequency domain were performed in order to estimate the muscle onset. The results demonstrated that the TKEO technique could efficiently remove the electrocardiogram (ECG) and motion artifacts compared with the simple classical filtering approach. However, the first and second strategies failed to find muscle onset in several trials, which shows the weakness of these two strategies. The time–frequency techniques (cepstral analysis and power spectrum) estimated longer activation onset compared with the other two strategies in the time domain, which we associate with lower-frequency movement in the maintaining of sitting stability. In addition, no correlation was found for the muscle activation sequence nor for the estimated delay value, which is most likely caused by motion redundancy and different stabilization strategies in each participant. The estimated time delay can be used in developing a sensory motor control model of the body. It not only can help therapists and biomechanics to understand the underlying mechanisms of body, but also can be useful in developing assistive technologies based on their stability mechanism.https://www.mdpi.com/1424-8220/23/3/1132spinal cord injuryphysiological time delayTeager–Kaiser Energy Operatorcepstral analysispower spectrumEMG |
| spellingShingle | Seyed Mohammadreza Shokouhyan Mathias Blandeau Laura Wallard Thierry Marie Guerra Philippe Pudlo Dany H. Gagnon Franck Barbier Sensorimotor Time Delay Estimation by EMG Signal Processing in People Living with Spinal Cord Injury Sensors spinal cord injury physiological time delay Teager–Kaiser Energy Operator cepstral analysis power spectrum EMG |
| title | Sensorimotor Time Delay Estimation by EMG Signal Processing in People Living with Spinal Cord Injury |
| title_full | Sensorimotor Time Delay Estimation by EMG Signal Processing in People Living with Spinal Cord Injury |
| title_fullStr | Sensorimotor Time Delay Estimation by EMG Signal Processing in People Living with Spinal Cord Injury |
| title_full_unstemmed | Sensorimotor Time Delay Estimation by EMG Signal Processing in People Living with Spinal Cord Injury |
| title_short | Sensorimotor Time Delay Estimation by EMG Signal Processing in People Living with Spinal Cord Injury |
| title_sort | sensorimotor time delay estimation by emg signal processing in people living with spinal cord injury |
| topic | spinal cord injury physiological time delay Teager–Kaiser Energy Operator cepstral analysis power spectrum EMG |
| url | https://www.mdpi.com/1424-8220/23/3/1132 |
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