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Hong YNG, Roh J. Alterations in the preferred direction of individual arm muscle activation after stroke. Front Neurol 2023; 14:1280276. [PMID: 37808491 PMCID: PMC10556656 DOI: 10.3389/fneur.2023.1280276] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2023] [Accepted: 09/12/2023] [Indexed: 10/10/2023] Open
Abstract
Introduction Stroke survivors have challenges appropriately coordinating the multiple muscles, resulting in a deficit in motor control. Therefore, comprehending the mechanism underlying abnormal intermuscular coordination becomes crucial in developing effective rehabilitation strategies. Quantitative analyses have been employed at pairwise or multi-dimensional levels to understand the underlying mechanism of abnormal intermuscular coordination and its relationship to motor impairment. However, how alterations in individual muscle activation contribute to abnormal intermuscular coordination, motor impairment, and motor performance remains unclear. Thus, we investigated the alterations in the preferred direction of individual muscles after stroke and their relationship with stroke-induced changes in intermuscular coordination, clinical motor impairment, and qualities of motor performance during isometric force generation in the upper extremity. Methods Twenty-four stroke survivors and six age-matched controls were recruited and performed isometric force target matches while recording electromyographic signals from eight upper limb muscles. We determined the preferred activation direction of each muscle, evaluated abnormal intermuscular coordination through a muscle synergy analysis, assessed motor impairment using upper extremity Fugl-Meyer Assessment scores, and examined motor performance characteristics defined by force trajectory features. Results The post-stroke alterations in the preferred direction of the brachioradialis, anterior, middle, and posterior deltoid were correlated with the motor impairment level and attributed to the changes in muscle synergy characteristics. Only alterations in the preferred direction of the brachioradialis and posterior deltoid activation in forward-backward and upward-downward axes were associated with the qualities of isometric force generation, respectively. Discussion These findings imply that alterations in the preferred direction of individual muscle activation contribute to various aspects of motor deficit following stroke. This insight may serve as a foundation for the development of innovative stroke neurorehabilitation approaches that take into account specific attributes of individual muscle activation, including their preferred activation direction.
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Affiliation(s)
| | - Jinsook Roh
- Department of Biomedical Engineering, University of Houston, Houston, TX, United States
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2
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Guo L, Li ZW, Zhang H, Li SM, Zhang JH. Morphological ECG subtraction method for removing ECG artifacts from diaphragm EMG. Technol Health Care 2023; 31:333-345. [PMID: 37066934 DOI: 10.3233/thc-236029] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/18/2023]
Abstract
BACKGROUND Diaphragmatic electromyographic (EMGdi) is a helpful method to reflect the respiratory center's activity visually. However, the electrocardiogram (ECG) severely affected its weakness, limiting its use. OBJECTIVE To remove the ECG artifact from the EMGdi, we designed a Morphological ECG subtraction method (MES) based on three steps: 1) ECG localization, 2) morphological tracking, and 3) ECG subtractor. METHODS We evaluated the MES method against the wavelet-based dual-threshold and stationary wavelet filters using visual and frequency-domain characteristics (median frequency and power ratio). RESULTS The results show that the MES method can preserve the features of the original diaphragm signal for both surface diaphragm signal (SEMGdi) and clinical collection of diaphragm signal (EMGdi_clinic), and it is more effective than the wavelet-based dual-threshold and stationary wavelet filtering methods. CONCLUSION The MES method is more effective than other methods. This technique may improve respiratory monitoring and assisted ventilation in patients with respiratory diseases.
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Affiliation(s)
- Liang Guo
- School of Electrical and Information Engineering, South China Normal University, Foshan, Guangdong, China
- School of Physics and Telecommunications Engineering, South China Normal University, Guangzhou, Guangdong, China
| | - Zhi-Wei Li
- School of Electrical and Information Engineering, South China Normal University, Foshan, Guangdong, China
- School of Physics and Telecommunications Engineering, South China Normal University, Guangzhou, Guangdong, China
| | - Han Zhang
- School of Electrical and Information Engineering, South China Normal University, Foshan, Guangdong, China
- School of Physics and Telecommunications Engineering, South China Normal University, Guangzhou, Guangdong, China
| | - Shuang-Miao Li
- School of Electrical and Information Engineering, South China Normal University, Foshan, Guangdong, China
- School of Physics and Telecommunications Engineering, South China Normal University, Guangzhou, Guangdong, China
| | - Jian-Heng Zhang
- The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, China
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3
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Boyer M, Bouyer L, Roy JS, Campeau-Lecours A. Reducing Noise, Artifacts and Interference in Single-Channel EMG Signals: A Review. SENSORS (BASEL, SWITZERLAND) 2023; 23:2927. [PMID: 36991639 PMCID: PMC10059683 DOI: 10.3390/s23062927] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/30/2023] [Revised: 02/22/2023] [Accepted: 03/01/2023] [Indexed: 06/19/2023]
Abstract
Electromyography (EMG) is gaining importance in many research and clinical applications, including muscle fatigue detection, control of robotic mechanisms and prostheses, clinical diagnosis of neuromuscular diseases and quantification of force. However, EMG signals can be contaminated by various types of noise, interference and artifacts, leading to potential data misinterpretation. Even assuming best practices, the acquired signal may still contain contaminants. The aim of this paper is to review methods employed to reduce the contamination of single channel EMG signals. Specifically, we focus on methods which enable a full reconstruction of the EMG signal without loss of information. This includes subtraction methods used in the time domain, denoising methods performed after the signal decomposition and hybrid approaches that combine multiple methods. Finally, this paper provides a discussion on the suitability of the individual methods based on the type of contaminant(s) present in the signal and the specific requirements of the application.
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Affiliation(s)
- Marianne Boyer
- Department of Mechanical Engineering, Université Laval, Québec, QC G1V 0A6, Canada
- Centre for Interdisciplinary Research in Rehabilitation and Social Integration, CIUSSS de la Capitale-Nationale, Québec, QC G1M 2S8, Canada
| | - Laurent Bouyer
- Centre for Interdisciplinary Research in Rehabilitation and Social Integration, CIUSSS de la Capitale-Nationale, Québec, QC G1M 2S8, Canada
- Department of Rehabilitation, Université Laval, Québec, QC G1 V0A, Canada
| | - Jean-Sébastien Roy
- Centre for Interdisciplinary Research in Rehabilitation and Social Integration, CIUSSS de la Capitale-Nationale, Québec, QC G1M 2S8, Canada
- Department of Rehabilitation, Université Laval, Québec, QC G1 V0A, Canada
| | - Alexandre Campeau-Lecours
- Department of Mechanical Engineering, Université Laval, Québec, QC G1V 0A6, Canada
- Centre for Interdisciplinary Research in Rehabilitation and Social Integration, CIUSSS de la Capitale-Nationale, Québec, QC G1M 2S8, Canada
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Seo G, Lee SW, Beer RF, Alamri A, Wu YN, Raghavan P, Rymer WZ, Roh J. Alterations in motor modules and their contribution to limitations in force control in the upper extremity after stroke. Front Hum Neurosci 2022; 16:937391. [PMID: 35967001 PMCID: PMC9365968 DOI: 10.3389/fnhum.2022.937391] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2022] [Accepted: 07/07/2022] [Indexed: 11/13/2022] Open
Abstract
The generation of isometric force at the hand can be mediated by activating a few motor modules. Stroke induces alterations in motor modules underlying steady-state isometric force generation in the human upper extremity (UE). However, how the altered motor modules impact task performance (force production) remains unclear as stroke survivors develop and converge to the three-dimensional (3D) target force. Thus, we tested whether stroke-specific motor modules would be activated from the onset of force generation and also examined how alterations in motor modules would induce changes in force representation. During 3D isometric force development, electromyographic (EMG) signals were recorded from eight major elbow and shoulder muscles in the paretic arm of 10 chronic hemispheric stroke survivors and both arms of six age-matched control participants. A non-negative matrix factorization algorithm identified motor modules in four different time windows: three “exploratory” force ramping phases (Ramps 1–3; 0–33%, 33–67%, and 67–100% of target force magnitude, respectively) and the stable force match phase (Hold). Motor module similarity and between-force coupling were examined by calculating the scalar product and Pearson correlation across the phases. To investigate the association between the end-point force representation and the activation of the motor modules, principal component analysis (PCA) and multivariate multiple linear regression analyses were applied. In addition, the force components regressed on the activation profiles of motor modules were utilized to model the feasible force direction. Both stroke and control groups developed exploratory isometric forces with a non-linear relationship between EMG and force. During the force matching, only the stroke group showed abnormal between-force coupling in medial-lateral and backward-forward and medial-lateral and downward-upward directions. In each group, the same motor modules, including the abnormal deltoid module in stroke survivors, were expressed from the beginning of force development instead of emerging during the force exploration. The PCA and the multivariate multiple linear regression analyses showed that alterations in motor modules were associated with abnormal between-force coupling and limited feasible force direction after stroke. Overall, these results suggest that alterations in intermuscular coordination contribute to the abnormal end-point force control under isometric conditions in the UE after stroke.
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Affiliation(s)
- Gang Seo
- Department of Biomedical Engineering, University of Houston, Houston, TX, United States
| | - Sang Wook Lee
- Department of Biomedical Engineering, Catholic University of America, Washington, DC, United States
- Center for Applied Biomechanics and Rehabilitation Research, MedStar National Rehabilitation Hospital, Washington, DC, United States
- Department of Mechanical Engineering, Korea Advanced Institute of Science and Technology, Daejeon, South Korea
| | - Randall F. Beer
- Department of Physical Medicine and Rehabilitation, Northwestern University, Chicago, IL, United States
| | - Amani Alamri
- Department of Biology, Temple University, Philadelphia, PA, United States
| | - Yi-Ning Wu
- Department of Physical Therapy and Kinesiology, University of Massachusetts Lowell, Lowell, MA, United States
| | - Preeti Raghavan
- Department of Physical Medicine and Rehabilitation, Johns Hopkins University, Baltimore, MD, United States
| | - William Z. Rymer
- Department of Physical Medicine and Rehabilitation, Northwestern University, Chicago, IL, United States
- Shirley Ryan AbilityLab, Chicago, IL, United States
| | - Jinsook Roh
- Department of Biomedical Engineering, University of Houston, Houston, TX, United States
- *Correspondence: Jinsook Roh,
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Gu X, Ren S, Shi Y, Li X, Guo Z, Zhao X, Mao Z, Cai M, Xie F. Evaluation of Correlation between Surface Diaphragm Electromyography and Airflow Using Fixed Sample Entropy in Healthy Subjects. IEEE Trans Neural Syst Rehabil Eng 2022; 30:238-250. [PMID: 35041610 DOI: 10.1109/tnsre.2022.3144412] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
In clinic, the acquisition of airflow with nasal prongs, masks, thermistor to monitor respiratory function is more uncomfortable and inconvenience than surface diaphragm electromyography (EMGdi) using electrode pads. The EMGdi with strong electrocardiograph (ECG) interference affect the extraction of its characteristic information. In this work, surface EMGdi and airflow signals of 20 subjects were collected under 5 incremental inspiratory threshold loading protocols from quiet breathing to maximum forced breathing. First, we filtered out the ECG interference in EMGdi based on the combination of stationary wavelet transform and the positioning of ECG to obtain pure EMGdi (EMGdip). Second, the Spearman's rank correlation coefficients between EMGdi and EMGdip quantified by time series fixed sample entropy (fSampEn), root mean square (RMS), and envelope were compared to verify the robustness of the fSampEn to ECG. A comparative analysis of correlation between fSampEn of EMGdi and inspiratory airflow and the correlation between envelope of EMGdip (EMGdie) and inspiratory airflow found that there was no significant difference between the two, indicating the feasibility of using fSampEn to predict airflow. Moreover, fSampEn of EMGdi was used as characteristic parameter to build a quantitative relationship with the airflow by polynomial regression analysis. Mean coefficient of determination of all subjects in any breathing state is greater than 0.88. Finally, nonlinear programming method was used to solve a universal fitting coefficient between fSampEn of EMGdi and airflow for each subject to further evaluate the possibility of using surface EMGdi to monitor and control respiratory activity.
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Moltó IN, Albiach JP, Amer-Cuenca JJ, Segura-Ortí E, Gabriel W, Martínez-Gramage J. Wearable Sensors Detect Differences between the Sexes in Lower Limb Electromyographic Activity and Pelvis 3D Kinematics during Running. SENSORS (BASEL, SWITZERLAND) 2020; 20:E6478. [PMID: 33198427 PMCID: PMC7697594 DOI: 10.3390/s20226478] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/13/2020] [Revised: 11/09/2020] [Accepted: 11/10/2020] [Indexed: 12/18/2022]
Abstract
Each year, 50% of runners suffer from injuries. Consequently, more studies are being published about running biomechanics; these studies identify factors that can help prevent injuries. Scientific evidence suggests that recreational runners should use personalized biomechanical training plans, not only to improve their performance, but also to prevent injuries caused by the inability of amateur athletes to tolerate increased loads, and/or because of poor form. This study provides an overview of the different normative patterns of lower limb muscle activation and articular ranges of the pelvis during running, at self-selected speeds, in men and women. METHODS 38 healthy runners aged 18 to 49 years were included in this work. We examined eight muscles by applying two wearable superficial electromyography sensors and an inertial sensor for three-dimensional (3D) pelvis kinematics. RESULTS the largest differences were obtained for gluteus maximus activation in the first double float phase (p = 0.013) and second stance phase (p = 0.003), as well as in the gluteus medius in the second stance phase (p = 0.028). In both cases, the activation distribution was more homogeneous in men and presented significantly lower values than those obtained for women. In addition, there was a significantly higher percentage of total vastus medialis activation in women throughout the running cycle with the median (25th-75th percentile) for women being 12.50% (9.25-14) and 10% (9-12) for men. Women also had a greater range of pelvis rotation during running at self-selected speeds (p = 0.011). CONCLUSIONS understanding the differences between men and women, in terms of muscle activation and pelvic kinematic values, could be especially useful to allow health professionals detect athletes who may be at risk of injury.
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Affiliation(s)
- Iván Nacher Moltó
- Department of Physiotherapy, Universidad Cardenal Herrera-CEU, CEU Universities, 46113 Valencia, Spain; (J.J.A.-C.); (E.S.-O.); (J.M.-G.)
| | - Juan Pardo Albiach
- Embedded Systems and Artificial Intelligence Group, Universidad Cardenal Herrera-CEU, CEU Universities, 46113 Alfara del Patriarca, Spain;
| | - Juan José Amer-Cuenca
- Department of Physiotherapy, Universidad Cardenal Herrera-CEU, CEU Universities, 46113 Valencia, Spain; (J.J.A.-C.); (E.S.-O.); (J.M.-G.)
| | - Eva Segura-Ortí
- Department of Physiotherapy, Universidad Cardenal Herrera-CEU, CEU Universities, 46113 Valencia, Spain; (J.J.A.-C.); (E.S.-O.); (J.M.-G.)
| | - Willig Gabriel
- Laboratorio de Investigaciones Biomecánicas, Cátedra de Anatomía Funcional y Biomecánica, Universidad de Buenos Aires, Buenos Aires 1107, Argentina;
| | - Javier Martínez-Gramage
- Department of Physiotherapy, Universidad Cardenal Herrera-CEU, CEU Universities, 46113 Valencia, Spain; (J.J.A.-C.); (E.S.-O.); (J.M.-G.)
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7
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van Leuteren RW, Hutten GJ, de Waal CG, Dixon P, van Kaam AH, de Jongh FH. Processing transcutaneous electromyography measurements of respiratory muscles, a review of analysis techniques. J Electromyogr Kinesiol 2019; 48:176-186. [PMID: 31401341 DOI: 10.1016/j.jelekin.2019.07.014] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2019] [Revised: 07/23/2019] [Accepted: 07/27/2019] [Indexed: 11/28/2022] Open
Abstract
Transcutaneous electromyography (tc-EMG) has been used to measure the electrical activity of respiratory muscles during inspiration in various studies. Processing the raw tc-EMG signal of these inspiratory muscles has shown to be difficult as baseline noise, cardiac interference, cross-talk and motion artefacts can influence the signal quality. In this review we will discuss the most important sources of signal noise in tc-EMG of respiratory muscles and the various techniques described to suppress or reduce this signal noise. Furthermore, we will elaborate on the options available to develop or improve an algorithm that can be used to guide the approach for analysis of tc-EMG signals of inspiratory muscles in future research.
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Affiliation(s)
- R W van Leuteren
- Department of Neonatology, Emma Children's Hospital, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands.
| | - G J Hutten
- Department of Neonatology, Emma Children's Hospital, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands; Department of Neonatology, Emma Children's Hospital, Amsterdam UMC, Vrije Universiteit, Amsterdam, the Netherlands
| | - C G de Waal
- Department of Neonatology, Emma Children's Hospital, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - P Dixon
- Vyaire Medical, Basingstoke, United Kingdom
| | - A H van Kaam
- Department of Neonatology, Emma Children's Hospital, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands; Department of Neonatology, Emma Children's Hospital, Amsterdam UMC, Vrije Universiteit, Amsterdam, the Netherlands
| | - F H de Jongh
- Department of Neonatology, Emma Children's Hospital, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands; Faculty of Science and Technology, University of Twente, Enschede, the Netherlands
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8
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Costa Junior JD, de Seixas JM, Miranda de Sá AMFL. A template subtraction method for reducing electrocardiographic artifacts in EMG signals of low intensity. Biomed Signal Process Control 2019. [DOI: 10.1016/j.bspc.2018.09.004] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/28/2022]
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9
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Nougarou F, Massicotte D, Descarreaux M. Efficient procedure to remove ECG from sEMG with limited deteriorations: Extraction, quasi-periodic detection and cancellation. Biomed Signal Process Control 2018. [DOI: 10.1016/j.bspc.2017.07.019] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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10
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Sbrollini A, Strazza A, Candelaresi S, Marcantoni I, Morettini M, Fioretti S, Di Nardo F, Burattini L. Surface electromyography low-frequency content: Assessment in isometric conditions after electrocardiogram cancellation by the Segmented-Beat Modulation Method. INFORMATICS IN MEDICINE UNLOCKED 2018. [DOI: 10.1016/j.imu.2018.10.006] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/28/2022] Open
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Jensen VN, Romer SH, Turner SM, Crone SA. Repeated Measurement of Respiratory Muscle Activity and Ventilation in Mouse Models of Neuromuscular Disease. J Vis Exp 2017. [PMID: 28448001 DOI: 10.3791/55599] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022] Open
Abstract
Accessory respiratory muscles help to maintain ventilation when diaphragm function is impaired. The following protocol describes a method for repeated measurements over weeks or months of accessory respiratory muscle activity while simultaneously measuring ventilation in a non-anesthetized, freely behaving mouse. The technique includes the surgical implantation of a radio transmitter and the insertion of electrode leads into the scalene and trapezius muscles to measure the electromyogram activity of these inspiratory muscles. Ventilation is measured by whole-body plethysmography, and animal movement is assessed by video and is synchronized with electromyogram activity. Measurements of muscle activity and ventilation in a mouse model of amyotrophic lateral sclerosis are presented to show how this tool can be used to investigate how respiratory muscle activity changes over time and to assess the impact of muscle activity on ventilation. The described methods can easily be adapted to measure the activity of other muscles or to assess accessory respiratory muscle activity in additional mouse models of disease or injury.
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Affiliation(s)
| | | | - Sarah M Turner
- Division of Neurosurgery, Cincinnati Children's Hospital Medical Center
| | - Steven A Crone
- Division of Neurosurgery, Cincinnati Children's Hospital Medical Center;
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12
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Barrios-Muriel J, Romero F, Alonso FJ, Gianikellis K. A simple SSA-based de-noising technique to remove ECG interference in EMG signals. Biomed Signal Process Control 2016. [DOI: 10.1016/j.bspc.2016.06.001] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
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13
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Sjödahl J, Gutke A, Ghaffari G, Strömberg T, Öberg B. Response of the muscles in the pelvic floor and the lower lateral abdominal wall during the Active Straight Leg Raise in women with and without pelvic girdle pain: An experimental study. Clin Biomech (Bristol, Avon) 2016; 35:49-55. [PMID: 27128765 DOI: 10.1016/j.clinbiomech.2016.04.007] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/27/2015] [Revised: 02/09/2016] [Accepted: 04/12/2016] [Indexed: 02/07/2023]
Abstract
BACKGROUND The relationship between activation of the stabilizing muscles of the lumbopelvic region during the Active Straight Leg Raise test and pelvic girdle pain remains unknown. Therefore, the aim was to examine automatic contractions in relation to pre-activation in the muscles of the pelvic floor and the lower lateral abdominal wall during leg lifts, performed as the Active Straight Leg Raise test, in women with and without persistent postpartum pelvic girdle pain. METHODS Sixteen women with pelvic girdle pain and eleven pain-free women performed contralateral and ipsilateral leg lifts, while surface electromyographic activity was recorded from the pelvic floor and unilaterally from the lower lateral abdominal wall. As participants performed leg lifts onset time was calculated as the time from increased muscle activity to leg lift initiation. FINDINGS No significant differences were observed between the groups during the contralateral leg lift. During the subsequent ipsilateral leg lift, pre-activation in the pelvic floor muscles was observed in 36% of women with pelvic girdle pain and in 91% of pain-free women (P=0.01). Compared to pain-free women, women with pelvic girdle pain also showed significantly later onset time in both the pelvic floor muscles (P=0.01) and the muscles of the lower lateral abdominal wall (P<0.01). INTERPRETATION We suggest that disturbed motor activation patterns influence women's ability to stabilize the pelvis during leg lifts. This could be linked to provocation of pain during repeated movements.
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Affiliation(s)
- Jenny Sjödahl
- Department of Medical and Health Sciences, Division of Physiotherapy, Linköping University, Linköping, Sweden.
| | - Annelie Gutke
- Department of Medical and Health Sciences, Division of Physiotherapy, Linköping University, Linköping, Sweden; Institute of Neuroscience and Physiology, Department of Health and Rehabilitation, Division of Physiotherapy, University of Gothenburg, Sweden.
| | - Ghazaleh Ghaffari
- Department of Biomedical Engineering, Linköping University, Linköping, Sweden.
| | - Tomas Strömberg
- Department of Biomedical Engineering, Linköping University, Linköping, Sweden.
| | - Birgitta Öberg
- Department of Medical and Health Sciences, Division of Physiotherapy, Linköping University, Linköping, Sweden.
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Agostinelli A, Sbrollini A, Giuliani C, Fioretti S, Nardo FD, Burattini L. Segmented beat modulation method for electrocardiogram estimation from noisy recordings. Med Eng Phys 2016; 38:560-8. [PMID: 27118623 DOI: 10.1016/j.medengphy.2016.03.011] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2015] [Revised: 02/25/2016] [Accepted: 03/28/2016] [Indexed: 11/28/2022]
Abstract
Clinical utility of an electrocardiogram (ECG) affected by too high levels of noise such as baseline wanders, electrode motion artifacts, muscular artifacts and power-line interference may be jeopardized if not opportunely processed. Template-based techniques have been proposed for ECG estimation from noisy recordings, but usually they do not reproduce physiological ECG variability, which, however, provides clinically useful information on the patient's health. Thus, this study proposes the Segmented-Beat Modulation Method (SBMM) as a new template-based filtering procedure able to reproduce ECG variability, and assesses SBMM robustness to the aforementioned noises in comparison to a standard template method (STM). SBMM performs a unique ECG segmentation into QRS segment and TUP segment, and successively modulates/demodulates (by stretching or compressing) the former segments in order to adaptively adjust each estimated beat to its original morphology and duration. Consequently, SBMM estimates ECG with significantly lower estimation errors than STM when applied to recordings affected by various levels of the considered noises (SBMM: 176-232µV and 79-499µV; STM: 215-496µV and 93-1056µV, for QRS and TUP segments, respectively). Thus, SBMM is able to reproduce ECG variability and is more robust to noise than STM.
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Affiliation(s)
- Angela Agostinelli
- Department of Information Engineering, Università Politecnica delle Marche, Ancona, Italy.
| | - Agnese Sbrollini
- Department of Information Engineering, Università Politecnica delle Marche, Ancona, Italy.
| | - Corrado Giuliani
- Department of Information Engineering, Università Politecnica delle Marche, Ancona, Italy.
| | - Sandro Fioretti
- Department of Information Engineering, Università Politecnica delle Marche, Ancona, Italy.
| | - Francesco Di Nardo
- Department of Information Engineering, Università Politecnica delle Marche, Ancona, Italy.
| | - Laura Burattini
- Department of Information Engineering, Università Politecnica delle Marche, Ancona, Italy.
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15
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Niegowski M, Zivanovic M. Wavelet-based unsupervised learning method for electrocardiogram suppression in surface electromyograms. Med Eng Phys 2016; 38:248-56. [DOI: 10.1016/j.medengphy.2015.12.008] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2015] [Revised: 10/26/2015] [Accepted: 12/20/2015] [Indexed: 11/28/2022]
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16
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Abbaspour S, Fallah A, Lindén M, Gholamhosseini H. A novel approach for removing ECG interferences from surface EMG signals using a combined ANFIS and wavelet. J Electromyogr Kinesiol 2015; 26:52-9. [PMID: 26643795 DOI: 10.1016/j.jelekin.2015.11.003] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2015] [Revised: 10/13/2015] [Accepted: 11/10/2015] [Indexed: 11/17/2022] Open
Abstract
In recent years, the removal of electrocardiogram (ECG) interferences from electromyogram (EMG) signals has been given large consideration. Where the quality of EMG signal is of interest, it is important to remove ECG interferences from EMG signals. In this paper, an efficient method based on a combination of adaptive neuro-fuzzy inference system (ANFIS) and wavelet transform is proposed to effectively eliminate ECG interferences from surface EMG signals. The proposed approach is compared with other common methods such as high-pass filter, artificial neural network, adaptive noise canceller, wavelet transform, subtraction method and ANFIS. It is found that the performance of the proposed ANFIS-wavelet method is superior to the other methods with the signal to noise ratio and relative error of 14.97dB and 0.02 respectively and a significantly higher correlation coefficient (p<0.05).
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Affiliation(s)
- Sara Abbaspour
- School of Innovation, Design and Engineering, Mälardalen University, 721 23, Högskoleplan 1, Västerås, Sweden.
| | - Ali Fallah
- Department of Biomedical Engineering, Amirkabir University of Technology, 424 Hafez Ave, Tehran, Iran
| | - Maria Lindén
- School of Innovation, Design and Engineering, Mälardalen University, 721 23, Högskoleplan 1, Västerås, Sweden
| | - Hamid Gholamhosseini
- School of Engineering, Computing and Mathematical Sciences, Auckland University of Technology, 1142 Auckland, New Zealand
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Niegowski M, Zivanovic M. ECG-EMG separation by using enhanced non-negative matrix factorization. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2015; 2014:4212-5. [PMID: 25570921 DOI: 10.1109/embc.2014.6944553] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
We present a novel approach to single-channel ECG-EMG signal separation by means of enhanced non-negative matrix factorization (NMF). The approach is based on a linear decomposition of the input signal spectrogram in two non-negative components, which represent the ECG and EMG spectrogram estimates. As ECG and EMG have different time-frequency (TF) patterns, the decomposition is enhanced by reshaping the input mixture spectrogram in order to emphasize a sparse ECG over a noisy-like EMG. Moreover, initialization of the classical NMF algorithm with accurately designed ECG and EMG structures further increases its separation performance. The comparative study suggests that the proposed method outperforms two reference methods for both synthetic and real signal mixture scenarios.
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18
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Petrović M, Petrović J, Simić G, Ilić I, Danicić A, Vukcević M, Bojović B, Hadzievski L, Allsop T, Webb DJ. A new method for respiratory-volume monitoring based on long-period fibre gratings. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2015; 2013:2660-3. [PMID: 24110274 DOI: 10.1109/embc.2013.6610087] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Respiratory-volume monitoring is an indispensable part of mechanical ventilation. Here we present a new method of the respiratory-volume measurement based on a single fibre-optical long-period sensor of bending and the correlation between torso curvature and lung volume. Unlike the commonly used air-flow based measurement methods the proposed sensor is drift-free and immune to air-leaks. In the paper, we explain the working principle of sensors, a two-step calibration-test measurement procedure and present results that establish a linear correlation between the change in the local thorax curvature and the change of the lung volume. We also discuss the advantages and limitations of these sensors with respect to the current standards.
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19
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Qiu S, Feng J, Xu R, Xu J, Wang K, He F, Qi H, Zhao X, Zhou P, Zhang L, Ming D. A Stimulus Artifact Removal Technique for SEMG Signal Processing During Functional Electrical Stimulation. IEEE Trans Biomed Eng 2015; 62:1959-68. [DOI: 10.1109/tbme.2015.2407834] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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20
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Effects of electrocardiography contamination and comparison of ECG removal methods on upper trapezius electromyography recordings. J Electromyogr Kinesiol 2014; 24:902-9. [DOI: 10.1016/j.jelekin.2014.08.003] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2013] [Revised: 08/05/2014] [Accepted: 08/18/2014] [Indexed: 11/23/2022] Open
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21
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Petrović MD, Petrovic J, Daničić A, Vukčević M, Bojović B, Hadžievski L, Allsop T, Lloyd G, Webb DJ. Non-invasive respiratory monitoring using long-period fiber grating sensors. BIOMEDICAL OPTICS EXPRESS 2014; 5:1136-44. [PMID: 24761295 PMCID: PMC3986006 DOI: 10.1364/boe.5.001136] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/25/2013] [Revised: 01/18/2014] [Accepted: 02/19/2014] [Indexed: 05/06/2023]
Abstract
In non-invasive ventilation, continuous monitoring of respiratory volumes is essential. Here, we present a method for the measurement of respiratory volumes by a single fiber-grating sensor of bending and provide the proof-of-principle by applying a calibration-test measurement procedure on a set of 18 healthy volunteers. Results establish a linear correlation between a change in lung volume and the corresponding change in a local thorax curvature. They also show good sensor accuracy in measurements of tidal and minute respiratory volumes for different types of breathing. The proposed technique does not rely on the air flow through an oronasal mask or the observation of chest movement by a clinician, which distinguishes it from the current clinical practice.
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Affiliation(s)
- M. D. Petrović
- Vinča Institute of Nuclear Sciences,University of Belgrade, Mike Petrovića Alasa 12-14, 11000 Belgrade, Serbia
| | - J. Petrovic
- Vinča Institute of Nuclear Sciences,University of Belgrade, Mike Petrovića Alasa 12-14, 11000 Belgrade, Serbia
| | - A. Daničić
- Vinča Institute of Nuclear Sciences,University of Belgrade, Mike Petrovića Alasa 12-14, 11000 Belgrade, Serbia
| | - M. Vukčević
- School of Medicine, University of Belgrade, Dr Subotića 8, 11000 Belgrade, Serbia
| | - B. Bojović
- Vinča Institute of Nuclear Sciences,University of Belgrade, Mike Petrovića Alasa 12-14, 11000 Belgrade, Serbia
| | - Lj. Hadžievski
- Vinča Institute of Nuclear Sciences,University of Belgrade, Mike Petrovića Alasa 12-14, 11000 Belgrade, Serbia
| | - T. Allsop
- Aston Institute of Photonic Technologies, Aston Triangle, B4 7ET Birmingham, UK
| | - G. Lloyd
- Moog Insensys LTD, Ocean House, Whittle Avenue, Segensworth West, Fareham, P015 5SX, UK
| | - D. J. Webb
- Aston Institute of Photonic Technologies, Aston Triangle, B4 7ET Birmingham, UK
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22
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FU RONGRONG, WANG HONG. DETECTION OF DRIVING FATIGUE BY USING NONCONTACT EMG AND ECG SIGNALS MEASUREMENT SYSTEM. Int J Neural Syst 2014; 24:1450006. [DOI: 10.1142/s0129065714500063] [Citation(s) in RCA: 79] [Impact Index Per Article: 7.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
Driver fatigue can be detected by constructing a discriminant mode using some features obtained from physiological signals. There exist two major challenges of this kind of methods. One is how to collect physiological signals from subjects while they are driving without any interruption. The other is to find features of physiological signals that are of corresponding change with the loss of attention caused by driver fatigue. Driving fatigue is detected based on the study of surface electromyography (EMG) and electrocardiograph (ECG) during the driving period. The noncontact data acquisition system was used to collect physiological signals from the biceps femoris of each subject to tackle the first challenge. Fast independent component analysis (FastICA) and digital filter were utilized to process the original signals. Based on the statistical analysis results given by Kolmogorov–Smirnov Z test, the peak factor of EMG (p < 0.001) and the maximum of the cross-relation curve of EMG and ECG (p < 0.001) were selected as the combined characteristic to detect fatigue of drivers. The discriminant criterion of fatigue was obtained from the training samples by using Mahalanobis distance, and then the average classification accuracy was given by 10-fold cross-validation. The results showed that the method proposed in this paper can give well performance in distinguishing the normal state and fatigue state. The noncontact, onboard vehicle drivers' fatigue detection system was developed to reduce fatigue-related risks.
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Affiliation(s)
- RONGRONG FU
- Laboratory of Bio-Mechatronic Engineering, School of Mechanical Engineering and Automation, Northeastern University, Shenyang 110189, P.R. China
| | - HONG WANG
- Laboratory of Bio-Mechatronic Engineering, School of Mechanical Engineering and Automation, Northeastern University, Shenyang 110189, P.R. China
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23
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Nitzken M, Bajaj N, Aslan S, Gimel'farb G, El-Baz A, Ovechkin A. Local Wavelet-Based Filtering of Electromyographic Signals to Eliminate the Electrocardiographic-Induced Artifacts in Patients with Spinal Cord Injury. ACTA ACUST UNITED AC 2013; 6. [PMID: 24307920 DOI: 10.4236/jbise.2013.67a2001] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
Abstract
Surface Electromyography (EMG) is a standard method used in clinical practice and research to assess motor function in order to help with the diagnosis of neuromuscular pathology in human and animal models. EMG recorded from trunk muscles involved in the activity of breathing can be used as a direct measure of respiratory motor function in patients with spinal cord injury (SCI) or other disorders associated with motor control deficits. However, EMG potentials recorded from these muscles are often contaminated with heart-induced electrocardiographic (ECG) signals. Elimination of these artifacts plays a critical role in the precise measure of the respiratory muscle electrical activity. This study was undertaken to find an optimal approach to eliminate the ECG artifacts from EMG recordings. Conventional global filtering can be used to decrease the ECG-induced artifact. However, this method can alter the EMG signal and changes physiologically relevant information. We hypothesize that, unlike global filtering, localized removal of ECG artifacts will not change the original EMG signals. We develop an approach to remove the ECG artifacts without altering the amplitude and frequency components of the EMG signal by using an externally recorded ECG signal as a mask to locate areas of the ECG spikes within EMG data. These segments containing ECG spikes were decomposed into 128 sub-wavelets by a custom-scaled Morlet Wavelet Transform. The ECG-related sub-wavelets at the ECG spike location were removed and a de-noised EMG signal was reconstructed. Validity of the proposed method was proven using mathematical simulated synthetic signals and EMG obtained from SCI patients. We compare the Root-mean Square Error and the Relative Change in Variance between this method, global, notch and adaptive filters. The results show that the localized wavelet-based filtering has the benefit of not introducing error in the native EMG signal and accurately removing ECG artifacts from EMG signals.
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Affiliation(s)
- Matthew Nitzken
- BioImaging laboratory, Bioengineering Department, University of Louisville, Louisville, KY 40292, USA
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24
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Zivanovic M, Gonzalez-Izal M. Nonstationary Harmonic Modeling for ECG Removal in Surface EMG Signals. IEEE Trans Biomed Eng 2012; 59:1633-40. [DOI: 10.1109/tbme.2012.2191287] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
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25
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Willigenburg NW, Daffertshofer A, Kingma I, van Dieën JH. Removing ECG contamination from EMG recordings: A comparison of ICA-based and other filtering procedures. J Electromyogr Kinesiol 2012; 22:485-93. [PMID: 22296869 DOI: 10.1016/j.jelekin.2012.01.001] [Citation(s) in RCA: 59] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2011] [Revised: 12/07/2011] [Accepted: 01/03/2012] [Indexed: 11/26/2022] Open
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