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Ma S, Mendez Guerra I, Caillet AH, Zhao J, Clarke AK, Maksymenko K, Deslauriers-Gauthier S, Sheng X, Zhu X, Farina D. NeuroMotion: Open-source platform with neuromechanical and deep network modules to generate surface EMG signals during voluntary movement. PLoS Comput Biol 2024; 20:e1012257. [PMID: 38959262 PMCID: PMC11251629 DOI: 10.1371/journal.pcbi.1012257] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2023] [Revised: 07/16/2024] [Accepted: 06/15/2024] [Indexed: 07/05/2024] Open
Abstract
Neuromechanical studies investigate how the nervous system interacts with the musculoskeletal (MSK) system to generate volitional movements. Such studies have been supported by simulation models that provide insights into variables that cannot be measured experimentally and allow a large number of conditions to be tested before the experimental analysis. However, current simulation models of electromyography (EMG), a core physiological signal in neuromechanical analyses, remain either limited in accuracy and conditions or are computationally heavy to apply. Here, we provide a computational platform to enable future work to overcome these limitations by presenting NeuroMotion, an open-source simulator that can modularly test a variety of approaches to the full-spectrum synthesis of EMG signals during voluntary movements. We demonstrate NeuroMotion using three sample modules. The first module is an upper-limb MSK model with OpenSim API to estimate the muscle fibre lengths and muscle activations during movements. The second module is BioMime, a deep neural network-based EMG generator that receives nonstationary physiological parameter inputs, like the afore-estimated muscle fibre lengths, and efficiently outputs motor unit action potentials (MUAPs). The third module is a motor unit pool model that transforms the muscle activations into discharge timings of motor units. The discharge timings are convolved with the output of BioMime to simulate EMG signals during the movement. We first show how MUAP waveforms change during different levels of physiological parameter variations and different movements. We then show that the synthetic EMG signals during two-degree-of-freedom hand and wrist movements can be used to augment experimental data for regressing joint angles. Ridge regressors trained on the synthetic dataset were directly used to predict joint angles from experimental data. In this way, NeuroMotion was able to generate full-spectrum EMG for the first use-case of human forearm electrophysiology during voluntary hand, wrist, and forearm movements. All intermediate variables are available, which allows the user to study cause-effect relationships in the complex neuromechanical system, fast iterate algorithms before collecting experimental data, and validate algorithms that estimate non-measurable parameters in experiments. We expect this modular platform will enable validation of generative EMG models, complement experimental approaches and empower neuromechanical research.
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Affiliation(s)
- Shihan Ma
- Department of Bioengineering, Imperial College London, London, United Kingdom
- State Key Laboratory of Mechanical System and Vibration, Shanghai Jiao Tong University, Shanghai, China
| | - Irene Mendez Guerra
- Department of Bioengineering, Imperial College London, London, United Kingdom
| | | | - Jiamin Zhao
- State Key Laboratory of Mechanical System and Vibration, Shanghai Jiao Tong University, Shanghai, China
| | | | | | | | - Xinjun Sheng
- State Key Laboratory of Mechanical System and Vibration, Shanghai Jiao Tong University, Shanghai, China
- Meta Robotics Institute, Shanghai Jiao Tong University, Shanghai, China
| | - Xiangyang Zhu
- State Key Laboratory of Mechanical System and Vibration, Shanghai Jiao Tong University, Shanghai, China
- Meta Robotics Institute, Shanghai Jiao Tong University, Shanghai, China
| | - Dario Farina
- Department of Bioengineering, Imperial College London, London, United Kingdom
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Wang X, Li L, Wei Y, Zhou P. Clustering index analysis on EMG-Torque relation-based representation of complex neuromuscular changes after spinal cord injury. J Electromyogr Kinesiol 2024; 76:102885. [PMID: 38723398 DOI: 10.1016/j.jelekin.2024.102885] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2023] [Revised: 03/12/2024] [Accepted: 04/26/2024] [Indexed: 05/23/2024] Open
Abstract
Spinal cord injury (SCI) resulting in complex neuromuscular pathology is not sufficiently well understood. To better quantify neuromuscular changes after SCI, this study uses a clustering index (CI) method for surface electromyography (sEMG) clustering representation to investigate the relation between sEMG and torque in SCI survivors. The sEMG signals were recorded from 13 subjects with SCI and 13 gender-age matched able-bodied subjects during isometric contraction of the biceps brachii muscle at different torque levels using a linear electrode array. Two torque representations, maximum voluntary contraction (MVC%) and absolute torque, were used. CI values were calculated for sEMG. Regression analyses were performed on CI values and torque levels of elbow flexion, revealing a strong linear relationship. The slopes of regressions between SCI survivors and control subjects were compared. The findings indicated that the range of distribution of CI values and slopes was greater in subjects with SCI than in control subjects (p < 0.05). The increase or decrease in slope was also observed at the individual level. This suggests that the CI and its sEMG clustering-torque relation may serve as valuable quantitative indicators for determining neuromuscular lesions after SCI, contributing to the development of effective rehabilitation strategies for improving motor performance.
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Affiliation(s)
- Xiang Wang
- Institute of Medical Research, Northwestern Polytechnical University, Xi'an, China; Research & Development Institute of Northwestern Polytechnical University in Shenzhen, Shenzhen, China
| | - Le Li
- Institute of Medical Research, Northwestern Polytechnical University, Xi'an, China; Research & Development Institute of Northwestern Polytechnical University in Shenzhen, Shenzhen, China.
| | - Yongli Wei
- School of Rehabilitation Science and Engineering, University of Health and Rehabilitation Sciences, Qingdao, China
| | - Ping Zhou
- School of Rehabilitation Science and Engineering, University of Health and Rehabilitation Sciences, Qingdao, China
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Huang C, Lu Z, Chen M, Klein CS, Zhang Y, Li S, Zhou P. Muscle innervation zone estimation from monopolar high-density M-waves using principal component analysis and radon transform. Front Physiol 2023; 14:1137146. [PMID: 37008017 PMCID: PMC10050562 DOI: 10.3389/fphys.2023.1137146] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2023] [Accepted: 02/27/2023] [Indexed: 03/17/2023] Open
Abstract
This study examined methods for estimating the innervation zone (IZ) of a muscle using recorded monopolar high density M waves. Two IZ estimation methods based on principal component analysis (PCA) and Radon transform (RT) were examined. Experimental M waves, acquired from the biceps brachii muscles of nine healthy subjects were used as testing data sets. The performance of the two methods was evaluated by comparing their IZ estimations with manual IZ detection by experienced human operators. Compared with manual detection, the agreement rate of the estimated IZs was 83% and 63% for PCA and RT based methods, respectively, both using monopolar high density M waves. In contrast, the agreement rate was 56% for cross correlation analysis using bipolar high density M waves. The mean difference in estimated IZ location between manual detection and the tested method was 0.12 ± 0.28 inter-electrode-distance (IED) for PCA, 0.33 ± 0.41 IED for RT and 0.39 ± 0.74 IED for cross correlation-based methods. The results indicate that the PCA based method was able to automatically detect muscle IZs from monopolar M waves. Thus, PCA provides an alternative approach to estimate IZ location of voluntary or electrically-evoked muscle contractions, and may have particular value for IZ detection in patients with impaired voluntary muscle activation.
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Affiliation(s)
- Chengjun Huang
- Department of Neuroscience, Baylor College of Medicine, Houston, TX, United States
| | - Zhiyuan Lu
- School of Rehabilitation Science and Engineering, University of Health and Rehabilitation Sciences, Qingdao, Shandong, China
- *Correspondence: Zhiyuan Lu, ; Ping Zhou,
| | - Maoqi Chen
- School of Rehabilitation Science and Engineering, University of Health and Rehabilitation Sciences, Qingdao, Shandong, China
| | - Cliff S. Klein
- Guangdong Work Injury Rehabilitation Center, Guangzhou, Guangdong, China
| | - Yingchun Zhang
- Department of Biomedical Engineering, University of Houston, Houston, TX, United States
| | - Sheng Li
- Department of Physical Medicine and Rehabilitation, University of Texas Health Science Center at Houston, Houston, TX, United States
- TIRR Memorial Hermann Hospital, Houston, TX, United States
| | - Ping Zhou
- School of Rehabilitation Science and Engineering, University of Health and Rehabilitation Sciences, Qingdao, Shandong, China
- *Correspondence: Zhiyuan Lu, ; Ping Zhou,
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Liu Y, Chen YT, Zhang C, Zhou P, Li S, Zhang Y. Motor Unit Number Estimation in Spastic Biceps Brachii Muscles of Chronic Stroke Survivors Before and After BoNT Injection. IEEE Trans Biomed Eng 2023; 70:1045-1052. [PMID: 36126033 PMCID: PMC10676740 DOI: 10.1109/tbme.2022.3208078] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
OBJECTIVE The study aims to characterize the motor unit (MU) loss in spastic biceps brachii muscle (BBM) of chronic stroke survivors before and after botulinum neurotoxin (BoNT) injection. METHODS High-density weighted average (HDWA) motor unit number estimation (MUNE) was employed to estimate the number of functioning motor units of BBMs of eight chronic stroke survivors 1-week before (1st visit) and 3-week after (2nd visit) BoNT injection based on the surface electromyography (sEMG) signals recorded during voluntary contraction and supramaximal electrical stimulation. RESULT Significant lower MUNE was estimated from the spastic BBMs compared to the non-spastic MUNEs during two visits. A surprisingly higher MUNE was obtained from the spastic side during the 2nd visit after BoNT injection. CONCLUSIONS The HDWA MUNE technique can be employed to characterize the motor unit loss in spastic muscle caused by upper motor neuro lesions at contraction level up to 30% MVC, but may fail to detect the MU loss caused by the chemodenervation effect of BoNT due to the non-uniform denervation of small and large size MUs. SIGNIFICANCE This study presents the first effort to evaluate the applicability of HDWA MUNE technique to characterize the MU loss in the spastic muscle following stroke and the subsequent BoNT injection for the treatment of post-stroke spasticity. The finding of this study suggests that HDWA MUNE can be a sensitive approach to detect the MU loss in spastic muscles after stroke, but the large inter-subject MUNE variability after the BoNT injection should be interpreted with caution.
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Affiliation(s)
- Yang Liu
- Department of Biomedical Engineering, University of Houston, Houston, TX 77204 USA
| | - Yen-Ting Chen
- (1) Department of Physical Medicine and Rehabilitation, University of Texas Health Science Center at Houston, Houston, TX 77030, United States; (2) TIRR Memorial Hermann Hospital, Houston, TX 77030, USA; (3) Department of Health and Kinesiology, Northeastern State University, Broken Arrow, OK 74014, USA
| | - Chuan Zhang
- Department of Biomedical Engineering, University of Houston, Houston, TX 77204 USA
| | - Ping Zhou
- Faculty of Rehabilitation Engineering, University of Health and Rehabilitation Sciences, Qingdao 266024, China
| | - Sheng Li
- (1) Department of Physical Medicine and Rehabilitation, University of Texas Health Science Center at Houston, Houston, TX 77030, United States; (2) TIRR Memorial Hermann Hospital, Houston, TX 77030, USA
| | - Yingchun Zhang
- Department of Biomedical Engineering, University of Houston, Houston, TX 77204 USA
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Xu J, Zhu J, Li Y, Yao Y, Xuan A, Li D, Yu T, Zhu D. Three-dimensional mapping reveals heterochronic development of the neuromuscular system in postnatal mouse skeletal muscles. Commun Biol 2022; 5:1200. [PMID: 36347940 PMCID: PMC9643545 DOI: 10.1038/s42003-022-04159-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Accepted: 10/24/2022] [Indexed: 11/09/2022] Open
Abstract
The development of the neuromuscular system, including muscle growth and intramuscular neural development, in addition to central nervous system maturation, determines motor ability improvement. Motor development occurs asynchronously from cephalic to caudal. However, whether the structural development of different muscles is heterochronic is unclear. Here, based on the characteristics of motor behavior in postnatal mice, we examined the 3D structural features of the neuromuscular system in different muscles by combining tissue clearing with optical imaging techniques. Quantitative analyses of the structural data and related mRNA expression revealed that there was continued myofiber hyperplasia of the forelimb and hindlimb muscles until around postnatal day 3 (P3) and P6, respectively, as well as continued axonal arborization and neuromuscular junction formation until around P3 and P9, respectively; feature alterations of the cervical muscle ended at birth. Such structural heterochrony of muscles in different body parts corresponds to their motor function. Structural data on the neuromuscular system of neonatal muscles provide a 3D perspective in the understanding of the structural status during motor development.
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Affiliation(s)
- Jianyi Xu
- Britton Chance Center for Biomedical Photonics - MoE Key Laboratory for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics - Advanced Biomedical Imaging Facility, Huazhong University of Science and Technology, 430074, Wuhan, Hubei, China
- Optics Valley Laboratory, 430074, Wuhan, Hubei, China
| | - Jingtan Zhu
- Britton Chance Center for Biomedical Photonics - MoE Key Laboratory for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics - Advanced Biomedical Imaging Facility, Huazhong University of Science and Technology, 430074, Wuhan, Hubei, China
- Optics Valley Laboratory, 430074, Wuhan, Hubei, China
| | - Yusha Li
- Britton Chance Center for Biomedical Photonics - MoE Key Laboratory for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics - Advanced Biomedical Imaging Facility, Huazhong University of Science and Technology, 430074, Wuhan, Hubei, China
- Optics Valley Laboratory, 430074, Wuhan, Hubei, China
| | - Yingtao Yao
- Britton Chance Center for Biomedical Photonics - MoE Key Laboratory for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics - Advanced Biomedical Imaging Facility, Huazhong University of Science and Technology, 430074, Wuhan, Hubei, China
- Optics Valley Laboratory, 430074, Wuhan, Hubei, China
| | - Ang Xuan
- Britton Chance Center for Biomedical Photonics - MoE Key Laboratory for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics - Advanced Biomedical Imaging Facility, Huazhong University of Science and Technology, 430074, Wuhan, Hubei, China
- Optics Valley Laboratory, 430074, Wuhan, Hubei, China
| | - Dongyu Li
- Britton Chance Center for Biomedical Photonics - MoE Key Laboratory for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics - Advanced Biomedical Imaging Facility, Huazhong University of Science and Technology, 430074, Wuhan, Hubei, China
- Optics Valley Laboratory, 430074, Wuhan, Hubei, China
| | - Tingting Yu
- Britton Chance Center for Biomedical Photonics - MoE Key Laboratory for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics - Advanced Biomedical Imaging Facility, Huazhong University of Science and Technology, 430074, Wuhan, Hubei, China.
- Optics Valley Laboratory, 430074, Wuhan, Hubei, China.
| | - Dan Zhu
- Britton Chance Center for Biomedical Photonics - MoE Key Laboratory for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics - Advanced Biomedical Imaging Facility, Huazhong University of Science and Technology, 430074, Wuhan, Hubei, China.
- Optics Valley Laboratory, 430074, Wuhan, Hubei, China.
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Liu Y, Chen YT, Zhang C, Zhou P, Li S, Zhang Y. Motor unit distribution and recruitment in spastic and non-spastic bilateral biceps brachii muscles of chronic stroke survivors. J Neural Eng 2022; 19:10.1088/1741-2552/ac86f4. [PMID: 35926440 PMCID: PMC9526353 DOI: 10.1088/1741-2552/ac86f4] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2022] [Accepted: 08/04/2022] [Indexed: 11/11/2022]
Abstract
Objective.This study aims to characterize the motor units (MUs) distribution and recruitment pattern in the spastic and non-spastic bilateral biceps brachii muscles (BBMs) of chronic stroke survivors.Approach.High-density surface electromyography (HD-sEMG) signals were collected from both spastic and non-spastic BBMs of fourteen chronic stroke subjects during isometric elbow flexion at 10%, 30%, 50% and 100% maximal voluntary contractions (MVCs). By combining HD-sEMG decomposition and bioelectrical source imaging, MU innervation zones (MUIZs) of the decomposed MUs were first localized in the 3D space of spastic and non-spastic BBMs. The MU depth defined as the distance between the localized MUIZ and its normal projection on the skin surface was then normalized to the arm radius of each subject and averaged at given contraction level. The averaged MU depth at different contraction levels on a specific arm side (intra-side) and the bilateral depths under a specific contraction level (inter-side) were compared.Main results.The average depth of decomposed MUs increased with the contraction force and significant differences observed between 10% vs 50% (p< 0.0001), 10% vs 100% (p< 0.0001) and 30% vs 100% MVC (p= 0.0017) on the non-spastic side, indicating that larger MUs with higher recruitment threshold locate in deeper muscle regions. In contrast, no force-related difference in MU depth was observed on the spastic side, suggesting a disruption of orderly recruitment of MUs with increase of force level, or the MU denervation and the subsequent collateral reinnervation secondary to upper motor neuron lesions. Inter-side comparison demonstrated significant MU depth difference at 10% (p= 0.0048) and 100% force effort (p= 0.0026).Significance.This study represents the first effort to non-invasively characterize the MU distribution inside spastic and non-spastic bilateral BBM of chronic stroke patients by combining HD-sEMG recording, EMG signal decomposition and bioelectrical source imaging. The findings of this study advances our understanding regarding the neurophysiology of human muscles and the neuromuscular alterations following stroke. It may also offer important MU depth information for botulinum toxin injection in clinical post-stroke spasticity management.
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Affiliation(s)
- Yang Liu
- Department of Biomedical Engineering, University of Houston, Houston, TX 77204 USA
| | - Yen-Ting Chen
- Department of Physical Medicine and Rehabilitation, University of Texas Health Science Center at Houston, Houston, TX 77030, United States
- TIRR Memorial Hermann Hospital, Houston, TX 77030, USA
- Department of Health and Kinesiology, Northeastern State University, Broken Arrow, OK 74014, USA
| | - Chuan Zhang
- Department of Biomedical Engineering, University of Houston, Houston, TX 77204 USA
| | - Ping Zhou
- Faculty of Rehabilitation Engineering, University of Health and Rehabilitation Sciences, Qingdao 266024, China
| | - Sheng Li
- Department of Physical Medicine and Rehabilitation, University of Texas Health Science Center at Houston, Houston, TX 77030, United States
- TIRR Memorial Hermann Hospital, Houston, TX 77030, USA
| | - Yingchun Zhang
- Department of Biomedical Engineering, University of Houston, Houston, TX 77204 USA
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Huang C, Chen M, Li X, Zhang Y, Li S, Zhou P. Neurophysiological Factors Affecting Muscle Innervation Zone Estimation Using Surface EMG: A Simulation Study. BIOSENSORS-BASEL 2021; 11:bios11100356. [PMID: 34677312 PMCID: PMC8534086 DOI: 10.3390/bios11100356] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/16/2021] [Revised: 09/16/2021] [Accepted: 09/24/2021] [Indexed: 11/16/2022]
Abstract
Surface electromyography (EMG) recorded by a linear or 2-dimensional electrode array can be used to estimate the location of muscle innervation zones (IZ). There are various neurophysiological factors that may influence surface EMG and thus potentially compromise muscle IZ estimation. The objective of this study was to evaluate how surface-EMG-based IZ estimation might be affected by different factors, including varying degrees of motor unit (MU) synchronization in the case of single or double IZs. The study was performed by implementing a model simulating surface EMG activity. Three different MU synchronization conditions were simulated, namely no synchronization, medium level synchronization, and complete synchronization analog to M wave. Surface EMG signals recorded by a 2-dimensional electrode array were simulated from a muscle with single and double IZs, respectively. For each situation, the IZ was estimated from surface EMG and compared with the one used in the model for performance evaluation. For the muscle with only one IZ, the estimated IZ location from surface EMG was consistent with the one used in the model for all the three MU synchronization conditions. For the muscle with double IZs, at least one IZ was appropriately estimated from interference surface EMG when there was no MU synchronization. However, the estimated IZ was different from either of the two IZ locations used in the model for the other two MU synchronization conditions. For muscles with a single IZ, MU synchronization has little effect on IZ estimation from electrode array surface EMG. However, caution is required for multiple IZ muscles since MU synchronization might lead to false IZ estimation.
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Affiliation(s)
- Chengjun Huang
- Guangdong Work Injury Rehabilitation Center, Guangzhou 510970, China;
- Department of Physical Medicine and Rehabilitation, University of Texas Health Science Center at Houston, Houston, TX 77030, USA;
| | - Maoqi Chen
- Faculty of Rehabilitation Engineering, University of Health and Rehabilitation Sciences, Qingdao 266024, China;
| | - Xiaoyan Li
- Department of Bioengineering, University of Maryland, College Park, MD 20742, USA;
- Department of Neurology, Medical College of Wisconsin, Milwaukee, WI 53226, USA
| | - Yingchun Zhang
- Department of Biomedical Engineering, University of Houston, Houston, TX 77204, USA;
| | - Sheng Li
- Department of Physical Medicine and Rehabilitation, University of Texas Health Science Center at Houston, Houston, TX 77030, USA;
| | - Ping Zhou
- Faculty of Rehabilitation Engineering, University of Health and Rehabilitation Sciences, Qingdao 266024, China;
- Correspondence:
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Zhang C, Chen YT, Liu Y, Magat E, Gutierrez-Verduzco M, Francisco GE, Zhou P, Li S, Zhang Y. Improving Botulinum Toxin Efficiency in Treating Post-Stroke Spasticity Using 3D Innervation Zone Imaging. Int J Neural Syst 2021; 31:2150007. [PMID: 33438529 DOI: 10.1142/s0129065721500076] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Spasticity is a common post-stroke syndrome that imposes significant adverse impacts on patients and caregivers. This study aims to improve the efficiency of botulinum toxin (BoNT) in managing spasticity, by utilizing a three-dimensional innervation zone imaging (3DIZI) technique based on high-density surface electromyography (HD-sEMG) recordings. Stroke subjects were randomly assigned to two groups: the control group ([Formula: see text]) which received standard ultrasound-guided injections, and the experimental group ([Formula: see text]) which received 3DIZI-guided injections. The amount of BoNT given was consistent for all subjects. The Modified Ashworth Scale (MAS), compound muscle action potential (CMAP) and muscle activation volume (MAV) from bilateral biceps brachii muscles were obtained at the baseline, 3 weeks, and 3 months after injection. Intra-group and inter-group comparisons of MAS, CMAP amplitude and MAV were performed. An overall improvement in MAS of spastic elbow flexors was observed during the 3-week visit ([Formula: see text]), yet no statistically significant difference found with intra-group or inter-group analysis. Compared to the baseline, a significant reduction of CMAP amplitude and MAV were observed in the spastic biceps muscles of both groups at 3-week post-injection, and returned to approximate baseline value at 12-week post injection. A significantly higher reduction was found in CMAP amplitude ([Formula: see text]% versus [Formula: see text]%, [Formula: see text]) and MAV ([Formula: see text]% versus [Formula: see text]%, [Formula: see text]) in the experimental group compared to the control group. The study has demonstrated preliminary evidence that precisely directing BoNT to the innervation zones (IZs) localized by 3DIZI leads to a significantly higher treatment efficiency improvement in spasticity management. Results have also shown the feasibility of developing a personalized BoNT injection technique for the optimization of clinical treatment for post-stroke spasticity using proposed 3DIZI technique.
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Affiliation(s)
- Chuan Zhang
- Department of Biomedical Engineering, University of Houston, Houston, TX, USA
| | - Yen-Ting Chen
- Department of Physical Medicine and Rehabilitation, University of Texas Health Science Center at Houston and TIRR, Memorial Hermann Hospital, Houston, TX, USA
| | - Yang Liu
- Department of Biomedical Engineering, University of Houston, Houston, TX, USA
| | - Elaine Magat
- Department of Physical Medicine and Rehabilitation, University of Texas Health Science Center at Houston and TIRR, Memorial Hermann Hospital, Houston, TX, USA
| | - Monica Gutierrez-Verduzco
- Department of Physical Medicine and Rehabilitation, University of Texas Health Science Center at Houston and TIRR, Memorial Hermann Hospital, Houston, TX, USA
| | - Gerard E Francisco
- Department of Physical Medicine and Rehabilitation, University of Texas Health Science Center at Houston and TIRR, Memorial Hermann Hospital, Houston, TX, USA
| | - Ping Zhou
- Institute of Rehabilitation Engineering, The University of Rehabilitation, Qingdao, P. R. China
| | - Sheng Li
- Department of Physical Medicine and Rehabilitation, University of Texas Health Science Center at Houston and TIRR, Memorial Hermann Hospital, Houston, TX, USA
| | - Yingchun Zhang
- Department of Biomedical Engineering, University of Houston, Houston, TX, USA
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Dias N, Zhang C, Smith CP, Lai HH, Zhang Y. High-density surface electromyographic assessment of pelvic floor hypertonicity in IC/BPS patients: a pilot study. Int Urogynecol J 2020; 32:1221-1228. [PMID: 32761375 DOI: 10.1007/s00192-020-04467-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2020] [Accepted: 07/23/2020] [Indexed: 11/25/2022]
Abstract
INTRODUCTION AND HYPOTHESIS To assess the feasibility of objectively assessing pelvic floor hypertonicity (PFH) in women with interstitial cystitis/bladder pain syndrome (IC/BPS) using an intra-vaginal high-density surface electromyography (HD-sEMG) probe. METHODS Seven female subjects (mean age 44 ± 13 years) with a prior diagnosis of IC/BPS were recruited. A full digital pelvic examination was administered to identify hypertonic muscles. Intra-vaginal HD-sEMG was acquired during rest. Root-mean-squared (RMS) amplitude during rest was calculated for each channel to define a hypertonicity index and hypertonic zone. Innervation zones (IZs) were identified from the bipolar mapping of decomposed HD-sEMG signals and summarized into an IZ distribution mapping. RESULTS Of the seven subjects recruited, five had normal pelvic floor muscle tone and two exhibited hypertonicity upon muscle palpation. Subjects with PFH demonstrated a higher hypertonicity index (12.6 ± 3.5 vs. 4.5 ± 1.2) in sessions 1 and 2. The hypertonic zone defined by the 64-channel RMS mapping coincided with the digital pelvic examination findings. The corresponding IZs were localized for each motor unit. The hypertonicity indices between two consecutive sessions were well correlated (CC = 0.95). CONCLUSIONS This study represents the first effort to employ intra-vaginal HD-sEMG to assess PFH in women with IC/BPS. Our results demonstrate the feasibility of HD-sEMG to provide a quantitative diagnosis of PFH and the precise localization of hypertonic muscles and IZs. The proposed HD-sEMG-based techniques provide promising tools for clinical diagnosis and treatment of PFH, such as the personalized guidance of BoNT injections.
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Affiliation(s)
- Nicholas Dias
- Department of Biomedical Engineering, University of Houston, Houston, TX, 77204, USA
| | - Chuan Zhang
- Department of Biomedical Engineering, University of Houston, Houston, TX, 77204, USA
| | | | - H Henry Lai
- Department of Surgery, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Yingchun Zhang
- Department of Biomedical Engineering, University of Houston, Houston, TX, 77204, USA.
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Gao F, Cao Y, Zhang C, Zhang Y. A Preliminary Study of Effects of Channel Number and Location on the Repeatability of Motor Unit Number Index (MUNIX). Front Neurol 2020; 11:191. [PMID: 32256444 PMCID: PMC7090144 DOI: 10.3389/fneur.2020.00191] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2019] [Accepted: 02/28/2020] [Indexed: 01/01/2023] Open
Affiliation(s)
- Farong Gao
- School of Automation, Artificial Intelligence Institute, Hangzhou Dianzi University, Hangzhou, China
| | - Yueying Cao
- School of Automation, Artificial Intelligence Institute, Hangzhou Dianzi University, Hangzhou, China
| | - Chuan Zhang
- Department of Biomedical Engineering, University of Houston, Houston, TX, United States
| | - Yingchun Zhang
- Department of Biomedical Engineering, University of Houston, Houston, TX, United States
- *Correspondence: Yingchun Zhang
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