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Suresh RE, Zobaer MS, Triano MJ, Saway BF, Rowland NC. Noninvasive brain stimulation during EEG improves machine learning classification in chronic stroke. RESEARCH SQUARE 2024:rs.3.rs-4809587. [PMID: 39281864 PMCID: PMC11398570 DOI: 10.21203/rs.3.rs-4809587/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/18/2024]
Abstract
BACKGROUND In individuals with chronic stroke and hemiparesis, noninvasive brain stimulation (NIBS) may be used as an adjunct to therapy for improving motor recovery. Specific states of movement during motor recovery are more responsive to brain stimulation than others, thus a system that could auto-detect movement state would be useful in correctly identifying the most effective stimulation periods. The aim of this study was to compare the performance of different machine learning models in classifying movement periods during EEG recordings of hemiparetic individuals receiving noninvasive brain stimulation. We hypothesized that transcranial direct current stimulation, a form of NIBS, would modulate brain recordings correlating with movement state and improve classification accuracies above those receiving sham stimulation. METHODS Electroencephalogram data were obtained from 10 participants with chronic stroke and 11 healthy individuals performing a motor task while undergoing transcranial direct current stimulation. Eight traditional machine learning algorithms and five ensemble methods were used to classify two movement states (a hold posture and an arm reaching movement) before, during and after stimulation. To minimize compute times, preprocessing and feature extraction were limited to z-score normalization and power binning into five frequency bands (delta through gamma). RESULTS Classification of disease state produced significantly higher accuracies in the stimulation (versus sham) group at 78.9% (versus 55.6%, p < 0.000002). We observed significantly higher accuracies when classifying stimulation state in the chronic stroke group (77.6%) relative to healthy controls (64.1%, p < 0.0095). In the chronic stroke cohort, classification of hold versus reach was highest during the stimulation period (75.2%) as opposed to the pre- and post-stimulation periods. Linear discriminant analysis, logistic regression, and decision tree algorithms classified movement state most accurately in participants with chronic stroke during the stimulation period (76.1%). For the ensemble methods, the highest classification accuracy for hold versus reach was achieved using low gamma frequency (30-50 Hz) as a feature (74.5%), although this result did not achieve statistical significance. CONCLUSIONS Machine learning algorithms demonstrated sufficiently high movement state classification accuracy in participants with chronic stroke performing functional tasks during noninvasive brain stimulation. tDCS improved disease state and movement state classification in participants with chronic stroke.
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Borzelli D, De Marchis C, Quercia A, De Pasquale P, Casile A, Quartarone A, Calabrò RS, d’Avella A. Muscle Synergy Analysis as a Tool for Assessing the Effectiveness of Gait Rehabilitation Therapies: A Methodological Review and Perspective. Bioengineering (Basel) 2024; 11:793. [PMID: 39199751 PMCID: PMC11351442 DOI: 10.3390/bioengineering11080793] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2024] [Revised: 07/19/2024] [Accepted: 07/29/2024] [Indexed: 09/01/2024] Open
Abstract
According to the modular hypothesis for the control of movement, muscles are recruited in synergies, which capture muscle coordination in space, time, or both. In the last two decades, muscle synergy analysis has become a well-established framework in the motor control field and for the characterization of motor impairments in neurological patients. Altered modular control during a locomotion task has been often proposed as a potential quantitative metric for characterizing pathological conditions. Therefore, the purpose of this systematic review is to analyze the recent literature that used a muscle synergy analysis of neurological patients' locomotion as an indicator of motor rehabilitation therapy effectiveness, encompassing the key methodological elements to date. Searches for the relevant literature were made in Web of Science, PubMed, and Scopus. Most of the 15 full-text articles which were retrieved and included in this review identified an effect of the rehabilitation intervention on muscle synergies. However, the used experimental and methodological approaches varied across studies. Despite the scarcity of studies that investigated the effect of rehabilitation on muscle synergies, this review supports the utility of muscle synergies as a marker of the effectiveness of rehabilitative therapy and highlights the challenges and open issues that future works need to address to introduce the muscle synergies in the clinical practice and decisional process.
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Affiliation(s)
- Daniele Borzelli
- Department of Biomedical and Dental Sciences and Morphofunctional Imaging, University of Messina, 98125 Messina, Italy; (A.Q.); (A.C.)
- Laboratory of Neuromotor Physiology, IRCCS Fondazione Santa Lucia, 00179 Rome, Italy;
| | | | - Angelica Quercia
- Department of Biomedical and Dental Sciences and Morphofunctional Imaging, University of Messina, 98125 Messina, Italy; (A.Q.); (A.C.)
| | - Paolo De Pasquale
- IRCCS Centro Neurolesi “Bonino Pulejo”, 98124 Messina, Italy; (P.D.P.); (A.Q.); (R.S.C.)
| | - Antonino Casile
- Department of Biomedical and Dental Sciences and Morphofunctional Imaging, University of Messina, 98125 Messina, Italy; (A.Q.); (A.C.)
| | - Angelo Quartarone
- IRCCS Centro Neurolesi “Bonino Pulejo”, 98124 Messina, Italy; (P.D.P.); (A.Q.); (R.S.C.)
| | | | - Andrea d’Avella
- Laboratory of Neuromotor Physiology, IRCCS Fondazione Santa Lucia, 00179 Rome, Italy;
- Department of Biology, University of Rome Tor Vergata, 00133 Rome, Italy
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Gopalakrishnan R, Cunningham DA, Hogue O, Schroedel M, Campbell BA, Baker KB, Machado AG. Electrophysiological Correlates of Dentate Nucleus Deep Brain Stimulation for Poststroke Motor Recovery. J Neurosci 2024; 44:e2149232024. [PMID: 38724284 PMCID: PMC11223455 DOI: 10.1523/jneurosci.2149-23.2024] [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] [Received: 11/16/2023] [Revised: 04/23/2024] [Accepted: 04/24/2024] [Indexed: 07/05/2024] Open
Abstract
While ipsilesional cortical electroencephalography has been associated with poststroke recovery mechanisms and outcomes, the role of the cerebellum and its interaction with the ipsilesional cortex is still largely unknown. We have previously shown that poststroke motor control relies on increased corticocerebellar coherence (CCC) in the low beta band to maintain motor task accuracy and to compensate for decreased excitability of the ipsilesional cortex. We now extend our work to investigate corticocerebellar network changes associated with chronic stimulation of the dentato-thalamo-cortical pathway aimed at promoting poststroke motor rehabilitation. We investigated the excitability of the ipsilesional cortex, the dentate (DN), and their interaction as a function of treatment outcome measures. Relative to baseline, 10 human participants (two women) at the end of 4-8 months of DN deep brain stimulation (DBS) showed (1) significantly improved motor control indexed by computerized motor tasks; (2) significant increase in ipsilesional premotor cortex event-related desynchronization that correlated with improvements in motor function; and (3) significant decrease in CCC, including causal interactions between the DN and ipsilesional cortex, which also correlated with motor function improvements. Furthermore, we show that the functional state of the DN in the poststroke state and its connectivity with the ipsilesional cortex were predictive of motor outcomes associated with DN-DBS. The findings suggest that as participants recovered, the ipsilesional cortex became more involved in motor control, with less demand on the cerebellum to support task planning and execution. Our data provide unique mechanistic insights into the functional state of corticocerebellar-cortical network after stroke and its modulation by DN-DBS.
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Affiliation(s)
- Raghavan Gopalakrishnan
- Center for Neurological Restoration, Neurological Institute, Cleveland Clinic, Cleveland, Ohio 44195
- Department of Biomedical Engineering, Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio 44195
- Cleveland FES Center, Cleveland, Ohio 44106
| | - David A Cunningham
- Cleveland FES Center, Cleveland, Ohio 44106
- Physical Medicine and Rehabilitation, Case Western Reserve University School of Medicine, Cleveland, Ohio 44106
- Center for Rehabilitation Research, MetroHealth Systems, Cleveland, Ohio 44109
| | - Olivia Hogue
- Center for Neurological Restoration, Neurological Institute, Cleveland Clinic, Cleveland, Ohio 44195
- Department of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio 44195
| | - Madeleine Schroedel
- Center for Neurological Restoration, Neurological Institute, Cleveland Clinic, Cleveland, Ohio 44195
| | - Brett A Campbell
- Department of Neurosciences, Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio 44195
| | - Kenneth B Baker
- Center for Neurological Restoration, Neurological Institute, Cleveland Clinic, Cleveland, Ohio 44195
- Department of Neurosciences, Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio 44195
| | - Andre G Machado
- Center for Neurological Restoration, Neurological Institute, Cleveland Clinic, Cleveland, Ohio 44195
- Department of Neurosciences, Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio 44195
- Department of Neurosurgery, Neurological Institute, Cleveland Clinic, Cleveland, Ohio 44195
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Lee HS, Kim S, Kim H, Baik SM, Kim DH, Chang WH. No Additional Effects of Sequential Facilitatory Cerebral and Cerebellar rTMS in Subacute Stroke Patients. J Pers Med 2024; 14:687. [PMID: 39063941 PMCID: PMC11278256 DOI: 10.3390/jpm14070687] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2024] [Revised: 06/20/2024] [Accepted: 06/24/2024] [Indexed: 07/28/2024] Open
Abstract
The aim of this study was to investigate the additional effects of cerebellar rTMS on the motor recovery of facilitatory rTMS over affected primary motor cortex (M1) in subacute stroke patients. Twenty-eight subacute stroke patients were recruited in this single-blind, randomized, controlled trial. The Cr-Cbll group received Cr-Cbll rTMS stimulation consisting of high-frequency rTMS over affected M1 (10 min), motor training (10 min), and high-frequency rTMS over contralesional Cbll (10 min). The Cr-sham group received sham rTMS instead of high-frequency rTMS over the cerebellum. Ten daily sessions were performed for 2 weeks. A Fugl-Meyer Assessment (FMA) was measured before (T0), immediately after (T1), and 2 months after the intervention (T2). A total of 20 participants (10 in the Cr-Cbll group and 10 in the Cr-sham group) completed the intervention. There was no significant difference in clinical characteristics between the two groups at T0. FMA was significantly improved after the intervention in both Cr-Cbll and Cr-sham groups (p < 0.05). However, there was no significant interaction in FMA between time and group. In conclusion, these results could not demonstrate that rTMS over the contralesional cerebellum has additional effects to facilitatory rTMS over the affected M1 for improving motor function in subacute stroke patients.
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Affiliation(s)
- Ho Seok Lee
- Department of Physical and Rehabilitation Medicine, Center for Prevention and Rehabilitation, Heart Vascular and Stroke Institute, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Republic of Korea
| | - Sungwon Kim
- Department of Physical and Rehabilitation Medicine, Center for Prevention and Rehabilitation, Heart Vascular and Stroke Institute, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Republic of Korea
| | - Heegoo Kim
- Department of Physical and Rehabilitation Medicine, Center for Prevention and Rehabilitation, Heart Vascular and Stroke Institute, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Republic of Korea
| | - Seung-min Baik
- Department of Physical and Rehabilitation Medicine, Center for Prevention and Rehabilitation, Heart Vascular and Stroke Institute, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Republic of Korea
| | - Dae Hyun Kim
- Department of Physical and Rehabilitation Medicine, Center for Prevention and Rehabilitation, Heart Vascular and Stroke Institute, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Republic of Korea
| | - Won Hyuk Chang
- Department of Physical and Rehabilitation Medicine, Center for Prevention and Rehabilitation, Heart Vascular and Stroke Institute, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Republic of Korea
- Department of Health Sciences and Technology, Department of Medical Device Management & Research, Department of Digital Health, SAIHST, Sungkyunkwan University, Seoul 06355, Republic of Korea
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Hellara H, Barioul R, Sahnoun S, Fakhfakh A, Kanoun O. Comparative Study of sEMG Feature Evaluation Methods Based on the Hand Gesture Classification Performance. SENSORS (BASEL, SWITZERLAND) 2024; 24:3638. [PMID: 38894429 PMCID: PMC11175337 DOI: 10.3390/s24113638] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/30/2024] [Revised: 05/27/2024] [Accepted: 06/01/2024] [Indexed: 06/21/2024]
Abstract
Effective feature extraction and selection are crucial for the accurate classification and prediction of hand gestures based on electromyographic signals. In this paper, we systematically compare six filter and wrapper feature evaluation methods and investigate their respective impacts on the accuracy of gesture recognition. The investigation is based on several benchmark datasets and one real hand gesture dataset, including 15 hand force exercises collected from 14 healthy subjects using eight commercial sEMG sensors. A total of 37 time- and frequency-domain features were extracted from each sEMG channel. The benchmark dataset revealed that the minimum Redundancy Maximum Relevance (mRMR) feature evaluation method had the poorest performance, resulting in a decrease in classification accuracy. However, the RFE method demonstrated the potential to enhance classification accuracy across most of the datasets. It selected a feature subset comprising 65 features, which led to an accuracy of 97.14%. The Mutual Information (MI) method selected 200 features to reach an accuracy of 97.38%. The Feature Importance (FI) method reached a higher accuracy of 97.62% but selected 140 features. Further investigations have shown that selecting 65 and 75 features with the RFE methods led to an identical accuracy of 97.14%. A thorough examination of the selected features revealed the potential for three additional features from three specific sensors to enhance the classification accuracy to 97.38%. These results highlight the significance of employing an appropriate feature selection method to significantly reduce the number of necessary features while maintaining classification accuracy. They also underscore the necessity for further analysis and refinement to achieve optimal solutions.
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Affiliation(s)
- Hiba Hellara
- Professorship for Measurements and Sensor Technology, Chemnitz University of Technology, Rechenhainer Straße 70, 09126 Chemnitz, Germany; (H.H.); (R.B.)
- Laboratory of Signals, Systems, Artificial Intelligence and Networks, Digital Research Centre of Sfax, National School of Electronics and Telecommunications of Sfax, University of Sfax, Technopole of Sfax, Sfax 3021, Tunisia; (S.S.); (A.F.)
| | - Rim Barioul
- Professorship for Measurements and Sensor Technology, Chemnitz University of Technology, Rechenhainer Straße 70, 09126 Chemnitz, Germany; (H.H.); (R.B.)
| | - Salwa Sahnoun
- Laboratory of Signals, Systems, Artificial Intelligence and Networks, Digital Research Centre of Sfax, National School of Electronics and Telecommunications of Sfax, University of Sfax, Technopole of Sfax, Sfax 3021, Tunisia; (S.S.); (A.F.)
| | - Ahmed Fakhfakh
- Laboratory of Signals, Systems, Artificial Intelligence and Networks, Digital Research Centre of Sfax, National School of Electronics and Telecommunications of Sfax, University of Sfax, Technopole of Sfax, Sfax 3021, Tunisia; (S.S.); (A.F.)
| | - Olfa Kanoun
- Professorship for Measurements and Sensor Technology, Chemnitz University of Technology, Rechenhainer Straße 70, 09126 Chemnitz, Germany; (H.H.); (R.B.)
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Meng H, Houston M, Zhang Y, Li S. Exploring the Prospects of Transcranial Electrical Stimulation (tES) as a Therapeutic Intervention for Post-Stroke Motor Recovery: A Narrative Review. Brain Sci 2024; 14:322. [PMID: 38671974 PMCID: PMC11047964 DOI: 10.3390/brainsci14040322] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2024] [Revised: 03/12/2024] [Accepted: 03/23/2024] [Indexed: 04/28/2024] Open
Abstract
INTRODUCTION Stroke survivors often have motor impairments and related functional deficits. Transcranial Electrical Stimulation (tES) is a rapidly evolving field that offers a wide range of capabilities for modulating brain function, and it is safe and inexpensive. It has the potential for widespread use for post-stroke motor recovery. Transcranial Direct Current Stimulation (tDCS), Transcranial Alternating Current Stimulation (tACS), and Transcranial Random Noise Stimulation (tRNS) are three recognized tES techniques that have gained substantial attention in recent years but have different mechanisms of action. tDCS has been widely used in stroke motor rehabilitation, while applications of tACS and tRNS are very limited. The tDCS protocols could vary significantly, and outcomes are heterogeneous. PURPOSE the current review attempted to explore the mechanisms underlying commonly employed tES techniques and evaluate their prospective advantages and challenges for their applications in motor recovery after stroke. CONCLUSION tDCS could depolarize and hyperpolarize the potentials of cortical motor neurons, while tACS and tRNS could target specific brain rhythms and entrain neural networks. Despite the extensive use of tDCS, the complexity of neural networks calls for more sophisticated modifications like tACS and tRNS.
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Affiliation(s)
- Hao Meng
- Department of Physical Medicine & Rehabilitation, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Michael Houston
- Department of Biomedical Engineering, University of Houston, Houston, TX 77204, USA;
| | - Yingchun Zhang
- Department of Biomedical Engineering, University of Miami, Coral Gables, FL 33146, USA;
| | - Sheng Li
- Department of Physical Medicine & Rehabilitation, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX 77030, USA
- TIRR Memorial Hermann Hospital, Houston, TX 77030, USA
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Wang C, Lin C, Zhao Y, Samantzis M, Sedlak P, Sah P, Balbi M. 40-Hz optogenetic stimulation rescues functional synaptic plasticity after stroke. Cell Rep 2023; 42:113475. [PMID: 37979173 DOI: 10.1016/j.celrep.2023.113475] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2023] [Revised: 10/18/2023] [Accepted: 11/03/2023] [Indexed: 11/20/2023] Open
Abstract
Evoked brain oscillations in the gamma range have been shown to assist in stroke recovery. However, the causal relationship between evoked oscillations and neuroprotection is not well understood. We have used optogenetic stimulation to investigate how evoked gamma oscillations modulate cortical dynamics in the acute phase after stroke. Our results reveal that stimulation at 40 Hz drives activity in interneurons at the stimulation frequency and phase-locked activity in principal neurons at a lower frequency, leading to increased cross-frequency coupling. In addition, 40-Hz stimulation after stroke enhances interregional communication. These effects are observed up to 24 h after stimulation. Our stimulation protocol also rescues functional synaptic plasticity 24 h after stroke and leads to an upregulation of plasticity genes and a downregulation of cell death genes. Together these results suggest that restoration of cortical dynamics may confer neuroprotection after stroke.
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Affiliation(s)
- Cong Wang
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD 4067, Australia; Engineering Research Centre of Traditional Chinese Medicine Intelligent Rehabilitation, Ministry of Education, Shanghai 201203, China
| | - Caixia Lin
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD 4067, Australia
| | - Yue Zhao
- Departments of Thoracic Surgery and State Key Laboratory of Genetic Engineering, Fudan University Shanghai Cancer Centre, Shanghai 200032, China; Institute of Thoracic Oncology, Fudan University, Shanghai 200032, China; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai 200032, China
| | - Montana Samantzis
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD 4067, Australia
| | - Petra Sedlak
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD 4067, Australia
| | - Pankaj Sah
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD 4067, Australia
| | - Matilde Balbi
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD 4067, Australia.
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Alito A, Portaro S, Leonardi G, Ventimiglia C, Bonanno F, Fenga D, Sconza C, Tisano A. Pressure Ulcers-A Longstanding Problem: A 7-Year Neurorehabilitation Unit Experience of Management, Care, and Clinical Outcomes. Diagnostics (Basel) 2023; 13:3213. [PMID: 37892035 PMCID: PMC10605717 DOI: 10.3390/diagnostics13203213] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2023] [Revised: 09/19/2023] [Accepted: 10/12/2023] [Indexed: 10/29/2023] Open
Abstract
BACKGROUND Neurological disease patients present an increased risk of developing pressure ulcers. The primary aim of this study is to evaluate the incidence and prevalence of pressure ulcers and their impact on length of stay and functional recovery. METHODS A retrospective study was conducted in a neurorehabilitation unit over a seven-year period. Data collected include demographic data, length of stay, functional evaluation, risk of pressure ulcers development, nutritional status, and skin. Pressure ulcers were classified according to the European Pressure Ulcer Advisory Panel System. RESULTS Data from 816 patients were analyzed. On admission, the authors found 236 pressure ulcers in 131 patients (about 16%), divided into stage I (25%), stage II (50%), and stage III-IV (25%). The most common sites were the heel (36%) and sacrum (29%). Among the risk factors for the development of pressure ulcers, malnutrition played a significant role, with approximately 76% of patients with pressure ulcers having mild to moderate malnutrition. CONCLUSION The presence of pressure ulcers seems to have a negative impact on the functional recovery of patients, as shown by the outcome scales and the average length of stay: 51 days versus 36 days (p < 0.01).
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Affiliation(s)
- Angelo Alito
- Department of Biomedical, Dental Sciences and Morphological and Functional Images, University of Messina, 98125 Messina, Italy
| | - Simona Portaro
- Physical Rehabilitation Medicine Department, University Hospital A.O.U. “G. Martino”, 98125 Messina, Italy
| | - Giulia Leonardi
- Physical Rehabilitation Medicine Department, University Hospital A.O.U. “G. Martino”, 98125 Messina, Italy
| | - Carlotta Ventimiglia
- Department of Adult and Developmental Human Pathology, University of Messina, 98125 Messina, Italy;
| | - Francesco Bonanno
- Department of Clinical and Experimental Medicine, University of Messina, 98125 Messina, Italy; (A.T.); (F.B.)
| | - Domenico Fenga
- Department of Orthopaedics and Traumatology, University Hospital A.O.U. “G. Martino”, 98125 Messina, Italy
| | - Cristiano Sconza
- IRCCS Humanitas Research Hospital, Rozzano, 20089 Milan, Italy
- Department of Biomedical Sciences, Humanitas University, Pieve Emanuele, 20090 Milan, Italy
| | - Adriana Tisano
- Department of Clinical and Experimental Medicine, University of Messina, 98125 Messina, Italy; (A.T.); (F.B.)
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Asogbon MG, Huai Y, Samuel OW, Jing Z, Ma Y, Liu J, Jiang Y, Fu Y, Li G, Li Y. Analysis of Artifactual Components Rejection Threshold towards Enhanced Characterization of Neural Activity in Post-Stroke Survivor. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2023; 2023:1-5. [PMID: 38083733 DOI: 10.1109/embc40787.2023.10340688] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/18/2023]
Abstract
Research advancement has spurred the usage of electroencephalography (EEG)-based neural oscillatory rhythms as a biomarker to complement clinical rehabilitation strategies for the recovery of motor functions in stroke survivors. However, the inevitable contamination of EEG signals with artifacts from various sources limits its utilization and effectiveness. Thus, the integration of Independent Component Analysis (ICA) and Independent Component Label (ICLabel) has been widely employed to separate neural activity from artifacts. A crucial step in the ICLabel preprocessing pipeline is the artifactual ICs rejection threshold (TH) parameter, which determines the overall signal's quality. For instance, selecting a high TH will cause many ICs to be rejected, thereby leading to signal over-cleaning, and choosing a low TH may result in under-cleaning of the signal. Toward determining the optimal TH parameter, this study investigates the effect of six different TH groups (NO-TH and TH1-TH6) on EEG signals recorded from post-stroke patients who performed four distinct motor imagery (MI) tasks including wrist and grasping movements. Utilizing the EEG-beta band signal at the brain's sensorimotor cortex, the performance of the TH groups was evaluated using three notable EEG quantifiers. Overall, the obtained result shows that the considered THs will significantly alter neural oscillatory patterns. Comparing the performance of the TH-groups, TH-3 with a confidence level of 60% showed consistently stronger signal desynchronization and lateralization. The correlation result shows that most of the electrode pairs with high correlation values are replicable across all the MI tasks. It also revealed that brain activity correlates linearly with distance, and a strong correlation between electrode pairs is independent of the different brain cortices. The study outcome may facilitate adequate therapeutic intervention for stroke rehab.Clinical Relevance: This study indicated that optimal selection of the ICLabel artifactual rejection threshold is essential for EEG enhancement for adequate signal characterization. Thus, a TH-values with a confidence level between 50% - 70% would be suggested for artifactual ICs rejection in MI-EEG.
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