Article
Engineering, Biomedical
Christos Stergiadis, Vasiliki-Despoina Kostaridou, Manousos A. Klados
Summary: This study evaluates the performance of the five most common BSS algorithms and finds that Adaptive Mixture ICA was the best performing method.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2022)
Review
Engineering, Biomedical
Dasa Gorjan, Klaus Gramann, Kevin De Pauw, Uros Marusic
Summary: This article discusses the use of EEG measurements in dynamic environments to increase the ecological validity of research and explores different methods for artifact removal. However, further development and evaluation of methods for removing EEG artifacts in dynamic environments are still needed.
JOURNAL OF NEURAL ENGINEERING
(2022)
Review
Neurosciences
Seongmi Song, Andrew D. Nordin
Summary: Studying human brain activity during locomotion is crucial for understanding neural circuits and developing rehabilitation and performance enhancement technologies. While technical barriers have hindered neuroimaging during gait, advancements in non-invasive EEG technology have offered new possibilities.
FRONTIERS IN HUMAN NEUROSCIENCE
(2021)
Review
Chemistry, Analytical
Kais Belwafi, Sofien Gannouni, Hatim Aboalsamh
Summary: BCI systems have a wide range of applications in restoring capabilities for people with severe motor disabilities, with a growing number of systems being developed. There is a significant interest in implementing BCIs on portable platforms, with smaller size, faster loading times, lower cost, fewer resources, and lower power consumption compared to full PCs.
Article
Neurosciences
Yongcheng Li, Po T. Wang, Mukta P. Vaidya, Robert D. Flint, Charles Y. Liu, Marc W. Slutzky, An H. Do
Summary: The study proposed a modified ICA model called ERASE for effectively removing EMG artifacts from EEG by adding real EMG sources as reference. The results showed that ERASE significantly improved the separation of EEG signal and EMG artifacts, while preserving the expected EEG features related to movement. This approach offers a promising method for enhancing the effectiveness of ICA in removing EMG artifacts from EEG recordings.
FRONTIERS IN NEUROSCIENCE
(2021)
Article
Chemistry, Analytical
Rodrigo Vitorio, Ellen Lirani-Silva, Diego Orcioli-Silva, Victor Spiandor Beretta, Anderson Souza Oliveira, Lilian Teresa Bucken Gobbi
Summary: This study investigated whether people with Parkinson's disease (PD) show distinct brain activity during regular walking and obstacle avoidance compared to healthy individuals. The results showed that during regular walking, PD patients had higher alpha/beta ratio in the left sensorimotor cortex. When approaching obstacles, both groups decreased alpha and beta power in the premotor and right sensorimotor cortices, and increased gamma power in the primary visual cortex. Only PD patients decreased alpha power and alpha/beta ratio in the left sensorimotor cortex. These findings suggest that PD affects cortical control of walking and changes electrocortical dynamics during obstacle avoidance.
Article
Biochemical Research Methods
Nigel C. Rogasch, Mana Biabani, Tuomas P. Mutanen
Summary: Combining transcranial magnetic stimulation (TMS) with electroencephalography (EEG) is a popular method for studying neural circuits. However, measuring neural responses to TMS using EEG is challenging due to unique artifacts. This paper reviews these artifacts and offline cleaning methods. Open science practices and open-source toolboxes have improved the availability and reproducibility of cleaning methods. The choice of cleaning pipeline affects TMS-evoked potentials (TEPs), highlighting the need for validation and comparison of cleaning methods.
JOURNAL OF NEUROSCIENCE METHODS
(2022)
Article
Neurosciences
Joanna E. M. Scanlon, Nadine Svenja Josee Jacobsen, Marike C. Maack, Stefan Debener
Summary: This study compared the performance of active and passive signal transmission electrodes during a mobile auditory task and found significant decreases in P3 amplitude, post-trial rejection trial numbers, and signal-to-noise ratio while walking. However, there were no significant differences in signal quality between the two electrode configurations. The study concluded that adequate use of a passive EEG electrode system can achieve signal quality equivalent to that of an active system during a mobile task.
EUROPEAN JOURNAL OF NEUROSCIENCE
(2021)
Article
Chemistry, Analytical
Colton B. Gonsisko, Daniel P. Ferris, Ryan J. Downey
Summary: This study tested the application of the iCanClean algorithm in the analysis of mobile electroencephalography (EEG) data and found that it improves the decomposition of EEG data corrupted by walking motion artifacts. It increases the number of correctly identified components.
Article
Neurosciences
Mingqi Zhao, Gaia Bonassi, Jessica Samogin, Gaia Amaranta Taberna, Camillo Porcaro, Elisa Pelosin, Laura Avanzino, Dante Mantini
Summary: Gait is a complex activity controlled by the nervous system, and understanding the neurokinematic and neuromuscular connectivity patterns in the brain during gait is important. This study used mobile brain/body imaging techniques to investigate gait-related brain-body connectivity and found that myogenic signals are more discriminative than kinematic signals in evaluating brain-body connectivity. The study also identified robust responses in the alpha and beta bands in the primary sensorimotor cortex. The findings demonstrate the potential of using hdEEG for studying gait-related brain-body connectivity.
FRONTIERS IN NEUROSCIENCE
(2022)
Article
Clinical Neurology
Richard Somervail, J. Cataldi, A. M. Stephan, F. Siclari, G. D. Iannetti
Summary: Whole-night sleep electroencephalogram (EEG) is often contaminated by large-amplitude artifacts. Artifact Subspace Reconstruction (ASR) is a promising approach to automatically clean EEG data, but it relies on calibration which can be problematic in whole-night EEG data. In this study, we validated ASR for cleaning sleep EEG and provided a procedure for automatic and rapid cleaning of whole-night EEG data. The procedure is freely available in a plugin called Dusk2Dawn.
Article
Neurosciences
Negin Gholamipourbarogh, Filippo Ghin, Moritz Mueckschel, Christian Frings, Ann-Kathrin Stock, Christian Beste
Summary: This study aims to investigate the neural mechanisms of response inhibition, particularly how the representational dynamics of inhibitory control processes are modulated in automatic and controlled modes. By combining EEG signal analysis methods with source localization, we gained insights into the fine-grained neural dynamics of response inhibition. The results showed that response inhibition was better in a controlled mode, and the neural dynamics involved coding of both stimulus-related information and rules of stimulus-motor program association. Additionally, we identified two independent neural activity patterns with differences in the temporal stability of the representational content. Source localization analysis revealed the importance of the precuneus and inferior parietal cortex regions in representing stimulus-response selection codes.
HUMAN BRAIN MAPPING
(2023)
Review
Chemistry, Analytical
Janis Peksa, Dmytro Mamchur
Summary: This paper gives a comprehensive overview of the current state-of-the-art in brain-computer interfaces (BCI). It introduces the basic principles and widely used platforms of BCIs. It examines the various components of a BCI system, including hardware, software, and signal processing algorithms. It discusses the current research trends and potential future applications of BCI technology in medical, educational, and other fields, as well as the challenges that need to be addressed for widespread adoption.
Article
Biology
Giuseppe Placidi, Luigi Cinque, Matteo Polsinelli
Summary: The study introduces a fully automatic, effective, fast, and scalable framework for real-time artifact recognition in EEG signals for online BCI applications. By utilizing optimized CNN networks for topoplot classification, the framework demonstrates high overall accuracy, sensitivity, and specificity on public EEG datasets.
COMPUTERS IN BIOLOGY AND MEDICINE
(2021)
Article
Engineering, Biomedical
Shaswati Dash, Pranjali Gajbhiye, Phattarapong Sawangjai, Guntitat Sawadwuthikul, Thapanun Sudhawiyangkul, Rajesh Kumar Tripathy, Ram Bilas Pachori
Summary: In this paper, a novel filter-bank-based hybrid approach is proposed to eliminate ocular artifacts from EEG signals. The approach combines multiscale decomposition and filter combination to achieve good denoising performance in removing eye movement and eye blink artifacts from EEG signals.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2023)
Article
Physiology
Morteza Yaserifar, Anderson Souza Oliveira
Summary: This study investigated the impact of running surfaces on inter-muscular coordination during running. The results showed that running surface hardness had a certain influence on the similarity of muscle weightings, but no significant differences were found in weighting coefficients. There were no temporal differences in activation signals across running surfaces. However, the activation duration was significantly shorter for treadmill running compared to other surfaces.
EUROPEAN JOURNAL OF APPLIED PHYSIOLOGY
(2023)
Article
Neurosciences
Mateus Andre Favretto, Felipe Rettore Andreis, Sandra Cossul, Francesco Negro, Anderson Souza Oliveira, Jefferson Luiz Brum Marques
Summary: The aim of this study was to determine whether HD-sEMG is sensitive to detecting changes in motor unit behavior in healthy adults and type 2 diabetes mellitus patients with different levels of DPN. The results support the use of HD-SEMG as a method to detect peripheral and central changes related to DPN.
JOURNAL OF ELECTROMYOGRAPHY AND KINESIOLOGY
(2023)
Article
Chemistry, Analytical
Colton B. Gonsisko, Daniel P. Ferris, Ryan J. Downey
Summary: This study tested the application of the iCanClean algorithm in the analysis of mobile electroencephalography (EEG) data and found that it improves the decomposition of EEG data corrupted by walking motion artifacts. It increases the number of correctly identified components.
Article
Biophysics
Angel Bu, Mhairi K. MacLean, Daniel P. Ferris
Summary: Bodyweight supported walking is a common gait rehabilitation method that can provide insights into walking biomechanics. In this study, we used a neuromuscular model to investigate the effects of varying bodyweight support levels on muscle force, activation, and fiber length during overground walking. The results showed that the lateral and medial gastrocnemius muscles had decreased force and activation with higher levels of support, while the soleus muscle had no significant change in activation but decreased force. These findings highlight the decoupling of muscle force from effective bodyweight during bodyweight supported walking.
JOURNAL OF BIOMECHANICS
(2023)
Article
Multidisciplinary Sciences
Evangelia-Regkina Symeonidou, Nicole M. Esposito, Roehl-Dean Reyes, Daniel P. Ferris
Summary: The goals of this study were to determine the effects of practicing walking on a treadmill mounted balance beam on sacral marker movement kinematics and balance measures. Participants trained with intermittent visual occlusions or unperturbed vision. Results showed significant changes in sacral marker velocity after training, but no significant group differences. There was limited evidence of balance transfer from beam-walking practice to treadmill walking and standing balance.
Article
Chemistry, Analytical
Rodrigo Vitorio, Ellen Lirani-Silva, Diego Orcioli-Silva, Victor Spiandor Beretta, Anderson Souza Oliveira, Lilian Teresa Bucken Gobbi
Summary: This study investigated whether people with Parkinson's disease (PD) show distinct brain activity during regular walking and obstacle avoidance compared to healthy individuals. The results showed that during regular walking, PD patients had higher alpha/beta ratio in the left sensorimotor cortex. When approaching obstacles, both groups decreased alpha and beta power in the premotor and right sensorimotor cortices, and increased gamma power in the primary visual cortex. Only PD patients decreased alpha power and alpha/beta ratio in the left sensorimotor cortex. These findings suggest that PD affects cortical control of walking and changes electrocortical dynamics during obstacle avoidance.
Article
Chemistry, Analytical
Cristina-Ioana Pirscoveanu, Anderson Souza Oliveira
Summary: Accelerometry is a popular method for assessing human movement outdoors. This study evaluated whether data from a fitness smartwatch and chest strap could detect changes in running style and found that these variables had limited sensitivity and could not be associated with lower limb vertical loading.
Article
Medicine, General & Internal
Jens Eg Norgaard, Stig Andersen, Jesper Ryg, Andrew James Thomas Stevenson, Jane Andreasen, Anderson Souza Oliveira, Mathias Brix Danielsen, Martin Gronbech Jorgensen
Summary: This study evaluated the effects of a 4-session treadmill perturbation-based balance training (PBT) intervention on daily-life fall rates among older adults. The results showed that the PBT intervention did not have a significant effect on daily-life fall rates, but there was a significant decrease in falls in the laboratory setting.
Article
Neurosciences
Amanda Studnicki, Daniel P. Ferris
Summary: Traditional human electroencephalography experiments in visuomotor processing often lack ecological validity due to controlled laboratory conditions. This study aimed to quantify the electrocortical dynamics of the parieto-occipital cortices during table tennis using high-density electroencephalography. The results suggest that training with a ball machine elicits different brain dynamics compared to training with a human opponent.
Article
Physiology
Cristina-Ioana Pirscoveanu, Anderson Souza Oliveira
Summary: This study used biomechanical parameters extracted from a commercial running smartwatch to predict the rate of perceived exertions during running. The results show that using subject-dependent regression models can accurately predict RPE, opening new possibilities for improving training workload monitoring.
EUROPEAN JOURNAL OF APPLIED PHYSIOLOGY
(2023)
Article
Neurosciences
Noelle A. Jacobsen, Daniel P. Ferris
Summary: Mobile brain imaging technology has revealed that multiple brain areas, including the sensorimotor and posterior parietal cortices, are involved in gait adaptation during human walking. The alpha and beta band power in these brain areas decreases during early adaptation to split-belt walking, but gradually recovers to pre-adaptation levels by the end of the adaptation period. These findings provide important insights for future studies on gait adaptation and its disorders.
JOURNAL OF PHYSIOLOGY-LONDON
(2023)
Article
Chemistry, Analytical
Ryan J. Downey, Daniel P. Ferris
Summary: The goal of this study was to test a novel approach (iCanClean) for removing non-brain sources from scalp EEG data recorded in mobile conditions. The study found that iCanClean consistently outperformed the other three methods in removing artifacts and preserving brain activity, regardless of the type or number of artifacts present.
Article
Engineering, Biomedical
Rachel L. Hybart, Daniel P. Ferris
Summary: This study aimed to determine if robotic ankle exoskeleton users decrease triceps surae muscle activity when using proportional myoelectric control. Healthy young participants walked with commercially available electromechanical ankle exoskeletons. The results showed that there was a small non-significant decrease in triceps surae muscle activity after walking with the exoskeleton for 30 minutes.
IEEE OPEN JOURNAL OF ENGINEERING IN MEDICINE AND BIOLOGY
(2023)
Article
Engineering, Biomedical
W. Sebastian Barrutia, James Bratt, Daniel P. Ferris
Summary: The development of assistive lower-limb exoskeletons is time-consuming and testing them on vulnerable populations such as children raises safety concerns. Mechanical phantoms that replicate lower-limb kinematics provide a fast validation method for exoskeletons, but most phantoms fail to capture soft tissue deformation at the human/exoskeleton interface. We have developed a methodology using a mechanical phantom capable of emulating knee kinematics and soft tissue deformation to quickly test and validate knee exoskeletons.
IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING
(2023)
Article
Engineering, Industrial
Matteo Musso, Anderson Souza Oliveira, Shaoping Bai
Summary: Exoskeletons have been found to have an impact on muscle activity in commonly performed tasks in the manufacturing and construction sectors. The influence of exoskeletons varies depending on the task and arm posture.
APPLIED ERGONOMICS
(2024)