Article
Chemistry, Analytical
Francisco Perez-Reynoso, Nein Farrera-Vazquez, Cesar Capetillo, Nestor Mendez-Lozano, Carlos Gonzalez-Gutierrez, Emmanuel Lopez-Neri
Summary: This study presents principles for the development of interfaces in physiotherapy or rehabilitation assistance systems and proposes a solution to the customization problem. By utilizing sEMG database and neural networks, the system enables personalized therapy and adaptation to individuals. The results demonstrate that customizing the interface reduces the learning curve, enhancing the effectiveness of the system.
Article
Engineering, Biomedical
I-Ling Yeh, Jessica Holst-Wolf, Naveen Elangovan, Anna Vera Cuppone, Kamakshi Lakshminarayan, Leonardo Capello, Lorenzo Masia, Juergen Konczak
Summary: This study provides evidence that non-visual proprioceptive training can lead to rapid improvements in proprioceptive function in chronic stroke survivors. However, it remains inconclusive whether such training transfers to untrained motor tasks.
JOURNAL OF NEUROENGINEERING AND REHABILITATION
(2021)
Article
Engineering, Biomedical
Marco Crepaldi, Rune Thorsen, Johanna Jonsdottir, Silvia Scarpetta, Lorenzo De Michieli, Mirco Di Salvo, Giorgio Zini, Matteo Laffranchi, Maurizio Ferrarin
Summary: This study successfully developed a wearable MeCFES device FITFES through user-centered design for the rehabilitation of the hemiplegic arm. The design includes minimal viable features and functionalities to ensure portability and usability of the device.
IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING
(2021)
Review
Chemistry, Multidisciplinary
Tao Song, Zhe Yan, Shuai Guo, Yuwen Li, Xianhua Li, Fengfeng Xi
Summary: Surface electromyography (sEMG) is a promising technology for controlling robots through human-machine interfaces by capturing muscle activation signals. This article provides an overview of sEMG-based robot control, including signal processing and classification methods, as well as robot control strategies and methods based on sEMG. The article discusses the steps in sEMG signal processing, commonly used data acquisition and feature extraction methods, and introduces machine-learning-based pattern recognition methods for sEMG signal classification. It also classifies user intent-based robot control strategies into three categories and compares their control methods and applicable scenarios.
APPLIED SCIENCES-BASEL
(2023)
Review
Engineering, Biomedical
Silvia Campagnini, Chiara Arienti, Michele Patrini, Piergiuseppe Liuzzi, Andrea Mannini, Maria Chiara Carrozza
Summary: Rehabilitation medicine is undergoing a new development phase, with clinical practice expected to change significantly due to rigorous clinical trials and personalized medical therapies. The emerging field of Rehabilomics relies on biomedical data collection and analysis. This study aims to systematically review machine learning algorithms for predicting motor functional recovery in post-stroke patients after treatment.
JOURNAL OF NEUROENGINEERING AND REHABILITATION
(2022)
Article
Medicine, General & Internal
Sarah Northcott, Shirley Thomas, Kirsty James, Alan Simpson, Shashivadan Hirani, Rachel Barnard, Katerina Hilari
Summary: The results of the study indicate that the Solution Focused Brief Therapy is feasible and acceptable for individuals with aphasia, including those with severe aphasia. The high retention and adherence rates suggest that a definitive randomized controlled trial of the intervention would be feasible. The qualitative data also support the acceptability of the therapy approach.
Article
Chemistry, Multidisciplinary
Francesco Scotto di Luzio, Francesca Cordella, Marco Bravi, Fabio Santacaterina, Federica Bressi, Silvia Sterzi, Loredana Zollo
Summary: The study aims to investigate hand muscular synergies in chronic stroke patients and evaluate potential benefits of robot-aided rehabilitation treatment for the hand. Seven chronic stroke patients with mild-to-moderate impairment were involved in a 5-week treatment with a hand exoskeleton. Results showed a high degree of similarity in muscle synergies between healthy and injured limbs, indicating potential effects of the rehabilitation treatment.
APPLIED SCIENCES-BASEL
(2022)
Article
Engineering, Biomedical
Alexa B. Keeling, Mark Piitz, Jennifer A. Semrau, Michael D. Hill, Stephen H. Scott, Sean P. Dukelow
Summary: The study developed robotic upper extremity therapy tasks for subacute stroke patients and found significant improvements in FMA UE, ARAT, FIM, and Visually Guided Reaching scores in the robotic therapy group post-intervention. However, only FIM and Arm Position Match scores improved in the control group over the same time period. The Kinarm therapy tasks show potential for improving outcomes in subacute stroke, but further studies are needed to confirm the benefits in a larger cohort.
JOURNAL OF NEUROENGINEERING AND REHABILITATION
(2021)
Article
Chemistry, Analytical
Sophia Otalora, Felipe Ballen-Moreno, Luis Arciniegas-Mayag, Carlos A. Cifuentes, Marcela Munera
Summary: This study evaluates the effects of the robotic ankle orthosis T-FLEX during cooperative assistance with the AGoRA unilateral lower-limb exoskeleton. The results show a reduction in muscle activity when adding T-FLEX to the exoskeleton, but no differences in gait parameters were found. However, stability is preserved when comparing the two legs. Future research should focus on evaluating these devices in ground tests with both healthy subjects and pathological patients.
Article
Engineering, Electrical & Electronic
Hyeyun Lee, Soyoung Lee, Jaeseong Kim, Heesoo Jung, Kyung Jae Yoon, Srinivas Gandla, Hogun Park, Sunkook Kim
Summary: With the help of AI-based algorithms, the accuracy of gesture recognition using sEMG signals has increased. An array of bipolar stretchable sEMG electrodes, combined with a self-attention-based graph neural network, is developed to achieve highly accurate gesture recognition. The system can differentiate static and dynamic gestures with about 97% accuracy using a single trial per gesture. The array also has skin-like attributes and can provide stable EMG signals even after long-term testing and multiple reuses.
NPJ FLEXIBLE ELECTRONICS
(2023)
Review
Physiology
Yunxia Huo, Xiaohan Wang, Weihua Zhao, Huijing Hu, Le Li
Summary: Objective: Research shows the promise and efficacy of EMG-based robot interventions in improving motor function in stroke survivors. However, it is controversial whether EMG-based robot is more effective than conventional therapies. This study compares the effects of EMG-based robot and conventional rehabilitation techniques on upper limb motor control, spasticity, and activity limitation in stroke survivors.
FRONTIERS IN PHYSIOLOGY
(2023)
Article
Clinical Neurology
Reeman Marzouqah, Laavanya Dharmakulaseelan, David R. Colelli, C. J. Lindo, Yakdehikandage S. Costa, Trevor Jairam, Kathy Xiong, Brian J. Murray, Joyce L. Chen, Kevin Thorpe, Yana Yunusova, Mark I. Boulos
Summary: This study aimed to determine the feasibility of using oropharyngeal exercise as an alternative therapy for obstructive sleep apnea in stroke or transient ischemic attack patients. The results showed that oropharyngeal exercise improved tongue pressures, reduced sleep apnea severity, decreased daytime sleepiness, and enhanced quality of life.
JOURNAL OF SLEEP RESEARCH
(2023)
Article
Neurosciences
Francesco Infarinato, Paola Romano, Michela Goffredo, Marco Ottaviani, Daniele Galafate, Annalisa Gison, Simone Petruccelli, Sanaz Pournajaf, Marco Franceschini
Summary: This study examined muscle activation patterns in subacute stroke patients undergoing Overground Robot-Assisted Gait Training (o-RAGT) and conventional therapy. Significant functional gains in gait and increased bilateral symmetry of Tibialis Anterior muscles were observed post-treatment. The study concluded that complex intensive rehabilitation with o-RAGT and conventional therapy led to improved gait function in stroke patients, highlighting the importance of muscle activation patterns in functional recovery.
Review
Engineering, Electrical & Electronic
Haiyang Yang, Jiacheng Wan, Ying Jin, Xixia Yu, Yinfeng Fang
Summary: Intelligent poststroke rehabilitation using electromyographic (EMG) signals and electroencephalographic (EEG) signals has attracted great attention worldwide. This article provides an overview of using EMG and EEG signals in rehabilitation, focusing on the changes after stroke and the technological interventions. The feasibility of motor function rehabilitation with these signals is analyzed, showing that the combination of EEG and EMG signals is more favorable for rehabilitation than using a single signal.
IEEE SENSORS JOURNAL
(2022)
Article
Health Care Sciences & Services
Arkers Kwan Ching Wong, Jonathan Bayuo, Frances Kam Yuet Wong, Vivian Wai Yan Kwok, Bernard Man Kam Yuen, Ching Sing Fong, Shun Tim Chan, Hoi Lam Pung, Oi Lam Kwek
Summary: The aim of this study is to determine the feasibility and effects of telecare consultations in nurse-led post-acute stroke clinics. The study adopts a quasi-experimental design and participants will receive three secondary stroke care consultations provided via telecare. The findings of this study may help facilitate the implementation of telecare consultations in nurse-led post-acute stroke clinics and benefit stroke survivors with mobility restrictions.
Article
Engineering, Biomedical
Dario Farina, Ivan Vujaklija, Rickard Branemark, Anthony M. J. Bull, Hans Dietl, Bernhard Graimann, Levi J. Hargrove, Klaus-Peter Hoffmann, He (Helen) Huang, Thorvaldur Ingvarsson, Hilmar Bragi Janusson, Kristleifur Kristjansson, Todd Kuiken, Silvestro Micera, Thomas Stieglitz, Agnes Sturma, Dustin Tyler, Richard F. Ff Weir, Oskar C. Aszmann
Summary: This Perspective discusses the development and clinical application of high-performance bionic limbs, emphasizing the use of different technologies, such as osseointegration, neural signal amplification, and muscle sensors, to create better performing bionic limbs.
NATURE BIOMEDICAL ENGINEERING
(2023)
Article
Engineering, Biomedical
Leonardo Pollina, Fabio Vallone, Matteo M. Ottaviani, Ivo Strauss, Lucia Carlucci, Fabio A. Recchia, Silvestro Micera, Sara Moccia
Summary: Bioelectronic medicine is an emerging field that aims to develop closed-loop neuromodulation protocols for the autonomic nervous system (ANS) to treat various disorders. In this study, a lightweight learning-based decoder was developed to classify cardiovascular and respiratory functional challenges from neural signals acquired from intraneural electrodes implanted in the cervical vagus nerve (VN) of anesthetized pigs. The algorithm achieved high balanced accuracy (BA) values and identified 500 ms as the optimal temporal windowing duration for classification with low computational execution time.
JOURNAL OF NEURAL ENGINEERING
(2022)
Article
Engineering, Biomedical
Outman Akouissi, Stephanie P. Lacour, Silvestro Micera, Antonio DeSimone
Summary: In this study, the mechanical stresses induced on the peripheral nerve by the implant's micromotion were modeled using finite element analysis. The results indicate that the material, geometry, and surface coating of the implant are crucial for its stability and durability. Specifically, implants with smooth edges, materials that are no more than three orders of magnitude stiffer than the nerve, and innovative geometries that redistribute micromotion-associated loads can improve the long-term performance of peripheral nerve implants.
JOURNAL OF NEURAL ENGINEERING
(2022)
Review
Clinical Neurology
Nawal Kinany, Elvira Pirondini, Silvestro Micera, Dimitri Van De Ville
Summary: The spinal cord, often overlooked in human neuroscience research, is now recognized as active and plastic. This review argues that fMRI can be utilized beyond the brain to unravel spinal mechanisms involved in human behaviors. It outlines strategies and applications of spinal cord fMRI, highlighting its potential to address fundamental and clinical questions.
Article
Neurosciences
Alessandro Panarese, Matteo Vissani, Nicolo Meneghetti, Eleonora Vannini, Marina Cracchiolo, Silvestro Micera, Matteo Caleo, Alberto Mazzoni, Laura Restani
Summary: Epileptic brain is the result of transforming normal neuronal populations into hyperexcitable networks, which leads to fundamental alterations of circuit function and behavior. In a mouse model of focal epilepsy, we found interlaminar alterations in sensory processing of the visual cortex, which may account for visual dysfunction observed in epileptic subjects.
Editorial Material
Engineering, Biomedical
Tamar R. Makin, Silvestro Micera, Lee E. Miller
Summary: Robotic fingers and arms can enhance the motor abilities of non-disabled individuals, but they face barriers and challenges in neurocognitive motor control.
NATURE BIOMEDICAL ENGINEERING
(2023)
Article
Chemistry, Physical
Raghav Garg, Nicolette Driscoll, Sneha Shankar, Todd Hullfish, Eugenio Anselmino, Francesco Iberite, Spencer Averbeck, Manini Rana, Silvestro Micera, Josh R. Baxter, Flavia Vitale
Summary: This study introduces a new MXtrode HDsEMG array fabricated from liquid-phase processing of Ti3C2Tx, which shows great potential for clinical applications. Compared to traditional wireless electromyography sensors, the MXtrode array provides higher quality and spatial resolution, with easy customization of array geometry and gel-free, minimal skin preparation for enhanced usability and comfort. Moreover, the study demonstrates the broad clinical applicability of MXtrodes in neuromuscular diagnostics and rehabilitation.
Article
Materials Science, Multidisciplinary
Gianni Ciofani, Marco Campisi, Clara Mattu, Roger D. Kamm, Valeria Chiono, Aji Alex Moothedathu Raynold, Joao S. Freitas, Eugenio Redolfi Riva, Silvestro Micera, Carlotta Pucci, Fernando Novio, Julia Lorenzo, Daniel Ruiz-Molina, Giulia Sierri, Francesca Re, Hannah Wunderlich, Prachi Kumari, Kristen L. Kozielski, Mounia Chami, Attilio Marino, Lino Ferreira
Summary: In recent years, significant efforts have been made to address the challenges of treating pathologies in the central nervous system (CNS), due to the presence of the blood-brain barrier. This article presents a roadmap of the latest developments, challenges, and opportunities in this field. The format of the roadmap encourages collaboration among experts across disciplines, emphasizing that it is a forward-looking summary rather than a comprehensive review.
JOURNAL OF PHYSICS-MATERIALS
(2023)
Article
Engineering, Biomedical
Daniela De Luca, Sara Moccia, Leonardo Lupori, Raffaele Mazziotti, Tommaso Pizzorusso, Silvestro Micera
Summary: This study aims to develop an algorithm that can automatically associate a cortical activation pattern with the visual stimulus that generated it. By conducting experiments on three mice using wide-field calcium imaging, a convolutional neural network (CNN) was trained to classify different visual stimuli. The results show that this method can be used to classify cortical responses to simple visual stimuli, offering a potential alternative to existing decoding methodologies.
JOURNAL OF NEURAL ENGINEERING
(2023)
Article
Engineering, Biomedical
Elena Sibilano, Antonio Brunetti, Domenico Buongiorno, Michael Lassi, Antonello Grippo, Valentina Bessi, Silvestro Micera, Alberto Mazzoni, Vitoantonio Bevilacqua
Summary: This study aims to design and implement a deep learning model for classifying subjects in the prodromic states of Alzheimer's disease (AD) based on resting-state EEG signals. The model achieved good performance in discriminating subjective cognitive decline and mild cognitive impairment, demonstrating the potential of DL approaches in supporting the use of non-invasive and economical techniques for patient stratification.
JOURNAL OF NEURAL ENGINEERING
(2023)
Article
Multidisciplinary Sciences
Francesco Iberite, Jonathan Muheim, Outman Akouissi, Simon Gallo, Giulio Rognini, Federico Morosato, Andre Clerc, Magnus Kalff, Emanuele Gruppioni, Silvestro Micera, Solaiman Shokur
Summary: Using a portable thermal device, heat sensation can be provided to amputees' phantom hands, improving their sense of touch and quality of life.
Review
Pharmacology & Pharmacy
Marta Bianchini, Silvestro Micera, Eugenio Redolfi Riva
Summary: When traumatic events cause complete denervation, muscle functional recovery is severely hindered. The use of biodegradable polymeric tubular scaffolds offers a potential solution by creating a biomimetic environment to support nerve regeneration. However, in cases of significant peripheral nerve damage, the regenerative capabilities are limited. Therefore, the development of biodegradable micro-nanostructured polymeric carriers for controlled and sustained release of molecules is a crucial challenge to enhance nerve regeneration. Drug delivery systems (DDSs) are promising solutions in this field as they allow targeted delivery of therapeutic molecules to maximize efficacy. This review aims to summarize recent advancements in biodegradable polymeric DDS for nerve regeneration and discuss their potential in improving regenerative performance in severe nerve damage scenarios.
Article
Neuroimaging
Michael Lassi, Carlo Fabbiani, Salvatore Mazzeo, Rachele Burali, Alberto Arturo Vergani, Giulia Giacomucci, Valentina Moschini, Carmen Morinelli, Filippo Emiliani, Maenia Scarpino, Silvia Bagnoli, Assunta Ingannato, Benedetta Nacmias, Sonia Padiglioni, Silvestro Micera, Sandro Sorbi, Antonello Grippo, Valentina Bessi, Alberto Mazzoni
Summary: Alzheimer's disease (AD) pathological changes can occur decades before cognitive decline symptoms. The first clinical pre-symptom of possible AD might be subjective cognitive decline (SCD), followed by mild cognitive impairment (MCI). However, the neural correlates of these stages are not fully understood. Recent studies suggest that analyzing EEG can help characterize SCD and MCI. This study used EEG analysis to identify significant markers differentiating SCD, MCI, and healthy individuals, finding differences in the temporal structure of microstates patterns.
NEUROIMAGE-CLINICAL
(2023)
Proceedings Paper
Engineering, Electrical & Electronic
Daniela De Luca, Sara Moccia, Leonardo Lupori, Raffaele Mazziotti, Tommaso Pizzorusso, Silvestro Micera
Summary: In this study, a convolutional neural network (CNN) was proposed to automatically detect what is present in the visual field of an animal. By using widefield calcium brain images, researchers trained a CNN model with an accuracy of 78.46% to predict visual stimuli, demonstrating the feasibility of automated detection of animal visual field.
Review
Computer Science, Information Systems
Tommaso Proietti, Emilia Ambrosini, Alessandra Pedrocchi, Silvestro Micera
Summary: This work provides an overview of the development of upper-limb rehabilitation assistive technologies, discussing three major revolutions in the field (end-effector robots, rigid exoskeletons, and soft exosuits), and reviewing the application of these technologies in clinical populations. By critically analyzing and comparing the technologies, it aims to identify new potential directions for development.