Search Results (35)

Sophisticated voluntary movements are essential for everyday functioning, making the study of how the brain controls muscle activity a central challenge in neuroscience. Investigating corticomuscular control through non-invasive electrophysiological recordings is particularly complex due to the intricate nature of neuronal signals. To address this challenge, we present a novel experimental methodology designed to study corticomuscular control using electroencephalography (EEG) and electromyography (EMG). Our approach integrates a serious gaming biofeedback system with a specialized experimental protocol for simultaneous EEG-EMG data acquisition, optimized for corticomuscular studies. This work introduces, for the first time, a method for assessing brain–muscle functional connectivity during the execution of a demanding motor task. By identifying neuronal sources linked to muscular activity, this methodology has the potential to advance our understanding of motor control mechanisms. These insights could contribute to improving clinical practices and fostering the development of novel brain–computer interface technologies. Full article

Background: The sense of agency (SoA)—the subjective experience of controlling one’s own actions and their consequences—is a fundamental aspect of human cognition, volition, and motor control. Understanding how the SoA arises and is disrupted in neuropsychiatric disorders has significant implications for human–machine interface (HMI) design for neurorehabilitation. Traditional cognitive models of agency often fail to capture its full complexity, especially in dynamic and uncertain environments. Objective: This review synthesizes computational models—particularly predictive coding, Bayesian inference, and optimal control theories—to provide a unified framework for understanding the SoA in both healthy and dysfunctional brains. It aims to demonstrate how these models can inform the design of adaptive HMIs and therapeutic tools by aligning with the brain’s own inference and control mechanisms. Methods: I reviewed the foundational and contemporary literature on predictive coding, Kalman filtering, the Linear–Quadratic–Gaussian (LQG) control framework, and active inference. I explored their integration with neurophysiological mechanisms, focusing on the somato-cognitive action network (SCAN) and its role in sensorimotor integration, intention encoding, and the judgment of agency. Case studies, simulations, and XR-based rehabilitation paradigms using robotic haptics were used to illustrate theoretical concepts. Results: The SoA emerges from hierarchical inference processes that combine top–down motor intentions with bottom–up sensory feedback. Predictive coding frameworks, especially when implemented via Kalman filters and LQG control, provide a mechanistic basis for modeling motor learning, error correction, and adaptive control. Disruptions in these inference processes underlie symptoms in disorders such as functional movement disorder. XR-based interventions using robotic interfaces can restore the SoA by modulating sensory precision and motor predictions through adaptive feedback and suggestion. Computer simulations demonstrate how internal models, and hypnotic suggestions influence state estimation, motor execution, and the recovery of agency. Conclusions: Predictive coding and active inference offer a powerful computational framework for understanding and enhancing the SoA in health and disease. The SCAN system serves as a neural hub for integrating motor plans with cognitive and affective processes. Future work should explore the real-time modulation of agency via biofeedback, simulation, and SCAN-targeted non-invasive brain stimulation. Full article

Chronic stress significantly influences the pathogenesis of headache disorders, affecting millions worldwide. This review explores the intricate relationship between stress and headaches, focusing on the dysregulation of the hypothalamic–pituitary–adrenal (HPA) axis and autonomic nervous system (ANS). Persistent stress could lead to neuroinflammation, increased pain sensitivity, and vascular changes that could contribute to headache development and progression. The bidirectional nature of this relationship creates a vicious cycle, with recurrent headaches becoming a source of additional stress. Dysregulation of the HPA axis and ANS imbalance could amplify susceptibility to headaches, intensifying their frequency and severity. While pharmacological interventions remain common, non-pharmacological approaches targeting stress reduction, such as cognitive-behavioral therapy, biofeedback, and relaxation techniques, offer promising avenues for comprehensive headache management. By addressing the underlying stress-related mechanisms, these approaches provide a sustainable strategy to reduce headache frequency and improve patients’ quality of life. Full article

This work focuses on biohybrid systems—plants with biosensors and actuating mechanisms that enhance the ability of biological organisms to control environmental parameters, to optimize growth conditions or to cope with stress factors. Biofeedback-based phytoactuation represents the next step of development in hydroponics, vertical farming and controlled-environment agriculture. The sensing part of the discussed approach uses (electro)physiological sensors. The hydrodynamics of fluid transport systems, estimated electrochemically, is compared with sap flow data provided by heat-based methods. In vivo impedance spectroscopy enables the discrimination of water, nutrient and photosynthates in the plant stem. Additionally to plant physiology, the system measures several air/soil and environmental parameters. The actuating part includes a multi-channel power module to control phytolight, irrigation, fertilization and air/water preparation. We demonstrate several tested in situ applications of a closed-loop control based on real-time biofeedback. In vertical farming, this is used to optimize energy and water consumption, reduce growth time and detect stress. Biofeedback was able to reduce the microgreen production cycle from 7 days to 4–5 days and the production of wheatgrass from 10 days to 7–8 days, and, in combination with biofeedback-based irrigation, a 30% increase in pea biomass was achieved. Its energy optimization can reach 25–30%. In environmental monitoring, the system performs the biological monitoring of environmental pollution (a low concentration of O₃) with tomato and tobacco plants. In AI research, a complex exploration of biological organisms, and in particular the adaptation mechanisms of circadian clocks to changing environments, has been shown. This paper introduces a phytosensor system, describes its electrochemical measurements and discusses its tested applications. Full article

Movement sonification has emerged as a promising approach for rehabilitation and motion control. Despite significant advancements in sensor technologies, challenges remain in developing cost-effective, user-friendly, and reliable systems for gait detection and sonification. This study introduces a novel wearable personalised sonification and biofeedback device to enhance movement awareness for individuals with irregular gait and posture. Through the integration of inertial measurement units (IMUs), MATLAB, and sophisticated audio feedback mechanisms, the device offers real-time, intuitive cues to facilitate gait correction and improve functional mobility. Utilising a single wearable sensor attached to the L4 vertebrae, the system captures kinematic parameters to generate auditory feedback through discrete and continuous tones corresponding to heel strike events and sagittal plane rotations. A preliminary test that involved 20 participants under various audio feedback conditions was conducted to assess the system’s accuracy, reliability, and user synchronisation. The results indicate a promising improvement in movement awareness facilitated by auditory cues. This suggests a potential for enhancing gait and balance, particularly beneficial for individuals with compromised gait or those undergoing a rehabilitation process. This paper details the development process, experimental setup, and initial findings, discussing the integration challenges and future research directions. It also presents a novel approach to providing real-time feedback to participants about their balance, potentially enabling them to make immediate adjustments to their posture and movement. Future research should evaluate this method in varied real-world settings and populations, including the elderly and individuals with Parkinson’s disease. Full article

The study of brainwaves and brain–computer interfaces (BCIs) or brain–machine interfaces (BMIs) has emerged as a transformative field with the potential to revolutionize society’s well-being. This technical paper delves into the multifaceted domain of brainwave analysis and its integration with BCIs, presenting an approach that aims to enhance the fabric of society through various applications, with BCIs aiding in various assistive technologies, the detection of neurological abnormalities, and biofeedback mechanisms for improved concentration. This study explores the relationship between brainwave patterns and the levels of focus using EEG data. The results reveal distinct changes in brainwave activity, notably in the delta and beta frequency ranges, corresponding to different levels of cognitive engagement. Building upon these findings, we propose the development of a biofeedback-based concentration enhancement program for students. This study, using an approach equipped with real-time EEG monitoring and feedback mechanisms, aims to empower students to improve their concentration, particularly in educational settings. Such an innovative approach holds promise for enhancing academic performance and learning experiences, offering valuable insights into the optimization of cognitive functions through neurofeedback interventions. Full article

Insomnia, often associated with anxiety and depression, is a prevalent sleep disorder. Biofeedback (BFB) treatment can help patients gain voluntary control over physiological events such as by utilizing electroencephalography (EEG) and electromyography (EMG) power. Previous studies have rarely predicted biofeedback efficacy by measuring the changes in relative EEG power; therefore, we investigated the clinical efficacy of biofeedback for insomnia and its potential neural mechanisms. We administered biofeedback to 82 patients with insomnia, of whom 68 completed 10 sessions and 14 completed 20 sessions. The average age of the participants was 49.38 ± 12.78 years, with 26 men and 56 women. Each biofeedback session consisted of 5 min of EMG and 30 min of EEG feedback, with 2 min of data recorded before and after the session. Sessions were conducted every other day, and four scale measures were taken before the first, fifth, and tenth sessions and after the twentieth session. After 20 sessions of biofeedback treatment, scores on the Pittsburgh Sleep Quality Index (PSQI) were significantly reduced compared with those before treatment (−5.5 ± 1.43,t = −3.85, p = 0.006), and scores on the Beck Depression Inventory (BDI-II) (−7.15 ± 2.43, t = −2.94, p = 0.012) and the State-Trait Anxiety Inventory (STAI) (STAI-S: −12.36 ± 3.40, t = −3.63, p = 0.003; and STAI-T: −9.86 ± 2.38, t = −4.41, p = 0.001) were significantly lower after treatment than before treatment. Beta and theta power were significantly reduced after treatment, compared with before treatment (F = 6.25, p = 0.014; and F = 11.91, p = 0.001). Alpha power was increased after treatment, compared with before treatment, but the difference was not prominently significant (p > 0.05). EMG activity was significantly decreased after treatment, compared with before treatment (F = 2.11, p = 0.015). Our findings suggest that BFB treatment based on alpha power and prefrontal EMG relieves insomnia as well as anxiety and depression and may be associated with increased alpha power, decreased beta and theta power, and decreased EMG power. Full article

Physical fitness is of great significance to athletes in both single-player and team sports. The countermovement jump (CMJ) is one of the most commonly applied jump tests for assessing the mechanical capacities of the lower extremities. The KForce Plates system is a portable force platform that sends action-time audio and visual biofeedback to a smartphone or tablet through the KForce application, making it a suitable instrument for assessing the CMJ. The aim of the present study was to evaluate the test–retest reliability and validity of the portable force platform (KForce Plates) in the evaluation of the CMJ in collegiate athletes compared to a validated application, My Jump 2. Thirty-four collegiate professional athletes, deriving from various sports backgrounds, participated in the present study. The CMJs were reported with the portable KForce Plates and the simultaneous use of the ‘My Jump 2’ application using an iPhone 13 between days 1 and 7. Our findings revealed high test–retest reliability (ICC = 1.00 and ICC = 0.99) in-between measurements. High correlations were monitored amongst the portable KForce plates and the My Jump 2 application for measuring the CMJ (r = 0.999, p = 0.001). The Bland–Altman plot exhibits the limits of agreement amongst the portable KForce plates and the My Jump 2 application, where the bulk of the data are within the 95% CIs with an agreement of ≈1 cm. Our findings suggest that the portable KForce Plates system is a reliable and valid instrument and, therefore, can be used by experts in the sports field. Full article

Cardiac damage has been attributed to SARS-CoV-2-related pathology contributing to increased risk of vascular events. Heart rate variability (HRV) is a parameter of functional neurocardiac integrity with low HRV constituting an independent predictor of cardiovascular mortality. Whether structural cardiac damage translates into neurocardiac dysfunction in patients infected with SARS-CoV-2 remains poorly understood. Hypothesized mechanisms of possible neurocardiac dysfunction in COVID-19 comprise direct systemic neuroinvasion of autonomic control centers, ascending virus propagation along cranial nerves and cardiac autonomic neuropathy. While the relationship between the autonomic nervous system and the cytokine cascade in general has been studied extensively, the interplay between the inflammatory response caused by SARS-CoV-2 and autonomic cardiovascular regulation remains largely unclear. We reviewed the current literature on the potential diagnostic and prognostic value of autonomic neurocardiac function assessment via analysis of HRV including time domain and spectral analysis techniques in patients with COVID-19. Furthermore, we discuss potential therapeutic targets of modulating neurocardiac function in this high-risk population including HRV biofeedback and the impact of long COVID on HRV as well as the approaches of clinical management. These topics might be of particular interest with respect to multimodal pandemic preparedness concepts. Full article

The swallowing process involves complex muscle coordination mechanisms. When alterations in such mechanisms are produced by neurological conditions or diseases, a swallowing disorder known as dysphagia occurs. The instrumental evaluation of dysphagia is currently performed by invasive and experience-dependent techniques. Otherwise, non-invasive magnetic methods have proven to be suitable for various biomedical applications and might also be applicable for an objective swallowing assessment. In this pilot study, we performed a novel approach for deglutition evaluation based on active magnetic motion sensing with permanent magnet cantilever actuators. During the intake of liquids with different consistency, we recorded magnetic signals of relative movements between a stationary sensor and a body-worn actuator on the cricoid cartilage. Our results indicate the detection capability of swallowing-related movements in terms of a characteristic pattern. Consequently, the proposed technique offers the potential for dysphagia screening and biofeedback-based therapies. Full article

Haptics plays a significant role not only in the rehabilitation of neurological disorders, such as stroke, by substituting necessary cognitive information but also in human–computer interfaces (HCIs), which are now an integral part of the recently launched metaverse. This study proposes a unique, soft, monolithic haptic feedback device (SoHapS) that was directly manufactured using a low-cost and open-source fused deposition modeling (FDM) 3D printer by employing a combination of soft conductive and nonconductive thermoplastic polyurethane (TPU) materials (NinjaTek, USA). SoHapS consists of a soft bellow actuator and a soft resistive force sensor, which are optimized using finite element modeling (FEM). SoHapS was characterized both mechanically and electrically to assess its performance, and a dynamic model was developed to predict its force output with given pressure inputs. We demonstrated the efficacy of SoHapS in substituting biofeedback with tactile feedback, such as gripping force, and proprioceptive feedback, such as finger flexion–extension positions, in the context of teleoperation. With its intrinsic properties, SoHapS can be integrated into rehabilitation robots and robotic prostheses, as well as augmented, virtual, and mixed reality (AR/VR/MR) systems, to induce various types of bio-mimicked feedback. Full article

Neurological diseases including stroke and neurodegenerative disorders cause a hefty burden on the healthcare system. Survivors experience significant impairment in mobility and daily activities, which requires extensive rehabilitative interventions to assist them to regain lost skills and restore independence. The advent of remote rehabilitation architecture and enabling technology mandates the elaboration of sensing mechanisms tailored to individual clinical needs. This study aims to review current trends in the application of sensing mechanisms in remote monitoring and rehabilitation in neurological diseases, and to provide clinical insights to develop bespoke sensing mechanisms. A systematic search was performed using the PubMED database to identify 16 papers published for the period between 2018 to 2022. Teleceptive sensors (56%) were utilized more often than wearable proximate sensors (50%). The most commonly used modality was infrared (38%) and acceleration force (38%), followed by RGB color, EMG, light and temperature, and radio signal. The strategy adopted to improve the sensing mechanism included a multimodal sensor, the application of multiple sensors, sensor fusion, and machine learning. Most of the stroke studies utilized biofeedback control systems (78%) while the majority of studies for neurodegenerative disorders used sensors for remote monitoring (57%). Functional assessment tools that the sensing mechanism may emulate to produce clinically valid information were proposed and factors affecting user adoption were described. Lastly, the limitations and directions for further development were discussed. Full article

Concurrent biofeedback has been demonstrated to be an effective strategy for reducing running-related injuries (RRI) [1–3]. The majority of these RRI are overuse injuries related to impact accelerations [4,5]. However, information regarding impact accelerations is not accessible to the entire population since it requires an accelerometry system. The objective of this study was to investigate the validity and reliability of a new accelerometry system placed directly into the treadmill (AccTrea) and compare it to the traditional system placed directly on the athlete’s body (AccAthl). Thirty recreational athletes with no history of lower body injuries performed two running tests on different days. They ran for 5 min at 10 km/h and at a 0% slope and acceleration impacts and spatiotemporal parameters were collected in two sets of 10 s during the last minute taken in each measurement session. The first session intended to assess the validity of an AccTrea versus an AccAthl, and the second session intended to test its reliability. The results showed that AccTrea is a valid and reliable tool for measuring spatiotemporal parameters such as step length (validity intraclass correlation coefficient (ICC) = 0.94; reliability ICC = 0.92), step time (validity ICC = 0.95; reliability ICC = 0.96), and step frequency (validity ICC = 0.95; reliability ICC = 0.96) during running. The peak acceleration impact variables manifested a high reliability for both left (reliability ICC = 0.88) and right legs (reliability ICC = 0.85), and the peak impact asymmetry demonstrated a modest validity (ICC = 0.55). The valid and reliable results make the AccTrea system an appropriate tool with which to inform athletes about their running mechanics, bringing the laboratory data closer to the running community.  Full article

This narrative review is aimed at presenting the galvanic skin response (GSR) Biofeedback method and possibilities for its application in persons with mental disorders as a modern form of neurorehabilitation. In the treatment of mental disorders of various backgrounds and courses, attention is focused on methods that would combine pharmacological treatment with therapies improving functioning. Currently, the focus is on neuronal mechanisms which, being physiological markers, offer opportunities for correction of existing deficits. One such indicator is electrodermal activity (EDA), providing information about emotions, cognitive processes, and behavior, and thus, about the function of various brain regions. Measurement of the galvanic skin response (GSR), both skin conductance level (SCL) and skin conductance responses (SCR), is used in diagnostics and treatment of mental disorders, and the training method itself, based on GSR Biofeedback, allows for modulation of the emotional state depending on needs occurring. Summary: It is relatively probable that neurorehabilitation based on GSR-BF is a method worth noticing, which—in the future—can represent an interesting area of rehabilitation supplementing a comprehensive treatment for people with mental disorders. Full article

The vagus or “wandering” nerve is the main branch of the parasympathetic nervous system (PNS), innervating most internal organs crucial for health. Activity of the vagus nerve can be non-invasively indexed by heart-rate variability parameters (HRV). Specific HRV parameters predict less all-cause mortality, lower risk of and better prognosis after myocardial infarctions, and better survival in cancer. A non-invasive manner for self-activating the vagus is achieved by performing a slow-paced breathing technique while receiving visual feedback of one’s HRV, called HRV-biofeedback (HRV-B). This article narratively reviews the biological mechanisms underlying the role of vagal activity and vagally mediated HRV in hypertension, diabetes, coronary heart disease (CHD), cancer, pain, and dementia. After searching the literature for HRV-B intervention studies in each condition, we report the effects of HRV-B on clinical outcomes in these health conditions, while evaluating the methodological quality of these studies. Generally, the levels of evidence for the benefits of HRV-B is high in CHD, pain, and hypertension, moderate in cancer, and poor in diabetes and dementia. Limitations and future research directions are discussed. Full article