Search Results (18)

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

Upper limb disabilities, often caused by conditions such as stroke or neurological disorders, severely limit an individual’s ability to perform essential daily tasks, leading to a significant reduction in quality of life. The development of effective rehabilitation technologies is crucial to restoring motor function and improving patient outcomes. This systematic review examines the application of machine learning and deep learning techniques in myoelectric-controlled systems for upper limb rehabilitation, focusing on the use of electroencephalography and electromyography signals. By integrating non-invasive signal acquisition methods with advanced computational models, the review highlights how these technologies can enhance the accuracy and efficiency of rehabilitation devices. A comprehensive search of literature published between January 2015 and July 2024 led to the selection of fourteen studies that met the inclusion criteria. These studies showcase various approaches in decoding motor intentions and controlling assistive devices, with models such as Long Short-Term Memory Networks, Support Vector Machines, and Convolutional Neural Networks showing notable improvements in control precision. However, challenges remain in terms of model robustness, computational complexity, and real-time applicability. This systematic review aims to provide researchers with a deeper understanding of the current advancements and challenges in this field, guiding future research efforts to overcome these barriers and facilitate the transition of these technologies from experimental settings to practical, real-world applications. Full article

Background and Objectives: This study aimed to determine the initial clinical characteristics of children diagnosed with intentional head trauma (IHT) to obtain information about the long-term developmental, psychological, and psychosocial status of these children, to detect delayed sequelae, and to find out information about their judicial processes. Materials and Methods: Fourteen children who were followed up with the diagnosis of IHT in the Ankara Child Protection Unit between 2010 and 2021 were included in the study. These cases were evaluated in terms of physical, developmental, psychological, and visual findings. A complete physical examination was performed on the patients and their anthropometric measurements were taken. Anterior and posterior segment evaluations and visual field examinations were conducted in the visual assessment. The Expanded Guide for Monitoring Child Development and Vineland Adaptive Behavior Scale Third Edition was used in the developmental assessment. A psychiatric evaluation was performed using the Ankara Developmental Screening Inventory, Crowell observation, Affective Disorders and Schizophrenia Form, and Wechsler Intelligence Scale for Children. Results: Of the patients diagnosed with IHT, 71.4% were male and the mean age was 8.39 ± 5.86 (1.27–22.30; IQR: 3.55–11.96) months. In the long-term follow-up, cerebral palsy was detected in three of the children, epilepsy in one, optic atrophy and deviation due to this in one, and deviation due to brain trauma in one. Motor delay was detected in 50.0% of the patients, language delay in 37.5%, cognitive delay in 37.5%, and attention deficit and hyperactivity disorder in 25%. It was observed that the people who caused the injuries of two patients were punished. Conclusions: Children diagnosed with IHT should be monitored with transdisciplinary methods in terms of physical and mental health throughout childhood, starting from the first intervention. Awareness of IHT diagnosis should be increased with training in social service approaches and judicial authorities providing services for child neglect and abuse. Full article

Motor impairments resulting from neurological disorders, such as strokes or spinal cord injuries, often impair hand and finger mobility, restricting a person’s ability to grasp and perform fine motor tasks. Brain plasticity refers to the inherent capability of the central nervous system to functionally and structurally reorganize itself in response to stimulation, which underpins rehabilitation from brain injuries or strokes. Linking voluntary cortical activity with corresponding motor execution has been identified as effective in promoting adaptive plasticity. This study introduces NeuroFlex, a motion-intent-controlled soft robotic glove for hand rehabilitation. NeuroFlex utilizes a transformer-based deep learning (DL) architecture to decode motion intent from motor imagery (MI) EEG data and translate it into control inputs for the assistive glove. The glove’s soft, lightweight, and flexible design enables users to perform rehabilitation exercises involving fist formation and grasping movements, aligning with natural hand functions for fine motor practices. The results show that the accuracy of decoding the intent of fingers making a fist from MI EEG can reach up to $85.3\%$, with an average AUC of 0.88. NeuroFlex demonstrates the feasibility of detecting and assisting the patient’s attempted movements using pure thinking through a non-intrusive brain–computer interface (BCI). This EEG-based soft glove aims to enhance the effectiveness and user experience of rehabilitation protocols, providing the possibility of extending therapeutic opportunities outside clinical settings. Full article

Autism spectrum disorder (ASD) has been intensely investigated since the term was first used over 80 years ago. The prevalence of ASD is constantly rising, and, currently, 1:36 children are diagnosed with this disorder. Despite the intense interest in ASD, the origins of this disorder remain obscure. This article explores motor issues and proprioceptive interoception difficulties as the prodrome of ASD. The importance of early intervention in the prognosis of ASD is common knowledge. Yet, since the communicational and social behaviors typical of ASD are observable only after the age of 18 months, diagnosis and early intervention are delayed. Therefore, the quest into the involvement of sensory–motor difficulties as a source of ASD traits, or at least as a potential early indicator, is warranted, with the intention of enabling early diagnosis and early intervention. This article examines the justification for this new avenue of early diagnosis and intervention and may open up a completely different way of viewing ASD. This new point of view may suggest an original path of assessment and intervention in infancy with this group of clients, possibly leading to improved prognosis for children and their families. Full article

Parkinson’s disease (PD) is a neurodegenerative disorder that affects people’s health. Constipation is probably one of the most prominent gastrointestinal symptoms (non-motor symptoms) of PD with devastating consequences. The aim of this research work is to formulate a functional food product, supplemented with inulin, cocoa, and Moringa, which can be an adjuvant in the treatment of constipation. The product was prepared according to a muffin or “Chilean cake” recipe; this basic muffin was prepared with additions of inulin (MI), inulin + cacao (MIC), and inulin + Moringa (MIM). A physical–chemical analysis of the macronutrients and an antioxidant capacity assessment of the samples were conducted, as well as a sensory evaluation performed by a group of people suffering from Parkinson’s disease. A statistically significant difference was observed in the soluble (p = 0.0023) and insoluble (p = 0.0015) fiber values between the control samples and all samples. Furthermore, inulin + cacao improved the antioxidant capacity and folate intake compared to the control. Inulin alone has been shown to have antioxidant capacity according to ABTS (262.5728 ± 34.74 μmol TE/g) and DPPH (9.092518 ± 10.43 μmol TE/g) assays. A sensory evaluation showed a preference for the product with inulin and for the product with inulin + cacao, with a 78% purchase intention being reported by the subjects who evaluated the products. The incorporation of inulin and cacao improved the nutritional value of the muffins; the dietary fiber, antioxidant capacity and folate content are some of the features that stood out. A bakery product enriched with inulin, cocoa and Moringa could serve as a nutritional strategy to enhance nutritional value, thus helping in the treatment of constipation. Full article

Mild cognitive impairment (MCI) is a relevant non-motor feature in Parkinson’s disease (PD). Social cognition (SC) is a cognitive domain that refers to the ability to decode others’ intentions and to guide behavior in social contexts. We aimed to compare SC performance in mid-stage PD patients compared to a healthy population and according to their cognitive state. Fifty-two PD patients were classified as being cognitively normal (PD-CN) or having mild cognitive impairment (PD-MCI) following the Movement Disorder Society (MDS) Level II criteria. SC assessment included facial emotion recognition (FER), affective and cognitive theory of mind (ToM), and self-monitoring (RSMS test). Twenty-seven age-matched healthy controls (HC) were enrolled. PD-MCI patients scored worse than HC on affective and cognitive ToM task scores. Only cognitive ToM scores were significantly lower when compared with the PD-MCI and PD-CN groups. We found no differences in FER or self-monitoring performance. There were significant correlations between cognitive ToM and executive functions, memory, language, and attention, whereas FER and affective ToM correlated with memory. Our findings indicates that SC is normal in cognitively unimpaired and non-depressed mid-stage PD patients, whereas a decline in affective and cognitive ToM is linked to the presence of MCI. Full article

Background: Vojta Therapy is a neurorehabilitation therapy that allows to activate reflex movement patterns. The scientific literature has shown its ability to generate muscle contractions. The activation of brain neural networks has also been proven. However, the relationship between these processes has not yet been demonstrated. For this reason, the aim of this study is to verify brain activation produced by recording with near-infrared spectroscopy and its relationship with muscle activation produced in the abdominal muscles recorded with surface electromyography. Methods: A total sample of 27 healthy subjects over 18 years of age was recruited. An experimental study on a cohort was conducted. Two experimental conditions were considered: stimuli according to the Vojta protocol, and a control non-stimuli condition. Abdominal muscle activation was measured using surface electromyography, and the activation of the motor cortex was assessed with near-infrared spectroscopy. Results: In relation to the oxygenated hemoglobin concentration (HbO), an interaction between the stimulation phase and group was observed. Specifically, the Vojta stimulation group exhibited an increase in concentration from the baseline phase to the first resting period in the right hemisphere, contralateral to the stimulation area. This rise coincided with an enhanced wavelet coherence between the HbO concentration and the electromyography (EMG) signal within a gamma frequency band (very low frequency) during the first resting period. Conclusions: The results underscore the neurophysiological effects on the brain following tactile stimulation via Vojta Therapy, highlighting increased activity in pivotal areas essential for sensory processing, motor planning, and control. This activation, particularly evident in the Vojta stimulation group, aligns with previous findings, suggesting that tactile stimuli can not only evoke the intention to move but can also initiate actual muscle contractions, emphasizing the therapy’s potential in enhancing innate locomotion and rolling movements in patients with neurological disorders. Full article

Biallelic variants in the Golgi SNAP receptor complex member 2 gene (GOSR2) have been reported in progressive myoclonus epilepsy with neurodegeneration. Typical clinical features include ataxia and areflexia during early childhood, followed by seizures, scoliosis, dysarthria, and myoclonus. Here, we report two novel patients from unrelated families with a GOSR2-related disorder and novel genetic and clinical findings. The first patient, a male compound heterozygous for the GOSR2 splice site variant c.336+1G>A and the novel c.364G>A,p.Glu122Lys missense variant showed global developmental delay and seizures at the age of 2 years, followed by myoclonus at the age of 8 years with partial response to clonazepam. The second patient, a female homozygous for the GOSR2 founder variant p.Gly144Trp, showed only mild fine motor developmental delay and generalized tonic–clonic seizures triggered by infections during adolescence, with seizure remission on levetiracetam. The associated movement disorder progressed atypically slowly during adolescence compared to its usual speed, from initial intention tremor and myoclonus to ataxia, hyporeflexia, dysmetria, and dystonia. These findings expand the genotype–phenotype spectrum of GOSR2-related disorders and suggest that GOSR2 should be included in the consideration of monogenetic causes of dystonia, global developmental delay, and seizures. Full article

Movement-based brain–computer Interfaces (BCI) rely significantly on the automatic identification of movement intent. They also allow patients with motor disorders to communicate with external devices. The extraction and selection of discriminative characteristics, which often boosts computer complexity, is one of the issues with automatically discovered movement intentions. This research introduces a novel method for automatically categorizing two-class and three-class movement-intention situations utilizing EEG data. In the suggested technique, the raw EEG input is applied directly to a convolutional neural network (CNN) without feature extraction or selection. According to previous research, this is a complex approach. Ten convolutional layers are included in the suggested network design, followed by two fully connected layers. The suggested approach could be employed in BCI applications due to its high accuracy. Full article

Although exclusive breastfeeding is recommended for the first 6 months of life, breastfeeding rates are low. Motor skills and ADHD-related characteristics have not yet been examined as breastfeeding barriers. The aim of this study was to explore whether mothers’ and infants’ motor skills, mothers’ ADHD-related characteristics and infants’ temperament are associated with exclusive breastfeeding at 6 months after birth. Participants were 164 mothers and their infants recruited 2 days after birth. Mothers completed a demographic and delivery information questionnaire, the Infant Feeding Intentions Scale and the Iowa Infant Feeding Attitude Scale. At 6 months, mothers completed the Adult DCD (developmental coordination disorder)/Dyspraxia Checklist, the Adult ADHD (attention deficit hyperactivity disorder) Self-Report Scale Symptom Checklist-v1.1, and the Infant Characteristics Questionnaire, and provided information about their breastfeeding status. They were then divided into two groups accordingly: EBF (exclusive breastfeeding) and NEBF (non-exclusive breastfeeding). Infants were observed using the Test of Sensory Functions in Infants and the Alberta Infant Motor Scale. At 6 months, NEBF mothers reported higher prevalence of DCD (10.2% vs. 1.9%, χ² = 5.561, p = 0.018) and ADHD (20.3% vs. 8.6%, χ² = 4.680, p = 0.030) compared to EBF mothers. EBF infants demonstrated better motor coordination (t = 2.47, p = 0.016, d = 0.511), but no temperament differences compared to NEBF infants. Maternal DCD, ADHD and poor infant motor coordination are associated with non-exclusive breastfeeding and may become exclusive breastfeeding barriers. These findings may assist in identifying women at risk of not exclusively breastfeeding and encourage tailoring interventions for achieving higher exclusive breastfeeding rates. Full article

Articulation disorders are deficiencies in the realization of speech sounds unrelated to organic or neurological disorders. Over the last decade, there has been a debate on the efficiency of non-verbal oro-motor exercises, which are orofacial movements programmed and organized in an intentional and coordinated way to control lips, tongue, and soft palate muscles. Of the 122 children evaluated, 52 presented articulatory difficulties. An intervention with nonverbal oro-motor exercises was applied, and children were again assessed following treatment. The results showed no differences between the experimental and control groups, either in the number of sounds that improved after this period or in the severity of difficulties (we categorized those with articulation difficulties in two to six sounds as ‘medium’ and those with difficulties in articulating more than seven sounds as ‘severe’). These results indicated that nonverbal oro-motor exercises alone are not efficient for intervention in difficulties in the realization of sounds in 4-year-old children. Full article

Recent engineering and neuroscience applications have led to the development of brain–computer interface (BCI) systems that improve the quality of life of people with motor disabilities. In the same area, a significant number of studies have been conducted in identifying or classifying upper-limb movement intentions. On the contrary, few works have been concerned with movement intention identification for lower limbs. Notwithstanding, lower-limb neurorehabilitation is a major topic in medical settings, as some people suffer from mobility problems in their lower limbs, such as those diagnosed with neurodegenerative disorders, such as multiple sclerosis, and people with hemiplegia or quadriplegia. Particularly, the conventional pattern recognition (PR) systems are one of the most suitable computational tools for electroencephalography (EEG) signal analysis as the explicit knowledge of the features involved in the PR process itself is crucial for both improving signal classification performance and providing more interpretability. In this regard, there is a real need for outline and comparative studies gathering benchmark and state-of-art PR techniques that allow for a deeper understanding thereof and a proper selection of a specific technique. This study conducted a topical overview of specialized papers covering lower-limb motor task identification through PR-based BCI/EEG signal analysis systems. To do so, we first established search terms and inclusion and exclusion criteria to find the most relevant papers on the subject. As a result, we identified the 22 most relevant papers. Next, we reviewed their experimental methodologies for recording EEG signals during the execution of lower limb tasks. In addition, we review the algorithms used in the preprocessing, feature extraction, and classification stages. Finally, we compared all the algorithms and determined which of them are the most suitable in terms of accuracy. Full article

People taken by upper limb disorders caused by neurological diseases suffer from grip weakening, which affects their quality of life. Researches on soft wearable robotics and advances in sensor technology emerge as promising alternatives to develop assistive and rehabilitative technologies. However, current systems rely on surface electromyography and complex machine learning classifiers to retrieve the user intentions. In addition, the grasp assistance through electromechanical or fluidic actuators is passive and does not contribute to the rehabilitation of upper-limb muscles. Therefore, this paper presents a robotic glove integrated with a force myography sensor. The glove-like orthosis features tendon-driven actuation through servo motors, working as an assistive device for people with hand disabilities. The detection of user intentions employs an optical fiber force myography sensor, simplifying the operation beyond the usual electromyography approach. Moreover, the proposed system applies functional electrical stimulation to activate the grasp collaboratively with the tendon mechanism, providing motion support and assisting rehabilitation. Full article

GNAO1 gene mutations are associated with a neurodevelopmental disorder characterized by developmental delay, epilepsy, and movement disorder. Eye tracking and eye movement analysis are an intriguing method to assess cognitive and language function and, to the best of our knowledge, it has never been tested in a standardized way in GNAO1. GNAO1 children are usually wheelchair-bound and with numerous motor constrains, including dystonic movements and postures, heterotropia, and hypotonia, making the cognitive assessment arduous. These contribute to the burden and disability, with a high level of frustration of caregivers and patients. We have herein demonstrated that, through an eye tracking system, six GNAO1 patients evaluated showed variable degrees of communicative intent through intentionally directed gaze. Moreover, three of these were able to complete a cognitive evaluation, and showed normal fluid intelligence and lexical comprehension. In conclusion, in GNAO1-related disorders, the degree of cognitive development is underestimated; eye tracking technologies may help in overcome these boundaries. Full article