Search Results (90)

Background/Objectives: Disorders of consciousness (DOC), including vegetative state/unresponsive wakefulness syndrome (VS/UWS) and minimally conscious state (MCS), present significant diagnostic challenges. Misdiagnosis rates approach 40%, often due to limitations in detecting subtle behavioural responses through clinical observation alone. Eye-tracking technology offers objective, quantitative assessment of visual behaviours that may reveal covert signs of consciousness. This systematic review aimed to evaluate the diagnostic accuracy of eye-tracking technology compared to the Coma Recovery Scale-Revised (CRS-R) for detecting visual responses and consciousness signs in patients with DOC; to examine stimulus effects; and to assess prognostic value. Methods: A systematic literature search was conducted across SciSpace, Google Scholar, PubMed, and institutional libraries following PRISMA 2020 guidelines. Eligibility criteria specified studies involving patients with prolonged DOC assessed using eye-tracking technology. Data extraction, risk of bias assessment, and GRADE certainty evaluation were conducted systematically. Results: Fifteen studies (n = 4–123 patients; published 2012–2025) were included. Eye-tracking detected visual responses in significantly more patients than clinical observation alone (46.2% vs. 18.1% in one study). Mirror stimuli demonstrated the highest detection sensitivity (97% vs. 69% for person and 57% for object). Affectively salient stimuli elicited stronger tracking responses in patients with MCS (37.3% vs. 29.9–30.6% neutral). Advanced VR-based systems achieved high diagnostic accuracy (sensitivity 100%, specificity 88.9%) with prognostic value (overt tracking predicting 62.5% command-following at one year). GRADE certainty was Low for detection rates and diagnostic discrimination, and Very Low for sensitivity, specificity, and prognostic outcomes. Conclusions: Eye-tracking provides objective, sensitive assessment of visual behaviours in patients with DOC and may reduce misdiagnosis rates, supporting a conditional recommendation for its use as a supplementary assessment tool alongside CRS-R. Methodological heterogeneity, small sample sizes, and absence of blinding limit certainty. Adequately powered, multicentre prospective studies are urgently needed. Full article

Could there be quantum superpositions of conscious states, as suggested by the Wigner’s friend thought experiment? Mathematical theories of consciousness, notably integrated information theory (IIT), make this question more precise by associating physical systems with both quantitative amounts of consciousness and structural characterizations of conscious states. Motivated by a recent proposal that ties wave-function collapse to integrated information, we construct a simple quantum circuit that would, on that proposal, place a minimal system—a feedback dyad—into a superposition of states that differ in their associated conscious states. This “Schrödinger’s dyad” provides a controlled setting for evaluating a central desideratum of consciousness-based collapse models: that collapse rates depend on how different the experiences in the superposition are. We prove a structural constraint on collapse dynamics of a standard (Lindblad) type: if collapse is governed by too few collapse operators, collapse rates cannot in general be made to depend solely on qualitative differences between conscious states. Avoiding this limitation requires introducing many commuting operators, leading to a rapid proliferation of collapse terms even for very simple systems. This proliferation bears directly on claims that IIT-based collapse theories may be especially experimentally tractable, since the required dynamics becomes highly complex. More generally, the difficulty is not specific to IIT: any Wigner-style collapse theory that distinguishes experiences using rich internal organization (such as neural connectivity in addition to neural state) will face a comparable explosion in dynamical complexity. Full article

Background and Clinical Significance: Deep thalamic and periventricular lesions are uncommon in adults but can result in significant loss of function because of their convergence on three interdependent processes: thalamocortical state regulation, throughput of periventricular long association systems, and ventricular compartmental compliance. The resulting combination of executive control collapse, retrieval-weighted language fragility, and load-sensitive gait instability may occur early after a lesion forms an atrial/posterior horn interface, and pressure-linked autonomic symptoms may be late to develop. Screening deficits will likely be minimal and therefore underreported. Objective/Aim: To present a thalamic–atrial/posterior horn tumor case with quantified load-sensitive cognitive–language–gait dysfunction and to detail a physiology-guided, sequence-driven decompression approach emphasizing ventricular relaxation and perforator-preserving, interface-limited thalamic resection. Case Presentation: A 56-year-old female patient experienced a 3-month, rapidly progressive decline in her cognitive and language abilities. The clinical progression was not stepwise or punctuated by a single “sentinel” event. She had a moderate level of cognitive impairment consistent with both Broca’s and Wernicke’s aphasias (MoCA: 22/30) and suffered from significant interference effects and increased cost of task-switching. Her ability to generate novel responses and name objects was significantly impaired; however, she was able to repeat words and phrases appropriately. In addition, she exhibited a severe sustained attention signature and a high error rate during dual-task performance, indicating severe gait instability, although her overall global anchors were nearly neutral (GCS 15; FOUR 15/16; NIHSS 2). Nausea and vomiting occurred simultaneously with the cognitive and language decline, suggesting decreased intracranial compliance. MRI revealed a heterogeneous left-sided thalamic tumor extending into the posterior horn of the lateral ventricle. The tumor caused deformation of the lateral ventricle and midline displacement. The patient underwent microsurgical intervention using a physiology-conscious sequence of graded cerebrospinal fluid (CSF) equilibration and primary mechanical removal of the tumor from the ventricular system. Additionally, decompression of the thalamus was performed in a manner that was cognizant of the boundaries formed by the perforating arteries of the thalamus. Early resolution of pressure symptoms was noted postoperatively. Objective measures demonstrated significant improvement in the patient’s executive functioning, language skills, attentional errors, and dual-task performance stability. The patient remained functionally independent at discharge and at subsequent follow-up visits. Surveillance imaging did not demonstrate any evidence of tumor recurrence. Conclusions: The clinical presentation described above is supportive of a model in which the synergy between deep network damage and distortion of the posterior ventricular compartment amplifies network dysfunction. Additionally, the use of quantitative stress-phenotyping makes it possible to identify deep network pathology early in its course. Finally, the physiology-guided decompression approach that was used in this case has the potential to increase functional reserve in patients with pathology that requires millimeter transitions. Full article

Background/Objectives: This study investigates the effects of multi-sensory stimulation on brain functional connectivity in patients with disorders of consciousness (DOC). DOC patients experience prolonged loss of consciousness due to brain injury, posing significant challenges for rehabilitation. Methods: In the study, visual, olfactory, and visual–olfactory (V-O) combined stimulation were applied to DOC patients while their EEG signals were recorded. A brain functional network was constructed based on the conditional Granger causality (CGC) method to analyze its topological characteristics. Results: The results revealed that the strength of brain functional connectivity in Minimally Conscious State (MCS) patients was significantly higher than that in Vegetative State (VS) patients, indicating a strong correlation between the intensity of synergistic activity in brain functional connectivity and the level of consciousness. Furthermore, V-O combined stimulation significantly enhanced brain functional connectivity compared to single-modality stimulation. The selection of different stimulation also differentially affected brain functional connectivity, with olfactory stimulation exhibiting high pleasure, arousal, and dominance (Self-Assessment Manikin) values demonstrating unique advantages in reducing individual variability and improving global efficiency. Conclusions: The study provides a theoretical foundation for the application of multi-sensory stimulation in the rehabilitation of DOC patients. V-O stimulation not only enhances information transmission in brain regions corresponding to visual and olfactory processing under single-modality stimulation but also increases the intensity of information transfer to other brain regions; this may serve as a reference for understanding the effects of multi-sensory stimulation on brain networks. Full article

Background: The clinical assessment of Disorders of Consciousness (DOC) has long been constrained by the subjectivity of behavioral scales and the low-temporal resolution of neuroimaging techniques. There is an urgent need for objective, high-temporal-resolution biomarkers to improve the accuracy of DOC severity evaluation and sub-state differentiation. This study aims to develop a resting-state/task-state dual-modality EEG microstate analysis method. By integrating a multisensory stimulation paradigm with a resting-state global template, we seek to verify the validity and clinical utility of this method in quantitatively assessing the severity of DOC sub-states, namely Minimally Conscious State-positive (MCS+), Minimally Conscious State-negative (MCS−), and Vegetative State (VS). Methods: A total of 27 subjects were enrolled, including 9 healthy controls (HC), 6 MCS+ patients, 6 MCS− patients, and 6 VS patients. A multisensory stimulation paradigm (visual, olfactory, and combined visual–olfactory) was applied, and EEG microstates were extracted using a revised K-means clustering algorithm. Key microstate parameters (duration, global field power, and coverage) were quantified for systematic analysis. Results: During the resting state, the HC group exhibited a significantly posterior parietal-dominant distribution of Microstate D, while this parameter showed a gradient attenuation pattern corresponding to the severity of consciousness impairment in the DOC group (p < 0.05). During the task state, the HC group showed a significant multisensory effect under combined visual–olfactory stimulation; within the DOC group, MCS+ patients demonstrated stronger task-related responses compared to MCS− and VS patients. Conclusions: The gradient attenuation of resting-state Microstate D parameters reflects the severity of DOC, and task-specific responses to multisensory stimulation serve as a potential biomarker for distinguishing MCS+ patients. This dual-modality EEG microstate analysis method provides an objective, high-temporal-resolution basis for the precise clinical evaluation of neurological function in DOC patients. Full article

(1) Patients in a minimally conscious state (MCS) and their families face prolonged emotional distress and psychological challenges due to the uncertainty of recovery and limited means of emotional communication. This study aims to develop an EEG-based emotion visualization system to support affected families by translating patients’ neural activity into perceivable emotional imagery. (2) Using simulated MCS patient EEG data corresponding to different emotional states, we designed a dynamic visual interface via TouchDesigner to convert bio-signals into real-time emotional animations. User tests involving questionnaires and interviews were conducted to evaluate the system’s performance. (3) The results demonstrate that the system accurately conveys emotional states, enhances caregivers’ perception of patients’ internal conditions, and significantly alleviates family members’ anxiety. (4) These findings suggest that EEG-based emotion visualization offers a viable and compassionate tool for supporting MCS families, providing new pathways for interdisciplinary research combining neuroscience and design while establishing a foundation for future clinical and home-care applications. Full article

We here delve into the intricate and evolving concepts of brain death and consciousness, particularly at the end of life. We examine the historical and technological advancements that have influenced our understanding of death, such as mechanical ventilation and resuscitation techniques. These developments have challenged traditional definitions of death, leading to the concept of brain death, defined as the irreversible loss of all brain functions, including the brainstem. We emphasize that consciousness exists on a continuum, ranging from full alertness to deep coma and complete cessation of brain activity. It explores various disorders of consciousness, including coma, vegetative state, minimally conscious state, and locked-in syndrome, each with distinct characteristics and levels of awareness. Neuroimaging techniques, such as EEG, fMRI, and DTI, are highlighted for their crucial role in diagnosing and understanding disorders of consciousness. These techniques help to detect covert consciousness, assess brain activity, and predict recovery potential. The phenomenon of the “wave of death,” which includes a paradoxical surge in brain activity at the point of death, is also discussed. We address the challenges in defining and understanding both death and consciousness, calling for biologically grounded, ethically defensible, and culturally sensitive definitions. We advocate for standardized neuroimaging protocols, longitudinal studies, and the integration of artificial intelligence to improve diagnosis and treatment. In conclusion, the document underscores the importance of an integrated, evidence-based approach to understanding the gray zones between life and death, recognizing that consciousness and death are dynamic processes with both biological and experiential dimensions. Full article

Background/Objectives: The Lowenstein Communication Scale (LCS) is a tool for the evaluation of communicative performance in patients with disorders of consciousness (DOC). This study investigated the reliability and validity of the LCS. Methods: We evaluated 23 inpatients with unresponsive wakefulness syndrome (UWS) and 18 in a minimally conscious state (MCS), at admission to a Consciousness Rehabilitation Department and one month later. The evaluations included assessments of LCS by two raters, and of the Coma Recovery Scale–Revised (CRS-R) by one rater. Results: Total inter-rater agreement in LCS task scoring was found in 58–100% of the patients. Cohen’s kappa values were >0.6 for most tasks. High correlations were found between the two raters on total scores and most subscales (r = 0.599–1.000, p < 0.001), and the differences between them were small. LCS subscales and total score intraclass correlations (ICC) were high. Internal consistency was acceptable (Cronbach’s α > 0.7) for most LCS subscales and total scores. Moderate to strong correlations were found between LCS and CRS-R scores (r = 0.554–0.949, p < 0.05), and the difference in responsiveness between LCS and CRS-R was non-significant. Conclusions: The findings indicate that the LCS is reliable and valid, making it a valuable clinical and research assessment tool for patients with DOC. Full article

This paper presents a hybrid fast charging strategy for static wireless power transfer (WPT) systems that synergistically combines pulsed current and multi-stage current (MCM) modes to enable rapid yet battery-health-conscious electric vehicle (EV) charging, thereby promoting sustainable transportation. The proposed approach employs a memetic algorithm (MA) to dynamically optimize the charging parameters, achieving an optimal balance between speed and battery longevity while maintaining 90.78% system efficiency at the SAE J2954-standard 85 kHz operating frequency. A neural-network-based state of charge (SOC) estimator provides accurate real-time monitoring, complemented by MA-tuned PI control for enhanced resonance stability and adaptive pulsed current–MCM profiles for the optimal energy transfer. Simulations and experimental validation demonstrate faster charging compared to that using the conventional constant current–constant voltage (CC-CV) methods while effectively preserving the battery’s state of health (SOH)—a critical advantage that reduces the environmental impact of frequent battery replacements and minimizes the carbon footprint associated with raw material extraction and battery manufacturing. By addressing both the technical challenges of high-power WPT systems and the ecological imperative of battery preservation, this research bridges the gap between fast charging requirements and sustainable EV adoption, offering a practical solution that aligns with global decarbonization goals through optimized resource utilization and an extended battery service life. Full article

Background/Objectives: The aim of this study was to evaluate the impact of chronic heart failure (CHF), chronic kidney dysfunction (CKD), and the combined CHF-CKD comorbidity on the outcomes of rehabilitation in stroke patients. Methods: A total of 586 patients who had suffered a stroke (mean age, 70 ± 13; 47.6% female; 72.4% ischemic and 27.6% hemorrhagic strokes) and who were admitted immediately after acute stroke care to a rehabilitation center were included in this cohort study and followed up with until their death or discharge from the rehabilitation center. The clinical characteristics of the patients were obtained from their medical records. The relationship between the background comorbidities (CHF, CKD, and concurrent CHF-CKD) and fatal and non-fatal unfavorable outcomes (emergency readmission to a primary hospital or transfer to a long-term care facility in a vegetative or minimally conscious state) were investigated. Results: Unfavorable outcomes were more common in the groups with background CHF and/or CKD. From the Cox multivariate analysis, both CHF and CKD were independent prognostic factors for the occurrence of unfavorable outcomes, with a hazard ratio (HR) of 2.28 (95% CI = 1.2–4.29; p-value = 0.01) and 2.19 (95% CI = 1.24–3.87; p-value = 0.007), respectively. Moreover, the combined CHF-CKD comorbidity showed a more than 5-fold increased risk of an adverse post-stroke outcome (HR of 5.8; 95% CI = 2.5–13.44; p-value < 0.001). Conclusions: The combined CHF-CKD comorbidity is an important independent complicating factor that, along with other known influencing factors, can affect unfavorable post-stroke outcomes more than CHF or CKD alone, and necessitates critical attention to its diagnosis and management as a separate mixed syndrome. Full article

Background/Objectives: Accurate and efficient segmentation of cell nuclei in biomedical images is critical for a wide range of clinical and research applications, including cancer diagnostics, histopathological analysis, and therapeutic monitoring. Although U-Net and its variants have achieved notable success in medical image segmentation, challenges persist in balancing segmentation accuracy with computational efficiency, especially when dealing with large-scale datasets and resource-limited clinical settings. This study aims to develop a lightweight and scalable U-Net-based architecture that enhances segmentation performance while substantially reducing computational overhead. Methods: We propose a novel evolving U-Net architecture that integrates multi-scale feature extraction, depthwise separable convolutions, residual connections, and attention mechanisms to improve segmentation robustness across diverse imaging conditions. Additionally, we incorporate channel reduction and expansion strategies inspired by ShuffleNet to minimize model parameters without sacrificing precision. The model performance was extensively validated using the 2018 Data Science Bowl dataset. Results: Experimental evaluation demonstrates that the proposed model achieves a Dice Similarity Coefficient (DSC) of 0.95 and an accuracy of 0.94, surpassing state-of-the-art benchmarks. The model effectively delineates complex and overlapping nuclei structures with high fidelity, while maintaining computational efficiency suitable for real-time applications. Conclusions: The proposed lightweight U-Net variant offers a scalable and adaptable solution for biomedical image segmentation tasks. Its strong performance in both accuracy and efficiency highlights its potential for deployment in clinical diagnostics and large-scale biological research, paving the way for real-time and resource-conscious imaging solutions. Full article

Objectives: Prolonged disorders of consciousness (DoC) present complex diagnostic and therapeutic challenges. This study aimed to evaluate the accuracy of two ChatGPT models (ChatGPT 4o and ChatGPT o1) in answering questions about prolonged DoC, framed as if they were posed by a patient’s relative. Secondary objectives included comparing performance across languages (English vs. Italian) and assessing whether responses conveyed an empathetic tone. Methods: Fifty-seven open-ended questions reflecting common caregiver concerns were generated in both English and Italian, each categorized into one of three domains: clinical data, instrumental diagnostics, or therapy. Each question contained a background context followed by a specific query and was submitted once to both models. Two reviewers evaluated the responses on a four-point scale, ranging from “incorrect and potentially misleading” to “correct and complete”. Discrepancies were resolved by a third reviewer. Accuracy, language differences, empathy, and recommendation to consult a healthcare professional were analyzed using absolute frequencies, percentages, the Mann–Whitney U test, and Chi-squared tests. Results: A total of 228 responses were analyzed. Both models provided predominantly correct answers (80.7–96.8%), with English responses achieving higher accuracy only for ChatGPT 4o on clinical data. ChatGPT 4o exhibited greater empathy in its responses, whereas ChatGPT o1 more frequently recommended consulting a healthcare professional in Italian. Conclusions: Both ChatGPT models demonstrated high accuracy in addressing prolonged DoC queries, highlighting their potential usefulness for caregiver support. However, occasional inaccuracies emphasize the importance of verifying chatbot-generated information with professional medical advice. Full article

Energy resources, particularly oil and natural gas, are vital for global development but have significant environmental impacts, including pollution and habitat destruction. Green management has become a critical concept in today’s global industries, mostly the petroleum industry. The petroleum industry is vital not only for the world but also for Türkiye’s energy needs and economic development. However, its operations significantly impact the environment through greenhouse gas emissions, water pollution, and habitat destruction. In response to both global and national environmental concerns and regulatory pressures, the Turkish petroleum industry should adopt green management practices. Despite the lack of prior studies regarding green management approaches and practices in Turkish petroleum industry, this study examines how Türkiye’s petroleum industry should integrate green management principles to minimize environmental impacts and promote sustainable development. To evaluate the environmental protection approaches and practices of petroleum enterprises based on their operational domains, a survey was conducted, and the collected data underwent statistical analysis. The survey questions were designed by the authors to determine the attitudes, approaches, and practices of managers in crude oil production and refining companies regarding green management. According to the results of the statistical data analysis, it has been determined that companies in the Turkish petroleum industry have adopted an approach known as green management or environmentally conscious entrepreneurship. The statistical analysis of the administered survey results indicates a positive relationship between firms’ operational performance scores and their green management practices scores (r = 0.247). The survey results demonstrate an increasing adoption of environmental consciousness and green management practices among managers in the Turkish petroleum sector, with 90.2% of participants providing a positive response. The survey results also indicate that green management practices have a positive impact on business operations. In this regard, 42.4% of participating managers believe that green management practices enhance corporate image, 38.0% state that they improve efficiency, 35.0% assert that they strengthen competitive advantage, and 31.5% indicate that they contribute positively to energy savings. The survey findings further indicate that 90.2% of participants recognize the contribution of green management practices to sustainable development in businesses, while an equal proportion asserts that these practices enhance clean and safe production. Moreover, 93.5% of respondents emphasize that production and processing activities carried out without environmental considerations pose a significant threat to the future of both the planet and humanity. In conclusion, based on the responses provided by the participants, it can be inferred that business managers have adopted the green management approach and recognize the significant role of green management practices in addressing environmental challenges. In line with the objectives of this study and the statistical findings obtained, a “green management model” has been proposed for enterprises in the Turkish petroleum industry, taking into consideration global practices and aligning with the principles of environmentally responsible green entrepreneurship. In this context, the study makes a significant contribution to the literature by proposing a green management model for the Turkish petroleum industry. Full article

Background: Disorders of Consciousness (DoC) following acute brain injuries, such as intracerebral hemorrhage, present significant clinical challenges in intensive care and rehabilitation settings. Early multidisciplinary interventions, including physiatric care, are critical in optimizing recovery trajectories. However, evidence regarding the timing and intensity of rehabilitation interventions remains limited. This case report highlights the role of physiatrists in managing a critically ill patient with a DoC in an Intensive Care Unit (ICU), focusing on early rehabilitation strategies and individualized care planning. Case presentation: A 63-year-old male with a history of hypertension and cardiac disease presented with a left hemispheric hemorrhage and quadriventricular intraventricular hemorrhage. The patient was admitted to the ICU in a comatose state (Glasgow Coma Scale [GCS] 5). Initial physiatric evaluation revealed a critical condition precluding immediate initiation of an Individual Rehabilitation Project (IRP). Over subsequent weeks, clinical improvements were observed, including an increased GCS and Coma Recovery Scale-Revised (CRS-R) score. A tailored IRP was implemented, emphasizing passive mobilization to prevent complications such as muscle atrophy, joint contractures, and pressure ulcers. The patient demonstrated gradual progress, transitioning to a Minimally Conscious State (MCS) and achieving improved joint mobility and reduced peripheral edema. Discussion and Conclusions: This case underscores the pivotal role of physiatrists in ICU settings, particularly for patients with DoC. Early physiatric interventions, even in critically ill patients, can prevent secondary complications and facilitate functional recovery. Close collaboration with ICU teams and infectious disease specialists ensured the safe implementation of rehabilitation strategies despite the patient’s severe condition. The observed clinical improvements highlight the potential benefits of early mobilization and individualized care plans, both in terms of survival (quoad vitam) and quality of life (quoad valetudinem). This report emphasizes the need for further research to refine rehabilitation practices for patients with DoC, bridging gaps between acute care and neurorehabilitation. Full article

Touch, particularly affective touch mediated by C-tactile fibers, plays a key role in emotional regulation and therapeutic interventions. However, tactile stimulation is underutilized in sensory stimulation (SS) protocols for brain injury patients, despite its potential to enhance consciousness and promote recovery through neural and autonomic regulation. Tools like the Neurowave enable advanced multisensory stimulation, including audio-visual and emotional inputs, but lack tactile components. Integrating gentle touch stimulation with such systems could further enhance neuroplasticity, improve heart rate regulation, and support recovery in patients with disorders of consciousness. In this study, twenty patients affected by minimally conscious state (MCS) were divided into two groups: an experimental group (EG n.10) and a control group (CG n.10). Both groups underwent standard neurorehabilitation, including conventional physiotherapy and speech therapy. The key difference was in the type of sensory stimulation. The EG received advanced sensory stimulation with the Neurowave system (which provides audio-visual and emotional sensory stimulation) in addition to gentle touch stimulation. The CG received conventional sensory stimulation without the Neurowave and neutral gentle touch stimulation. Each patient was evaluated by a multidisciplinary rehabilitation team, using clinical scales such as coma recovery scale—revised (CSR-R), level of cognitive functioning (LCF), before (T0) and after (T1) treatment. Additionally, heart rate (HR) and neurophysiological outcomes (P300) were also recorded for both groups (EG and CG). The MANOVA model revealed a significant interaction effect between group and phase on P300 latency (F (1, 18) = 10.23, p < 0.001, η² = 0.09), indicating that the intervention involving gentle touch stimulation significantly influenced the P300 latency in the EG. The findings of this study contribute to our understanding of the therapeutic potential of emotional multisensory stimulation, which also includes gentle touch stimulation, in MCS rehabilitation. By demonstrating significant effects on both neurophysiological and functional measures, our results support the integration of tactile interventions into comprehensive neurorehabilitation programs. Full article