Search Results (144)

Competitive eSports impose substantial cognitive workload, yet performance evaluation still emphasizes post-match statistics without considering players’ cognitive states. We reviewed 30 papers that recorded physiological signals using sensors and utilized machine learning (ML) for predicting cognitive states and/or game performance. Findings showed that cardiovascular monitoring (heart rate variability/HRV) was the most prevalent modality (20/30 studies), followed by oculometry (10), electrodermal activity/EDA (9), and electroencephalogram/EEG (5); however, no standardized protocols (device/pre-processing/feature subset) were observed across HRV studies despite it being the most common measure. The best outcomes per construct (measure, accuracy) were: mental workload (pupillometry, ~82%), stress/arousal (EDA, p < 0.001), cognitive fatigue (pupil diameter/EEG, ~88%), expertise (EEG, ~92%), and tilt (EDA/HRV/eye-tracking, ~82–87%). Notably, current studies used small samples and were gender-imbalanced, while ML studies often lacked cross-validation. Only 2 of 30 studies examined flow state—a mental state of optimal performance characterized by total immersion and effortless execution—and interestingly, HRV showed decreases during stress/workload but increases during flow, suggesting context-dependent autonomic regulation. To address this gap, a new framework for flow detection is presented. This review will be of interest to game developers, eSports players, and coaches, and the reported findings may help towards improving player experience and game performance. Full article

Environmental noise may interfere with the reading experience by increasing cognitive load and psychophysiological arousal, yet these effects are difficult to perceive and communicate in real time. This study presents Reading Noise, an interactive installation that combines physiological sensing and sound-driven visualization to externalize perceived noise-related disturbance and psychophysiological strain during reading. In a controlled experiment, 46 participants completed reading tasks under four levels of background conversational noise (0–30, 31–60, 61–90, and >90 dB) while ambient sound level, electrodermal activity (EDA), and electrocardiogram (ECG) were recorded in real time. Following data quality screening, inferential statistical analyses were performed on the analyzable physiological subset (n = 16). Based on these data, a hybrid mapping strategy combining rule-based assignment and LMM-informed exploratory calibration was developed to map acoustic and physiological changes onto dynamic text-based visual parameters, including deformation intensity, jitter, and motion instability, for real-time feedback. Within the analyzable subset, noise level was associated with significant changes in the recorded physiological indicators (all p < 0.05): skin conductance level (SCL) and skin conductance responses per minute (SCRs/min) increased (4.69 ± 2.13 to 5.93 ± 2.19 μS; 1.49 ± 1.59 to 2.51 ± 2.13), whereas the percentage of successive RR intervals differing by more than 50 ms (pNN50) and the root mean square of successive differences (RMSSD) decreased (15.84 ± 16.52% to 10.57 ± 11.35%; 36.63 ± 17.62 to 29.67 ± 16.66 ms). Subjective cognitive load also increased significantly (2.06 ± 0.29 to 6.38 ± 0.31). A follow-up installation study with 24 cross-disciplinary participants, with reported group interaction observations drawn from a 12-participant subset, suggested that the installation may facilitate shared interpretation of attention-related disruption and cognitive strain, indicating the potential of physiology-informed visual translation as a boundary object approach for empathetic, sound-mediated communication. Full article

After neurological injury, individuals often undergo physical therapy to regain motor function, which can be supplemented with use of virtual reality (VR). Rehabilitation commonly employs methods that encourage movement variability to promote functional gains, such as perturbations. Rehabilitation also commonly integrates additional sensory modalities for guidance and cognitive engagement to the protocol. In this exploratory, proof-of-concept study, neurotypical participants were trained on a custom tracing task with targeted dynamic shifting to induce movement variability, under both expected (proactive) and unexpected (reactive) conditions, with and without added auditory feedback. Participants significantly (p < 0.05) improved performance (tracing accuracy) after training with audio feedback. Participants trained without audio feedback showed decreased electrodermal activity (EDA), a measure of physiological engagement. Audio feedback during reach training with complex objectives (e.g., dynamic shifting) can promote performance improvements and cognitive engagement. Full article

In this study, a multicomponent composite film system based on alginate, chitosan, κ-carrageenan, agar, and Rapana venosa protein hydrolysate (RVPH) was developed, and the effect of RVPH incorporation (0–1.5%) on molecular interactions, microstructure, and functional performance was evaluated using FTIR, SEM, mechanical testing, optical analysis, and water-related measurements. FTIR results indicated that RVPH interacted with the polysaccharide matrix mainly through hydrogen bonding and ionic interactions without causing chemical degradation. SEM analysis revealed concentration-dependent microstructural changes, with smoother morphologies at low RVPH levels and increased roughness and heterogeneity at higher concentrations. These structural differences were reflected in the functional properties. All films exhibited high swelling and water solubility. Optical properties were significantly affected by RVPH. Mechanical properties exhibited a non-linear response, with numerical variations observed but no statistically significant differences (p > 0.05). The EDAS and SWARA methods were employed to determine the optimal incorporation level of RVPH in the film formulations. Among the RVPH-containing films, the formulation incorporating 1% RVPH was identified as the most suitable alternative. Full article

This paper proposes a corner analysis approach for CMOS circuits taking into the account radiation effects. The presented simulation approach is implemented using the open-source design automation (EDA) software QUCS-S 25.2.0 and Ngspice 45. It was developed a radiation-sensitive field-effect transistor (RADFET) SPICE macromodel representing threshold voltage shift versus radiation dose. The extraction procedure for this model is based on statistical measurements of pMOS transistors and process corner models (Slow, Typical, Fast) and involves percentile analysis. The article proposes an original design of the RADFET-based radiation sensor with RADFET device and CMOS readout circuit placed on the same die, which allows us to simplify the dosimeter schematic. The sensor output parameter dependency on process parameters, supply voltage, and temperature was investigated using the proposed simulation approach. Full article

Background: Pain remains one of the most debilitating and prevalent symptoms in cancer patients. However, assessment based solely on subjective self-report tools is limited by cognitive impairment and the heterogeneous nature of cancer pain. Since evidence on the ability of physiological biosignals to discriminate cancer pain intensity and pain phenotypes in real clinical settings remains limited, this study explored the potential of biosignals to discriminate between pain intensity and pain type. Methods: Electrodermal activity (EDA) and electrocardiogram (ECG) signals were recorded in cancer patients using the BITalino (r)evolution board (sampling frequency 1000 Hz). EDA was processed to extract skin conductance responses (SCRs) using continuous decomposition analysis (CDA) and trough-to-peak (TTP) methods. Heart rate variability (HRV) features were extracted in both time and frequency domains, including low frequency (LF), high frequency (HF), and the LF/HF ratio. Non-parametric Kruskal–Wallis tests were performed to compare biosignal parameters across pain intensity (Numeric Rating Scale, NRS: low 1–3; medium 4–6; and high 7–10) and pain types (nociceptive, neuropathic, mixed, and breakthrough cancer pain—BTCP). Results: Data from 61 patients were analyzed. For EDA, the maximum skin conductance response amplitude (MaxCDA) significantly differed across intensity groups (p = 0.037). Post hoc analysis showed a significant difference between the low- and high-intensity groups (p = 0.015), with the low-intensity group exhibiting a higher mean MaxCDA (0.063 µS) than the high-intensity group (0.024 µS). Several EDA parameters were significantly associated with pain type. The number of SCRs (TTP) (p = 0.015) and maximum SCR amplitude (TTP) (p = 0.040) were significantly lower in the mixed pain group compared with the nociceptive and neuropathic groups. No HRV parameters showed significant associations with pain intensity or pain type. BTCP did not significantly affect any biosignal parameters. Subgroup analyses showed that EDA features discriminating mixed pain were preserved in patients without bone metastases, BTCP, or high opioid burden, whereas no clinical variable modified the association between biosignals and pain intensity and type. Conclusions: In this investigation, selected EDA parameters were associated with cancer pain intensity and pain type, whereas heart rate variability measures did not show significant discrimination under the present methodological conditions. These findings suggest that EDA may provide complementary information on pain-related autonomic alterations in oncology patients. However, biosignals should not be considered standalone indicators of pain, and their interpretation requires integration with clinical variables and pharmacological context. Further studies adopting multimodal and longitudinal approaches are needed to clarify their role in automatic pain assessment in cancer care. Full article

Traditional interoception research investigates cardioception, respiroception, or gastroception as a proxy for the sense of the body as a whole. These single-organ tasks sacrifice construct and ecological validity for a content validity that has been elusive. We propose that interoception is better captured by one’s sense of their own autonomic nervous system, or ANSception. The ANS integrates multimodal signals via lesser-myelinated neurons, making it an integral part of the interoceptive nervous system. Thirty-four participants moved a slider to reflect their perceived sympathetic activation (ANSception) while their physiology was monitored. Most participants reported integrating information from two or more organ systems during ANSception. The relationship between ANSception and physiology showed unique but often robust responses by condition and physiological measure. For example, one participant had a negative-to-positive-to-negative pattern for ANSception-EDA correlations from baseline to stimulus to recovery (r = −0.677; 0.657; −0.507, p < 0.001). Another participant had a strong positive correlation between their ANSception and blood pressure (r = 0.601, p < 0.001) during a five-minute reportedly meditative state. We propose that the role of interoception is to scan, integrate and manage information across organ systems, and we conclude that ANSception better captures this role than traditional single-organ tasks. Full article

Background: this paper reports an investigation into the cognitive and emotional states of adolescents while learning from an LLM. It seeks to address a relative dearth in empirical evidence which might otherwise facilitate informed decisions being made by curriculum designers, school leaders and policy makers regarding the use of Generative AI, amidst the wider discourse about the effectiveness of AI in teaching and learning. Methods: in this paper, we analyze electrodermal activity (EDA) in the context of students’ scholastic engagement using LLMs in comparison to curated texts. In our 27-min-long experiment, we recorded the EDA of participants learning from both learning methods, for 8 min each. A quiz was also conducted to assess the effectiveness of the learning method. We collected 23 samples of EDA from the experiment, and 42 samples of quiz results. Results: we have found that learning with an LLM results in greater Skin Conductance Response (p = 0.09404), which is linked to more positive emotional valence, and lower Skin Conductance Level (p = 0.09473), which is linked to lower cognitive load, compared to curated texts. We also discovered that learning with an LLM correlates to a higher quiz result (p = 0.02053). While this suggests that learning and absorbing information with an LLM could be more effective than curated texts, results from self-reported data indicate that there are few perceived differences between the effectiveness of LLM and curated texts. Conclusions: this exploratory and preliminary study revealed empirical insights between LLM usage and learning effectiveness in situ via physiological indicators, in contrast to prior work that has adopted post hoc frames over the medium- to long-term. Full article

While circuit parameter optimization has matured significantly, the systematic discovery of novel circuit topologies remains a bottleneck in analog design automation. This work presents SymXplorer, an open-source Python framework designed for automated topology exploration through symbolic modeling of analog components. The framework enables a component-agnostic approach to architecture-level synthesis, integrating stability analysis and higher-order filter exploration within a streamlined API. By modeling non-idealities as lumped parameters, the framework accounts for physical constraints directly within the symbolic analysis. To facilitate circuit sizing, SymXplorer incorporates a multi-objective optimization toolbox featuring Bayesian optimization and evolutionary algorithms for simulation-in-the-loop evaluation. Using this framework, we conduct a systematic search for differential Common-Gate (CG) Bandpass Transimpedance Amplifier (TIA) topologies tailored for 5G New Radio (NR) Radio-over-Fiber applications. We propose a novel, orthogonally tunable Bandpass TIA architecture identified by the tool. Implementation in 65 nm CMOS technology demonstrates the efficacy of the framework. Post-layout results exhibit a tunable gain of 30–50 dBΩ, a center frequency of 3.5 GHz, and a tuning range of 500 MHz. The design maintains a power consumption of less than 400 μW and an input-referred noise density of less than 50 pA/$\sqrt{\mathrm{Hz}}$ across the passband. Finally, we discuss how this symbolic framework can be integrated into future agentic EDA workflows to further automate the analog design cycle. SymXplorer is open-sourced to encourage innovation in symbolic-driven analog design automation. Full article

Background/Objectives: X-linked hypohidrotic ectodermal dysplasia (XLHED) is a rare monogenic disorder characterized by hypohidrosis, hypotrichosis, and hypodontia, caused primarily by pathogenic variants in the EDA gene. XLHED predominantly affects males due to its X-linked recessive inheritance, while female carriers may exhibit variable phenotypes due to random X-inactivation. Early diagnosis is critical for timely counseling and emerging therapeutic interventions. We report a rare prenatal diagnosis of XLHED in dizygotic dichorionic male twins during a dichorionic diamniotic pregnancy. At 24 weeks’ gestation, ultrasonographic anomalies—facial dysmorphisms, oligodontia, and hypoechogenic skin—raised suspicion for ectodermal dysplasia. Methods: Non-invasive prenatal test and targeted next-generation sequencing (NGS) of Cell-free DNA identified an hemizygous EDA deletion (c.612_629del; p.Ile205_Gly210del) with 52% variant allele frequency. Results: This in-frame deletion affects a highly conserved region in the TNF homology domain of ectodysplasin-A1, likely compromising protein function. The variant was confirmed in both fetuses via genetic analysis on amniotic fluid and in the heterozygous state in the mother, consistent with X-linked recessive inheritance. Family history revealed a maternal uncle with XLHED. Additional heterozygous variants were also identified in CPT2, GBA1, GJB2, and SMN1 genes. Following comprehensive genetic counseling, the mother opted for abortion. Conclusions: This case underscores the value of applying advanced genomic technologies—cfDNA-based NGS—for prenatal diagnosis of rare genetic disorders. The identification of apathogenic EDA variant expands the mutational spectrum of XLHED and supports early diagnosis for informed reproductive decisions and potential access to emerging prenatal therapies. Broader application of such technologies may improve outcomes in future pregnancies at risk for monogenic disorders. Full article

Computed tomography (CT) is a major source of low-dose ionizing radiation exposure in medical imaging. Risk assessment at this dose level is difficult and relies on the hypothetical linear no-threshold model. To address the response to such low doses in patients undergoing CT scans, we examined radiation-induced alterations at the transcriptomic and DNA damage levels in peripheral blood cells. Peripheral whole blood of 60 patients was collected before and after CT. Post-CT samples were obtained 4–6 h after scan (n = 28, in vivo incubation) or alternatively immediately after the CT scan, followed by ex vivo incubation (n = 32). The gene expression of known radiation-responsive genes (n = 9) was quantified using qRT-PCR. DNA double-strand breaks (DSB) were assessed in 12 patients through microscopic γ-H2AX + 53BP1 DSB focus staining. The mean dose–length product (DLP) across all scans was 561.9 ± 384.6 mGy·cm. Significant differences in the median differential gene expression (DGE) were detected between in vivo and ex vivo incubation conditions, implicating that ex vivo incubation masked the true effect in low-dose settings. The median DGE of in vivo-incubated samples showed a significant upregulation of EDA2R, MIR34AHG, PHLDA3, DDB2, FDXR, and AEN (p ranging from <0.001 to 0.041). In vivo, we observed a linear dose-dependent upregulation for several genes and an explained variance of 0.66 and 0.56 for AEN and FDXR, respectively. DSB focus analysis revealed a slight, non-significant increase in the average DSB damage post-exposure, at a mean DLP of 321.0 mGy·cm. Our findings demonstrate that transcriptional biomarkers are sensitive indicators of low-dose radiation exposure in medical imaging and could prove themselves as clinically applicable biodosimetry tools. Furthermore, the results underscore the need for dose optimization. Full article

Spinal cord injury (SCI) impairs motor function and requires rigorous rehabilitative therapy, motivating the development of approaches that are engaging and customizable. Virtual reality (VR) motor training with augmented sensory feedback (ASF) offers a promising pathway to enhance functional outcomes, yet it remains unclear how ASF modalities affect performance and underlying psychophysiological states in persons with SCI. Five participants with chronic incomplete cervical-level SCI controlled a virtual robotic arm with semi-isometric upper-body contractions while undergoing ASF training with either visual feedback (VF) or combined visual plus haptic feedback (VHF). Motor performance (pathlength, completion time), psychophysiological measures (EEG, EMG, EDA, HR), and perceptual ratings (agency, motivation, utility) were assessed before and after ASF training. VF significantly reduced pathlength (−12.5%, p = 0.0011) and lowered EMG amplitude (−32.5%, p = 0.0063), suggesting the potential for improved motor performance and neuromuscular efficiency. VHF did not significantly improve performance, but trended toward higher cortical engagement. EEG analyses showed VF significantly decreased alpha and beta activity after training, whereas VHF trended toward mild increases. Regression revealed improved performance was significantly (p < 0.05) associated with changes in alpha power, EMG, EDA, and self-reported motivation. ASF type may differentially shape performance and psychophysiological responses in SCI participants. These preliminary findings suggest VR-based ASF as a potent multidimensional tool for personalizing rehabilitation. Full article

Chemical modification is a valuable strategy for tuning enzyme functionality by introducing new reactive groups without disrupting the overall fold. Conventional amination using ethylenediamine (EDA) is effective, but the resulting modified proteins show limited reactivity for conjugation at neutral pH, and the modifier itself poses safety concerns due to its volatility and corrosive nature. Dihydrazides, in contrast, offer a safer and more versatile alternative: they operate through the same carboxyl-activation mechanism while enabling systematic investigation of chain-length effects. In this study, Thermomyces lanuginosus lipase (TLL) and Myceliophthora thermophila laccase (MTL) were modified using dihydrazides with different alkyl chain lengths (carbonyl (CZ), oxalyl (OX), succinyl (SC), and adipic (AA)), and compared to EDA-modified and unmodified enzymes to evaluate their effects on catalytic performance. Hydrazide-modified variants exhibited enhanced catalytic performance, reaching up to 2.5-fold (TLL-CZ) and 4.2-fold (MTL-AA and MTL-OX) higher efficiencies than unmodified and EDA-modified enzymes. Notably, AA provided the most consistent improvement across both enzymes (1.3-fold in TLL and the best in MTL). Molecular dynamics and docking analyses supported these findings, linking increased flexibility (higher RoG and RMSF) with higher k_cat, and changes in substrate binding with lower k_m. Overall, hydrazide-based modification broadens the spectrum of enzyme variants attainable through amination, while offering safer procedures, thus representing an alternative that overcomes the limitations of using EDA as a conventional aminating agent. Full article

Post-occlusive reactive hyperemia (PORH) is widely used to assess microvascular reactivity, but its systemic impact on contralateral neurovascular function remains unclear. This study quantified bilateral synchrony and asymmetry of cutaneous signals during unilateral PORH in healthy subjects using a novel multidimensional framework of inter-limb coherence. Twelve young adults underwent a standard suprasystolic occlusion (5 min at 200 mmHg) on the upper limb, while photoplethysmography (PPG), skin temperature, and electrodermal activity (EDA) were recorded bilaterally in the fingers. Coherence was characterized by profile similarity (Cross-Signal Similarity Index, CSSI), temporal lag (τ*), magnitude asymmetry (Bilateral Magnitude Difference Index, BDMI), directional concordance (Signal Direction Index, SDI; Directional Concordance Index, DCI), and integrated indices (IBIL, IBIS). At baseline, all signals showed high bilateral synchrony (CSSI ≈ 0.9; τ* < 20 ms). Occlusion markedly reduced CSSI for blood flow (0.89 to 0.07, p = 0.002) and temperature (0.93 to −0.03, p = 0.06), while EDA coherence remained preserved (0.95 to 0.82). Integrated indices decreased significantly (IBIL 0.84 to 0.17, p = 0.005; IBIS 0.84 to 0.18, p = 0.004) and recovered only partially during hyperemia (IBIL 0.20, p = 0.003). Directional concordance was heterogeneous: during hyperemia, 9 of 12 subjects showed concordant EDA changes but only 7 of 12 for perfusion. BDMI was largest for perfusion (≈0.8), moderate for temperature (≈0.5), and minimal for EDA (≈0.3). Unilateral PORH thus induces a marked loss of bilateral coherence in microvascular signals, whereas sympathetic-driven responses remain strongly synchronized. This dissociation reveals that occlusion evokes systemic autonomic adjustments beyond local hemodynamics. The proposed framework captures hidden aspects of neurovascular integration and may provide new markers for autonomic imbalance or perfusion asymmetry. Full article

Background/Objectives: Mental fatigue during driving, whether passive (arising from monotony) or active (caused by cognitive overload), is a critical factor for road safety. Despite the growing interest in monitoring techniques based on neurophysiological signals, current biomarkers are primarily validated only for detecting passive mental fatigue under monotonous conditions. The objective of this study is to evaluate the sensitivity of the MDrow index, which is based on EEG Alpha band activity, previously validated for detecting passive mental fatigue, with respect to active mental fatigue, i.e., the mental fatigue occurring in cognitively demanding driving scenarios. Methods: A simulated experimental protocol was developed featuring three driving scenarios with increasing complexity: monotonous, urban, and urban with dual tasks. Nineteen participants took part in the experiment, during which electroencephalogram (EEG), photoplethysmogram (PPG), and electrodermal activity (EDA) data were collected in addition to subjective assessments, namely the Karolinska Sleepiness Scale (KSS) and the Driving Activity Load Index (DALI) questionnaires. Results:The findings indicate that MDrow shows sensitivity to both passive and active mental fatigue (p < 0.001), thereby demonstrating stability even in the presence of additional cognitive demands. Furthermore, Heart Rate (HR) and Heart Rate Variability (HRV) increased significantly during the execution of more complex tasks, thereby suggesting a heightened response to mental workload in comparison to mental fatigue alone. Conversely, electrodermal measures evidenced no sensitivity to mental fatigue-related changes. Conclusions: These findings confirm the MDrow index’s validity as an objective and continuous marker of mental fatigue, even under cognitively demanding conditions. Full article