Search Results (100)

Neuroactive steroids (NAS) have long been recognized for their hypnotic and anesthetic properties in both clinical and preclinical settings. While sex differences in NAS sensitivity are acknowledged, the underlying mechanisms remain poorly understood. Here, we examined sex-specific responses to an endogenous NAS epipregnanolone (EpiP) in wild-type mice using behavioral assessment of hypnosis (loss of righting reflex, LORR) and in vivo electrophysiological recordings. Specifically, local field potentials (LFPs) were recorded from the central medial thalamus (CMT) and electroencephalogram (EEG) signals were recorded from the barrel cortex. We found that EpiP-induced LORR exhibited clear sex differences, with females showing increased sensitivity. Spectral power analysis and thalamocortical (TC) and corticocortical (CC) phase synchronization further supported enhanced hypnotic susceptibility in female mice. Our findings reveal characteristic sex-dependent effects of EpiP on the synchronized electrical activity in both thalamus and cortex. These results support renewed exploration of endogenous NAS as clinically relevant anesthetic agents. Full article

Background/Objectives: In the current opioid crisis, medical hypnosis has been proposed as an alternative to opioids to control acute and chronic pain. The aim of this study was to use a meta-analysis to conduct an objective assessment of the value of medical hypnosis for the management of acute and chronic pain and opioid consumption. Methods: An initial PubMed search showed 111 relevant studies out of 1115. Twelve randomized controlled studies (RCTs) were identified, published from January 2014 to December 2024, focusing on acute and chronic pain. These RCTs were analyzed to compare the effects of medical hypnosis vs. standard care. Results: The use of medical hypnosis for acute pain was found to decrease pain by 0.54 standard deviations (SD) compared to the standard care, and the effect was medium and statistically significant (95% CI [0.19–0.90]; p = 0.0024). Oral morphine equivalents (OME) in the hypnosis group were 1.5 SD lower than in the placebo group, which was statistically significant (95% CI [0.12, 2.88]; p = 0.03). Unlike the effectiveness of hypnosis for acute pain treatment, hypnosis was not found to have any impact on the treatment of chronic pain. The mean pain value difference in the hypnosis group had little effect and showed a statistically insignificant result—a Hedges’ g score of 0.07 (95% CI [−0.14–0.27]; p = 0.518). Conclusions: The use of medical hypnosis was associated with a statistically significant decrease in acute pain scores and OME, suggesting it is a potential alternative to opioids, but our analysis indicates that hypnosis does not reduce chronic pain. Full article

Driver factors are the main cause of road traffic accidents. For the research of automotive active safety, an identification method for road hypnosis of a driver of a car with dynamic human–vehicle heterogeneous data fusion calculation is proposed. Road hypnosis is an unconscious driving state formed by the combination of external environmental factors and the psychological state of the car driver. When drivers fall into a state of road hypnosis, they cannot clearly perceive the surrounding environment and make various reactions in time to complete the driving task. The safety of humans and cars is greatly affected. Therefore, the study of the identification of drivers’ road hypnosis is of great significance. Vehicle and virtual driving experiments are designed and carried out to collect human and vehicle data. Eye movement data and EEG data of human data are collected with eye movement sensors and EEG sensors. Vehicle speed and acceleration data are collected by a mobile phone with AutoNavi navigation, which serves as an onboard sensor. In order to screen the characteristics of human and vehicles related to the road hypnosis state, the characteristic parameters of the road hypnosis in the preprocessed data are selected by the method of independent sample T-test, the hidden Markov model (HMM) is constructed, and the identification of the road hypnosis of the Ridge Regression model is combined. In order to evaluate the identification performance of the model, six evaluation indicators are used and compared with multiple regression models. The results show that the hidden Markov-Ridge Regression model is the most superior in the identification accuracy and effect of the road hypnosis state. A new technical scheme reference for the development of intelligent driving assistance systems is provided by the proposed comprehensive road hypnosis state identification model based on human–vehicle data can provide, which can effectively improve the life recognition ability of automobile intelligent cockpits, enhance the active safety performance of automobiles, and further improve traffic safety. Full article

Background: Pregnant women are likely to experience depression due to various factors. Hypnobirthing is a non-invasive therapy that can be used to treat depression during pregnancy. This study aims to systematically review the effect of hypnobirthing on antenatal depression. Methods: This study employs a systematic review following PRISMA guidelines. Articles were retrieved from PubMed, ScienceDirect, the Cochrane Library, Google Scholar, and hand searches. Articles were included for review if they met the following inclusion criteria: (1) published in the last ten years (2014–2024); (2) the articles published in English; (3) article types are original research articles and reviews; (4) the full text can be retrieved; and (5) the findings of the selected articles should discuss the effect of hypnobirthing or hypnosis for birth. Articles were critically appraised using Joanna Briggs Institute tools. Results: The initial search yielded 7603 records; nine studies met the inclusion criteria for systematic review, and four studies for meta-analysis. The articles were analyzed, and findings were presented in narrative ways and categorized into three themes: the effect of therapy, the administration of the therapy, and the mechanism of the therapy. The therapy was performed by different methods, involving hypnosis, daily relaxation, progressive muscle relaxation, breathing exercises, the J-breathing technique, meditation, visualization, and ego strengthening. Additionally, participants were encouraged to do self-practice at home and were followed up by personal visits, phone calls, or text messages. Conclusions: The majority of the studies found that hypnobirthing ameliorated antenatal depression, despite the variation in initial administration and the duration of therapy. Further research is needed to standardize therapy protocols and explore long-term outcomes. Full article

Human factors are the most important factor in road traffic crashes. Human-caused traffic crashes can be reduced through the active safety system of vehicles. Road hypnosis is an unconscious driving state caused by the combination of external environmental factors and the driver’s psychological state. When drivers fall into a state of road hypnosis, they cannot clearly perceive the surrounding environment and make various reactions in time to complete the driving task, and driving safety is greatly affected. Therefore, road hypnosis identification is of great significance for the active safety of vehicles. A road hypnosis identification model based on XGBoost—Hidden Markov is proposed in this study. Driver data and vehicle data related to road hypnosis are collected through the design and conduct of vehicle driving experiments. Driver data, including eye movement data and EEG data, are collected with eye movement sensors and EEG sensors. A mobile phone with AutoNavi navigation is used as an on-board sensor to collect vehicle speed, acceleration, and other information. Power spectrum density analysis, the sliding window method, and the point-by-point calculation method are used to extract the dynamic characteristics of road hypnosis, respectively. Through normalization and standardization, the key features of the three types of data are integrated into unified feature vectors. Based on XGBoost and the Hidden Markov algorithm, a road hypnotic identification model is constructed. The model is verified and evaluated through visual analysis. The results show that the road hypnosis state can be effectively identified by the model. The extraction of road hypnosis-related features is realized in non-fixed driving routes in this study. A new research idea for road hypnosis and a technical scheme reference for the development of intelligent driving assistance systems are provided, and the life identification ability of the vehicle intelligent cockpit is also improved. It is of great significance for the active safety of vehicles. Full article

Background: Hypnosis sedation has recently been used for anesthesia in breast oncologic surgery. Methods: Between January 2017 and October 2019, 284 patients from our Breast Clinic (Cliniques Universitaires Saint-Luc, Université Catholique de Louvain) and from the Jolimont Hospital were prospectively included in an interventional non-randomized study approved by our two local ethics committees and registered on clinicaltrials.gov (NCT03330117). Ninety-three consecutive patients underwent surgery while on general anesthesia (GA group). Ninety-two consecutive patients underwent surgery while on general anesthesia preceded by a hypnorelaxation session (GAVRH group). Ninety-five consecutive patients underwent surgery while exclusively on hypnosis sedation (HYPS group). Clinical parameters (pain score, anxiety and distress score) were measured on days 0, 1 and 8 for all patients. All evaluable patients underwent NLR (neutrophil-to-lymphocyte ratio) and CRP (C-reactive protein) dosage on days 0, 1 and 8. Results: Pain scores and anxiety scores were statistically lower in the HYPS group on days 1 and 8, as was the duration of NSAID consumption. NLR and CRP values were significantly inferior on day 1 for all patients who benefited from hypnosis sedation. Conclusions: Some benefits of hypnosis sedation (reduction in postoperative pain, decrease in NSAID consumption) are correlated with a significant reduction in inflammatory parameters in the perioperative process. Full article

A driver in road hypnosis has two different types of characteristics. One is the external characteristics, which are distinct and can be directly observed. The other is internal characteristics, which are indistinctive and cannot be directly observed. The eye movement characteristic, as a distinct external characteristic, is one of the typical characteristics of road hypnosis identification. The electroencephalogram (EEG) characteristic, as an internal feature, is a golden parameter of drivers’ life identification. This paper proposes an identification method for road hypnosis based on the fusion of human life parameters. Eye movement data and EEG data are collected through vehicle driving experiments and virtual driving experiments. The collected data are preprocessed with principal component analysis (PCA) and independent component analysis (ICA), respectively. Eye movement data can be trained with a self-attention model (SAM), and the EEG data can be trained with the deep belief network (DBN). The road hypnosis identification model can be constructed by combining the two trained models with the stacking method. Repeated Random Subsampling Cross-Validation (RRSCV) is used to validate models. The results show that road hypnosis can be effectively recognized using the constructed model. This study is of great significance to reveal the essential characteristics and mechanisms of road hypnosis. The effectiveness and accuracy of road hypnosis identification can also be improved through this study. Full article

Background: Managing anxiety and behavior during pediatric dental procedures is challenging. This study examines the effects of combining ibuprofen with midazolam sedation using both behavioral management and clinical hypnosis to improve patient cooperation and reduce post-treatment pain. Methods: A retrospective cohort study of 311 children (mean age 74.2 months, standard deviation (SD) = 24.7) was conducted. Patients received either midazolam with ibuprofen (n = 156) or midazolam only (n = 155). Behavior was assessed using the Venham Behavior Rating Scale and anxiety with the Dental Subscale of Children’s Fear Survey Schedule (CFSS-DS) and the Inventory of Stressful Situations (ISS) questionnaires. Statistical analyses included Mann–Whitney U tests and correlation analyses. Results: Ibuprofen did not significantly improve behavior during procedures (drinking phase 0.61, SD 1.31, p = 0.13; before treatment 0.25, SD 0.93, p = 0.53, anesthesia 1.21, SD 1.55, p = 0.29; after treatment 0.51, SD 1.22, p = 0.68), indicating that pharmacological pain management alone is insufficient to address behavioral challenges. Ibuprofen significantly reduced post-treatment pain, with 7.2% of cases reporting pain in the non-ibuprofen group compared to none in the ibuprofen group (p < 0.05). Conclusions: Ibuprofen had no effect on intraoperative behavior and only a limited effect on post-procedural pain, mainly for more invasive procedures. This study highlights the integration of sedation with behavioral strategies, such as clinical hypnosis, to manage anxiety and improve patient cooperation, aiming to enhance treatment outcomes using this integrative approach to pediatric dentistry. Further research is needed to optimize these strategies and verify them in a prospective setting. Full article

Within biomedical engineering, there has been significant collaboration among clinicians, control engineers, and researchers to tailor treatments to individual patients. Anesthesia is integral to numerous medical procedures, necessitating precise management of hypnosis, analgesia, neuromuscular blockade, and hemodynamic variables. Recent attention has focused on computer-controlled anesthesia and hemodynamic stabilization. This research proposes the integration of a decentralized control strategy for the induction phase with a decoupled control approach for the maintenance phase, aimed at mitigating interactions within the multivariable human system. The proposed strategy is based on fractional-order controllers. The solution is validated using an open-source patient simulator featuring data from 24 virtual patients, demonstrating the efficiency of the proposed approach with respect to decentralized control. Full article

Background/Objectives: Hypnosis shows great potential for managing patients suffering from fibromyalgia and chronic pain. Several studies have highlighted its efficacy in improving pain, quality of life, and reducing psychological distress. Despite its known feasibility and efficacy, the mechanisms of action remain poorly understood. Building on these insights, this innovative study aims to assess neural activity during hypnosis in fibromyalgia patients using high-density electroencephalography (EEG) and self-reported measures. Methods: Thirteen participants with fibromyalgia were included in this study. EEG recordings were done during resting state and hypnosis conditions. After both conditions, levels of pain, comfort, absorption, and dissociation were assessed using a numerical rating scale. Time perception was collected via an open-ended question. The study was prospectively registered in the ClinicalTrials.gov public registry (NCT04263324). Results: Neural oscillations showed increased theta power during hypnosis in the left parietal and occipital electrodes, increased beta power in the frontal and left temporal electrodes, and increased slow-gamma power in the frontal and left parietal electrodes. Functional connectivity using pairwise-phase consistency measures showed decreased connectivity in the frontal electrodes during hypnosis. Graph-based measures, the node strength, and the cluster coefficient were lower in frontal electrodes in the slow-gamma bands during hypnosis compared to resting state. Key findings indicate significant changes in neural oscillations and brain functional connectivity, suggesting potential electrophysiological markers of hypnosis in this patient population. Full article

Hypnotic phenomena exhibit significant inter-individual variability, with some individuals consistently demonstrating efficient responses to hypnotic suggestions, while others show limited susceptibility. Recent neurophysiological studies have added to a growing body of research that shows variability in hypnotic susceptibility is linked to distinct neural characteristics. Building on this foundation, our previous work identified that individuals with high and low hypnotic susceptibility can be differentiated based on the arrhythmic activity observed in resting-state electrophysiology (rs-EEG) outside of hypnosis. However, because previous work has largely focused on mean spectral characteristics, our understanding of the variability over time of these features, and how they relate to hypnotic susceptibility, is still limited. Here we address this gap using a time-resolved assessment of rhythmic alpha peaks and arrhythmic components of the EEG spectrum both prior to and following hypnotic induction. Using multivariate pattern classification, we investigated whether these neural features differ between individuals with high and low susceptibility to hypnosis. Specifically, we used multivariate pattern classification to investigate whether these non-stationary neural features could distinguish between individuals with high and low susceptibility to hypnosis before and after a hypnotic induction. Our analytical approach focused on time-resolved spectral decomposition to capture the intricate dynamics of neural oscillations and their non-oscillatory counterpart, as well as Lempel–Ziv complexity. Our results show that variations in the alpha center frequency are indicative of hypnotic susceptibility, but this discrimination is only evident during hypnosis. Highly hypnotic-susceptible individuals exhibit higher variability in alpha peak center frequency. These findings underscore how dynamic changes in neural states related to alpha peak frequency represent a central neurophysiological feature of hypnosis and hypnotic susceptibility. Full article

The driver in road hypnosis has not only some external characteristics, but also some internal characteristics. External features have obvious manifestations and can be directly observed. Internal features do not have obvious manifestations and cannot be directly observed. They need to be measured with specific instruments. Electroencephalography (EEG), as an internal feature of drivers, is the golden parameter for drivers’ life identification. EEG is of great significance for the identification of road hypnosis. An identification method for road hypnosis based on human EEG data is proposed in this paper. EEG data on drivers in road hypnosis can be collected through vehicle driving experiments and virtual driving experiments. The collected data are preprocessed with the PSD (power spectral density) method, and EEG characteristics are extracted. The neural networks EEGNet, RNN, and LSTM are used to train the road hypnosis identification model. It is shown from the results that the model based on EEGNet has the best performance in terms of identification for road hypnosis, with an accuracy of 93.01%. The effectiveness and accuracy of the identification for road hypnosis are improved in this study. The essential characteristics for road hypnosis are also revealed. This is of great significance for improving the safety level of intelligent vehicles and reducing the number of traffic accidents caused by road hypnosis. Full article

Burn injuries are among the most traumatic events a person can endure, often causing significant psychological dysfunction and severe pain. Hypnosis shows promise as a complementary intervention to manage pain and reduce the psychological distress associated with burn injury and treatment. This paper reviews the literature regarding hypnosis and potential applications of hypnosis in the management of burns. Hypnosis offers an effective, low-cost intervention that is widely applicable in the management of burns and can play a role in more acute and austere settings where resources are often limited. Full article

Despite the lack of evidence, opioids are still routinely used as a solution to long-term management for chronic noncancer pain (CNCP). Given the significant risks associated with long-term opioid use, including the increased number of unregulated opioid pills at large in the opioid ecosystem, opioid cessation or reduction may be the desired goal of the patient and clinician. Viable nonpharmacological interventions (NPIs) to complement and/or replace opioids for CNCP are needed. Comprehensive reviews that address the impact of NPIs to help adults with CNCP reduce opioid use safely are lacking. We conducted a literature search in PubMed, CINAHL, Embase, PsycINFO, and Scopus for studies published in English. The initial search was conducted in April 2021, and updated in January 2024. The literature search yielded 19,190 relevant articles. Thirty-nine studies met the eligibility criteria and underwent data extraction. Of these, nineteen (49%) were randomized controlled trials, eighteen (46%) were observational studies, and two (5%) were secondary analyses. Among adults with CNCP who use opioids for pain management, studies on mindfulness, yoga, educational programs, certain devices or digital technology, chiropractic, and combination NPIs suggest that they might be an effective approach for reducing both pain intensity and opioid use, but other NPIs did not show a significant effect (e.g., hypnosis, virtual reality). This review revealed there is a small to moderate body of literature demonstrating that some NPIs might be an effective and safe approach for reducing pain and opioid use, concurrently. Full article