Sudden Interruption Research Articles

Enhancing Ischemic Stroke Evaluation by a Model-Based Photoacoustic Tomography Algorithm.

Ischemic stroke (IS) is characterized by the sudden interruption of blood supply to the brain, resulting in neurological impairments and even mortality. Photoacoustic computed tomography (PACT) integrates the high contrast of optical imaging and the penetration of ultrasound imaging, enabling non-invasive IS evaluation. However, the image reconstruction quality significantly affects the oxyhemoglobin saturation (sO2) estimation. This study investigates a model-based with total variation minimized by augmented Lagrangian and alternating direction (MB-TVAL3) approach and compared it with the widely used back-projection (BP) and delay-and-sum (DAS) algorithms. Both simulations and invivo experiments are conducted to validate the performance of the MB-TVAL3 algorithm, showing a higher sO2 estimation accuracy and sensitivity in detecting infarct area compared to BP and DAS. The findings of this study emphasize the impact of acoustic inverse problem on the accuracy of sO2 estimation and the proposed approach offers valuable support for IS evaluation and cerebrovascular diagnosis.

The multiple dimensions of resilience in agricultural trade networks

Abstract The global food and agricultural trade network is crucial for food security. Shocks such as those posed by extreme weather events, conflicts, pandemics, and economic crises can test the resilience of the trade network to the sudden interruption of trade flows. Depending on the level of connectivity in the trade network and its structure, such shocks have the potential to propagate through the entire network and can affect countries’ food availability and variety. The paper contributes to the literature on food and agricultural trade networks in two main ways: (1) understanding the global trade network as a complex system that can be affected by and responds to shocks, we define and operationalize its resilience as a multidimensional concept which is shaped by the interdependencies in the network and their structure; (2) applying techniques from network analysis to examine the evolution of three dimensions of resilience within the global food and agricultural trade network between 1995 and 2019. The main findings show that, between 1995 and 2007, trade connectivity among countries increased. Overall, this bolstered countries’ and the network's resilience to trade shocks. However, vulnerabilities persisted in terms of ensuring sufficient product variety and quantity. Adding to these vulnerabilities, trade integration stalled in the second half of the series, pointing to a slight tendency towards trade disintegration and potentially lower resilience of countries to trade shocks already in 2019.

Study on the role of peripheral immune cells in cerebral ischemia

Stroke, primarily resulting from the sudden interruption of blood supply to the brain, remains a leading cause of morbidity and mortality worldwide. Following an ischemic stroke, the peripheral immune system significantly contributes to brain damage. Damage-associated molecular patterns (DAMPs) released from ischemic cells activate peripheral immune cells, resulting in increased inflammation and disruption of the blood-brain barrier (BBB). This review highlights the critical immune cells of the peripheral immune system activated after cerebral ischemia, with an emphasis on the roles of T cells, B cells, macrophages, and neutrophils. We discuss the pathophysiological mechanisms of cerebral ischemia, which include reduced blood flow, energy metabolism disorders, neuronal injury and death, and BBB disruption and cerebral edema. The interplay between the peripheral immune system and cerebral ischemia is explored, offering insights into the inflammatory and immunosuppressive responses following ischemic events. Meanwhile, current research advances and future research directions are presented, focusing on potential therapeutic targets within the peripheral immune system to improve outcomes in ischemic brain injury. In summary, this review underscores the necessity of understanding the peripheral immune system's role in cerebral ischemia to develop effective treatment strategies and enhance patient recovery.

Association between periodic variation of air temperature, humidity, atmospheric pressure and hospital admissions for acute occlusive mesenteric ischaemia

Referring to the intestinal ischemic injury caused by sudden interruption of the blood supply, acute mesenteric ischemia (AMI) is a highly fatal emergency with mortality rates varying from 58 to 80%. The aim of this study was to explore the effect of temperature on AMI admission. This was a retrospective, multicentric study. The medical records of 1477 patients with verified AMI who were consecutively admitted to 3 hospitals anytime between January 2010 and December 2020 were included in the study. Distributed lag non-linear model was applied, the model was adjusted for temperature, atmospheric pressure, relative humidity, year, holiday, day of the week, time and seasonality. AMI exhibited obvious sex preference, AMI patients tended to be male (M/F ratio = 2.3:1) and in their late 50 s. Hospital admissions of acute mesenteric arterial thromboembolism (AMAT) increased significantly with high temperatures on day of exposure and lag 0–14 day. The effect curve of daily average temperature on acute mesenteric venous thromboembolism (AMVT) admission was J-shaped, and the duration of cold effect was longer, while the duration of heat effect was shorter. An increase in hospital admissions of AMVT was found above 20 °C at lag 0–30. For the first time, our study indicated that temperature is significantly associated with the risk of AMI. Although it is not possible to always avoid exposure to extreme temperatures, one should be aware of dramatic temperature fluctuations and take appropriate precautions.

Modeling and SOC estimation of on-board energy storage device for trains under emergency traction

The sudden interruption of train power supply in an extreme environment will seriously threaten the safety of passengers and affect the operational efficiency of the railway system. In this case, the focus of attention becomes a method of running the train to the nearest rescue point based on the limited capacity of the on-board emergency energy storage device. Therefore, this paper reports research on the state of charge (SOC) estimation of train energy storage equipment to optimize the emergency traction strategy and energy utilization rate of trains to the maximum extent. First, with the emergency power supply of on-board lithium titanate batteries, the energy flow model of train emergency power supply is constructed for the first time. Second, based on the second-order equivalent circuit model and considering the utilization of regenerative braking energy, the relationship between battery capacity and open circuit voltage (OCV), temperature, current and SOC are constructed through experimental data, which significantly improves the accuracy and robustness of SOC estimation in complex and variable environments. Then, to effectively eliminate the impact of environmental on the estimation especially in the case of extremely low temperature (−20 °C), online model parameter discrimination and SOC estimation of lithium batteries are realized by combining recursive least squares with an optimal forgetting factor (FRLS) algorithm and a new temperature forgetting factor based adaptive extended Kalman filter (TFFAEKF) algorithm. The experimental results show that the proposed method achieves accurate SOC estimation, and the maximum error is less than 1% at different temperatures.

Exploring Factors Influencing Stroke Risk: Insights From a Predictive Analysis.

Introduction Stroke is a serious medical condition characterized by the sudden interruption of blood flow to the brain, resulting in the death of brain cells. It is a leading cause of long-term disability and mortality worldwide. Stroke has some associated risk factors, both modifiable and non-modifiable ones.As for non-modifiable risk factors, these are age, gender (men are more vulnerable), and family history of stroke.The controllable or adjustable risk factors include hypertension (high blood pressure), diabetes, smoking, high cholesterol levels, obesity, and insulin resistance. Methods In our study, we collected data from 229 patients which were originally collected for clinical purposes and were retrospectively analyzed. These data contain features such assex and age, the presence of ischemic heart disease (IHD) or stroke history, and different blood sugar readings. These measurements include fasting blood sugar (FBS), postprandial blood sugar (PPBS), HbA1c%, and insulin levels (fasting and postprandial).Furthermore, cholesterol was also tested, such as total cholesterol, triglycerides (TGL), high-density lipoprotein (HDL), low-density lipoprotein (LDL), and very low-density lipoprotein (VLDL). Surprisingly, stroke was observed in 24of the 205 patients. This contrast permits us to be concerned with the chance of the association between stroke and insulin levels. Given the imbalanced nature of our outcome variable (stroke occurrence), the primary analytical method will be logistic regression. Results In this cross-sectional study, we investigated the association between high insulin levels (both fasting and postprandial) and the occurrence of stroke within a dataset of 229 patients. Out of the 229 included cases, 102 individuals were female (44.5%) and 127 individuals were male (55.5%). Twenty-four cases have ischemic heart disease (10.5%). Among the analyzed cases, 24 individuals have a history of stroke. The average age of the sample is approximately 57 years ± 14.87. There was no significant difference between the males and females in most of the descriptive statistics. However, females experienced significantly higher levels of postprandial glucose level and significantly lower levels of postprandial insulin. According to our predictive model, we found that an increase in fasting insulin levels was linked to a lower risk of stroke occurrence. On the other hand, increasing insulin postprandial levels and age were associated with an increased risk of stroke. Conclusion Our study identified age, fasting insulin, and postprandial insulin as key factors influencing stroke risk. Higher fasting insulin levels were associated with reduced risk, while increased postprandial insulin and age were linked to higher risk. Blood glucose, cholesterol, and triglycerides had minor effects. Notably, higher total cholesterol and triglyceride levels were slightly associated with lower stroke occurrence. Further research with larger samples is needed for validation.

Virtual reality-brain computer interface hand function enhancement rehabilitation system incorporating multi-sensory stimulation

Stroke is an acute cerebrovascular disease in which sudden interruption of blood supply to the brain or rupture of cerebral blood vessels cause damage to brain cells and consequently impair the patient's motor and cognitive abilities. A novel rehabilitation training model integrating brain-computer interface (BCI) and virtual reality (VR) not only promotes the functional activation of brain networks, but also provides immersive and interesting contextual feedback for patients. In this paper, we designed a hand rehabilitation training system integrating multi-sensory stimulation feedback, BCI and VR, which guides patients' motor imaginations through the tasks of the virtual scene, acquires patients' motor intentions, and then carries out human-computer interactions under the virtual scene. At the same time, haptic feedback is incorporated to further increase the patients' proprioceptive sensations, so as to realize the hand function rehabilitation training based on the multi-sensory stimulation feedback of vision, hearing, and haptic senses. In this study, we compared and analyzed the differences in power spectral density of different frequency bands within the EEG signal data before and after the incorporation of haptic feedback, and found that the motor brain area was significantly activated after the incorporation of haptic feedback, and the power spectral density of the motor brain area was significantly increased in the high gamma frequency band. The results of this study indicate that the rehabilitation training of patients with the VR-BCI hand function enhancement rehabilitation system incorporating multi-sensory stimulation can accelerate the two-way facilitation of sensory and motor conduction pathways, thus accelerating the rehabilitation process.

A distributed coordinated control strategy for isolated AC microgrids based on consensus algorithm considering communication delay

AbstractIn the multi‐paralleled converter microgrid system, the traditional hierarchical control strategy can eliminate the bus voltage amplitude and frequency deviation from the rated value. However, isolated AC microgrids may face extreme scenarios such as communication delays and interruptions in data transmission due to the use of low‐bandwidth communication (LBC) lines. Additionally, the inconsistent line impedance of each distributed generation (DG) unit may result in the inaccurate division of reactive power in multi‐paralleled converter systems, thus affecting system stability. To address these issues, this paper presents a distributed coordinated control strategy for isolated AC microgrids based on the consensus algorithm. The proposed strategy first replaces LBC lines with a filter to alleviate the effects of communication delays. A small‐signal model is established in its state space, and stability of the microgrid system under the proposed control strategy is verified through eigenvalue analysis. Furthermore, based on the above theoretical analysis, a consensus algorithm is introduced, and a distributed control strategy for isolated AC microgrids based on the consensus algorithm is proposed to solve the issue of inaccurate equalization of the system's reactive power. Finally, factors that influence the dynamic convergence performance of the consensus algorithm are analyzed through simulation in PLECS software. Also, the maximum tolerable communication delays of the microgrid system under different communication topologies are also compared, and the system's robustness is evaluated under the condition of sudden communication interruption in a DG unit and sudden weather variation. These analyses confirmed the robustness of the proposed strategy against communication delays, output power fluctuation, and communication interruptions.

From brain “scar” to “bat shit crazy”: negotiating the madness of sexual violence discourse

AbstractThis article analyses how people who identify with psychiatric diagnoses in England and Wales make sense of and talk about their experiences of sexual violence. I examine how interview participants engaged with the hegemonic trauma discourse, as well as the consequences of this for meaning-making, affective pain, and the feminist imperative to ‘speak out’. The hegemonic trauma discourse is characterised by leaving a psychological ‘scar’; is premised on a sudden interruption to a ‘good life’; and is considered pathologically unspeakable without intervention. This discourse was both validating and affectively painful for participants, and interventions targeting dissociation were helpful for assuaging distress. However, it was additionally normative and exclusionary, and did not fulfil the political promise of ‘speaking out’, as all participants faced myriad socio-political denial.

Data-Driven Identification of Stroke through Machine Learning Applied to Complexity Metrics in Multimodal Electromyography and Kinematics.

A stroke represents a significant medical condition characterized by the sudden interruption of blood flow to the brain, leading to cellular damage or death. The impact of stroke on individuals can vary from mild impairments to severe disability. Treatment for stroke often focuses on gait rehabilitation. Notably, assessing muscle activation and kinematics patterns using electromyography (EMG) and stereophotogrammetry, respectively, during walking can provide information regarding pathological gait conditions. The concurrent measurement of EMG and kinematics can help in understanding disfunction in the contribution of specific muscles to different phases of gait. To this aim, complexity metrics (e.g., sample entropy; approximate entropy; spectral entropy) applied to EMG and kinematics have been demonstrated to be effective in identifying abnormal conditions. Moreover, the conditional entropy between EMG and kinematics can identify the relationship between gait data and muscle activation patterns. This study aims to utilize several machine learning classifiers to distinguish individuals with stroke from healthy controls based on kinematics and EMG complexity measures. The cubic support vector machine applied to EMG metrics delivered the best classification results reaching 99.85% of accuracy. This method could assist clinicians in monitoring the recovery of motor impairments for stroke patients.

High-reliability uninterruptible power supply manager for critical virtualization cluster

Information technology servers are complex, delicate, and expensive systems; power grid interruption is one of the possible causes that can lead to hardware damage or logical disk structure damage, with severe consequences. Moreover, a power grid drop causes a sudden interruption of the services managed by a server. Uninterruptible power supplies (UPS) provide backup power when the regular power grid source drops. UPSs can only maintain a server for a short time. Therefore, it is necessary to introduce a blackout manager who can correctly shut down the server activities. Moreover, the manager must be able to restore the servers' status when the electrical grid power returns to its normal state. This paper proposes a possible UPS power manager able to manage servers during a prolonged electrical blackout. The UPS power manager identifies the blackout and keeps the servers safe by saving their state and shutting them down properly. Following the power grid restoration, the UPS power manager restarts the servers and restores their state. The proposed approach has been evaluated on a virtualization cluster used for critical activities at the Politecnico di Torino.

Flexible optimal bus‐schedule bridging for metro operation‐interruption

AbstractUnder the sudden interruption of the metro, it is significant to dispatch emergency bridging buses to evacuate stranded passengers to improve linkage management and service reliability. Aiming at the problem of emergency bridging bus scheduling, considering the remaining capacity of conventional buses, passenger tolerance, and site convenience, a flexible combined emergency bridging bus scheduling model is constructed based on the constraints of vehicle capacity, dispatching capacity, and maximum evacuation times of emergency bridging bus, aiming at minimizing the maximum evacuation time and passenger delay. The improved Harris hawk algorithm is used to solve the model, and the evacuation plan of the demand‐responsive and station‐station bridging lines is obtained. The maximum evacuation time is 41 min, and the average delay of stranded passengers is 19 min. The results show that the maximum evacuation time is 10% and 27% less than the fixed combined and single scheduling. The average delay is 16% and 42% less than the fixed combination and traditional single scheduling. The sensitivity analysis of the influencing factors of emergency bridging bus scheduling is conducted. The results show that the flexible combined emergency bridging bus scheduling model constructed in this paper can improve evacuation efficiency and reduce passenger travel delays.

Central retinal artery occlusion after cardioversion of atrial fibrillation.

Central retinal artery occlusion (CRAO) is a vascular ophthalmic emergency. Often caused by a sudden interruption of blood flow to the eye, with profound and painless vision loss, resulting in irreversible cell damage. An impacted embolus at the narrowest part of the central retinal artery is the most common cause. Cardioversion is a medical procedure used to restore a normal heart rhythm in individuals with atrial fibrillation (AF). In some cases, cardioversion can lead to thromboembolic complications. If an embolus reaches the central retinal artery, it can block the blood flow to the retina, resulting in CRAO and subsequent vision loss.

Serum Calcium Normal Range in 1,000 Term Newborns

Introduction: Serum calcium rapidly declines at birth because of the sudden interruption of the maternal-fetal calcium influx. Several factors are known to influence serum calcium in the first days of life, including circulating concentrations of maternal vitamin D. Objective was to establish the normal range variations of neonatal serum calcium according to the current French vitamin D supplementation during pregnancy, i.e., 100,000 IU of cholecalciferol during the third trimester. Methods: We included in our prospective cohort study 1,002 mother-newborn dyads recruited from April 2012 to July 2014 in two centers located in the neighborhoods of Paris, France. Results: Total serum calcium at 3 days of life in neonates varied from 2.06 mmol/L to 2.73 mmol/L [2.5 and 97.5 percentiles], with a mean of 2.45 mmol/L. Serum calcium was similar between babies born from vitamin D-supplemented mothers and those born from non-supplemented ones. In univariate and multivariable analyses, we demonstrated the importance of maternal and cord blood 25(OH)D concentrations for newborn serum calcium maintenance. Conclusion: We established that the expected serum calcium in neonates ranges between 2.06 mmol/L and 2.73 mmol/L which is significantly wider than the adult range. This finding should help physicians in the diagnosis of hypo- or hypercalcemia. In addition, our study supports the importance of vitamin D supplementation and 25(OH)D status for neonatal serum calcium maintenance.

The Threat of Economic Deglobalization from Cold War 2.0: A Japanese Perspective

Abstract The intensified geopolitical tension in Northeast Asia and the U.S.–China confrontation have shifted policy debates in Japan toward national security while the economic discussion has become thin. To regain more balanced policy talks, this paper tries to quantitatively comprehend the effect of the United States and its allies’ export controls on the East Asian machinery production networks and Japan's trade performance. Major findings include the following four points: First, most of the supply chain decoupling policies by the Japanese government have been the ones to prepare for sudden interruptions of the supply of important items while decoupling policies for strategic competition are limited only in the context of the cooperation with the United States. Second, international trade statistics at the industry level do not show clear evidence of supply chain decoupling in East Asia due to the U.S. export controls, at least up to 2022. Third, however, the negative trade effect becomes visible at the product or individual firms’ level, and the recent strengthening of the United States and its allies’ export controls may augment the negative effect on machinery production networks. Fourth, although the scope of trade controls would expand further, the supply chain decoupling is likely to end up with a partial one. The paper claims that middle powers such as Japan must establish a well-balanced trade policy.

Ocular microvascular alteration in patients with myocardial infarction—a new OCTA study

Myocardial infarction is defined as a sudden decrease or interruption in blood flow to the coronary arteries, causing ischemic necrosis of the corresponding cardiomyocytes. It is unclear whether systemic macrovascular alterations are associated with retinal microvascular changes. This study utilized optical coherence tomography angiography (OCTA) to compare variations in conjunctival vascular density and fundus retinal vessel density between patients with myocardial infarction (MI) and healthy controls. This study recruited 16 patients (32 eyes) with MI and 16 healthy controls (32 eyes). The superficial retinal layer (SRL), deep retinal layer (DRL) and conjunctival capillary plexus in each eye were evaluated by OCTA. Parameters measured included the density of the temporal conjunctival capillary, retinal microvascular (MIR) and macrovascular (MAR) alterations and total MIR (TMI). The microvascular density of each retinal region was evaluated by the hemisphere segmentation (SR, SL, IL, and IR), annular partition (C1, C2, C3, C4, C5 and C6), and modified early treatment of diabetic retinopathy study (R, S, L, and I) methods. In the macular area, the superficial and deep retinal microvascular densities displayed notable variations. In the superficial layers, the superficial TMI, superficial MIR, and superficial MAR, as well as densities in the SL, IL, S, L, C1, C2, C5 and C6 regions, were significantly lower in MI patients (p < 0.05 each). In the deep layers, the deep MIR and deep TMI), as well as densities in the SL, IL, L, C1, C2 and C6 regions were significantly lower in MI patients (p < 0.05 each). In contrast, the conjunctival microvascular density was significantly higher in MI patients than in healthy controls (p < 0.001). The microvascular densities measured in the deep and superficial retinal layers and in the conjunctiva differ in MI patients and healthy controls. OCTA is effective in detecting changes in the ocular microcirculation.

Negative Myoclonus: Neurophysiological Study and Clinical Impact in Progressive Myoclonus Ataxia.

Negative myoclonus (NM) is an involuntary movement caused by a sudden interruption of muscular activity, resulting in gait problems and falls. To establish frequency, clinical impact, and neurophysiology of NM in progressive myoclonus ataxia (PMA) patients. Clinical, neurophysiological, and genetic data of 14 PMA individuals from University Medical Centre Groningen (UMCG) Expertise Center Movement Disorder Groningen were retrospectively collected. Neurophysiological examination included video-electromyography-accelerometry assessment in all patients and electroencephalography (EEG) examination in 13 individuals. Jerk-locked (or silent period-locked) back-averaging and cortico-muscular coherence (CMC) analysis aided the classification of myoclonus. NM was present in 6 (NM+) and absent in 8 (NM-) PMA patients. NM+ individuals have more frequent falls (100% vs. 37.5%) and higher scores on the Gross Motor Function Classification System (GMFCS) (4.3 ±0.74 vs. 2.5 ±1.2) than NM- individuals. Genetic background of NM+ included GOSR2 and SEMA6B, while that of NM- included ATM, KCNC3, NUS1, STPBN2, and GOSR2. NM was frequently preceded by positive myoclonus (PM) and silent-period length was between 88 and 194 ms. EEG epileptiform discharges were associated with NM in 2 cases. PM was classified as cortical in 5 NM+ and 2 NM- through EEG inspection, jerk-locked back-averaging, or CMC analysis. Neurophysiological examination is crucial for detecting NM that could be missed on clinical examination due to a preceding PM. Evidence points to a cortical origin of NM, an association with more severe motor phenotype, and suggests the presence of genetic disorders causing either a PMA or progressive myoclonus epilepsy, rather than pure PMA phenotype. © 2024 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Advanced Management of Electric Vehicle Charging Conditions Utilizing a Photovoltaic-Based Multi-Mode Converter System

The surging popularity of electric vehicles (EVs) as an environmentally friendly mode of transportation has heightened the need for conveniently situated charging stations, since EVs have limited range on their internal batteries. Fast charging stations, especially super-fast charging stations, may strain the power infrastructure owing to the risk of overload during peak hours, sudden power interruptions, and voltage drops. This work examines the detailed modeling of a direct current (DC) power generation and battery energy storage system integrated into a multiport converter-based electric vehicle (EV) charging station. This project assesses the feasibility of utilizing Plug-in electric vehicles (PEVs) in Vehicle to Home (V2H) scenarios as a means of residential battery storage or backup generator during power outages or distribution system faults, which are typically of shorter duration. Both the simulated and experimental results validate the feasibility of PCMM and demonstrate its capacity to accomplish the design objective. The charger has been designed and its operation validated using a space vector modulation technique and a simulation analysis. The simulation findings indicate that the proposed charger and a compatible autonomous EMS would interact well in a typical residential setting.

On the usage of pulsator data within the load spectra assessment of gears

Tooth root fatigue fracture is one of the most critical gear failure modes. This is due to the fact that it may cause a sudden interruption of the power flow within the gearbox, which typically results in the complete failure of the transmission. Therefore, a crucial design aspect is the accurate characterization of the gear bending fatigue strength. Here, designers can rely on experimental tests in order to obtain data related to their specific industrial reality.Within this context, pulsator test, also called Single Tooth Bending Fatigue (STBF) test, is the most adopted experimental methodology. As such tests are performed only on selected teeth within a testing device and not on all teeth of a running gear pair, the pulsator experimental outcome has to be elaborated before using it in the actual design phase.Depending on the elaboration methods, several SN curves can be obtained, and those curves will differ from the one predicted by the standards (e.g. ISO 6336 and ANSI AGMA 2001-D04). Furthermore, different SN curves will provide a different assessment when load spectra are considered. Here, the usage of data obtained from pulsator tests is analyzed within the phase in which load spectra are considered while designing a gear. In particular, this article discusses the differences between various elaboration methodologies and an assessment based on standardized curves.

Causality-Enhanced Multiple Instance Learning with Graph Convolutional Networks for Parkinsonian Freezing-of-Gait Assessment.

Freezing of gait (FoG) is a common disabling symptom of Parkinson's disease (PD). It is clinically characterized by sudden and transient walking interruptions for specific human body parts, and it presents the localization in time and space. Due to the difficulty in extracting global fine-grained features from lengthy videos, developing an automated five-point FoG scoring system is quite challenging. Therefore, we propose a novel video-based automated five-classification FoG assessment method with a causality-enhanced multiple-instance-learning graph convolutional network (GCN). This method involves developing a temporal segmentation GCN to segment each video into three motion stages for stage-level feature modeling, followed by a multiple-instance-learning framework to divide each stage into short clips for instance-level feature extraction. Subsequently, an uncertainty-driven multiple-instance-learning GCN is developed to capture spatial and temporal fine-grained features through GCN scheme and uncertainty learning, respectively, for acquiring global representations. Finally, a causality-enhanced graph generation strategy is proposed to exploit causal inference for mining and enhancing human structures causally related to clinical assessment, thereby extracting spatial causal features. Extensive experimental results demonstrate the excellent performance of the proposed method on five-classification FoG assessment with an accuracy of 62.72% and an acceptable accuracy of 91.32%, which is confirmed by independent testing. Additionally, it enables temporal and spatial localization of FoG events to a certain extent, facilitating reasonable clinical interpretations. In conclusion, our method provides a valuable tool for automated FoG assessment in PD, and the proposed causality-related component exhibits promising potential for extension to other general and medical fine-grained action recognition tasks.