Brain mass estimation by head circumference and body mass methods in neonatal glycaemic modelling and control

Introduction

Hyperglycaemia is a common complication of stress and prematurity in extremely low-birth-weight infants. Model-based insulin therapy protocols have the ability to safely improve glycaemic control for this group. Estimating non-insulin-mediated brain glucose uptake by the central nervous system in these models is typically done using population-based body weight models, which may not be ideal.

Method

A head circumference-based model that separately treats small-for-gestational-age (SGA) and appropriate-for-gestational-age (AGA) infants is compared to a body weight model in a retrospective analysis of 48 patients with a median birth weight of 750 g and median gestational age of 25 weeks. Estimated brain mass, model-based insulin sensitivity (S_I) profiles, and projected glycaemic control outcomes are investigated. SGA infants (5) are also analyzed as a separate cohort.

Results

Across the entire cohort, estimated brain mass deviated by a median 10% between models, with a per-patient median difference in S_I of 3.5%. For the SGA group, brain mass deviation was 42%, and per-patient S_I deviation 13.7%. In virtual trials, 87–93% of recommended insulin rates were equal or slightly reduced (Δ < 0.16 mU/h) under the head circumference method, while glycaemic control outcomes showed little change.

Conclusion

The results suggest that body weight methods are not as accurate as head circumference methods. Head circumference-based estimates may offer improved modelling accuracy and a small reduction in insulin administration, particularly for SGA infants.     

医疗大数据特征挖掘及重大突发疾病早期预警

通过运用新兴的尖端云计算技术,设计研发了健康云平台。采用分布式云存储技术存储大规模的异构多模态生理信号数据,将数据挖掘模型（L1-逻辑斯蒂）整合至MapReduce框架中,快速挖掘用户的健康信息以及重大疾病高风险因子,让用户能实时地了解自己的身体状况,同时对用户的异常状况给出预警信息,并通知其前往医院就医,实现了对重大突发疾病的早期预警。     

An integrated emotional and physiological assessment for VR-based active shooter incident experiments

Unfortunately, active shooter incidents are on the rise in the United States. With the recent technological advancements, virtual reality (VR) experiments could serve as an effective method to prepare civilians and law enforcement personnel for such scenarios. However, for VR experiments to be effective for active shooter training and research, such experiments must be able to evoke emotional and physiological responses as live active shooter drills and events do. The objective of this study is thus to test the effectiveness of an active shooter VR experiment on emotional and physiological responses. Additionally, we consider different locomotion techniques (i.e., walk-in-place and controller) and explore their impact on users’ sense of presence. The results suggest that the VR active shooter experiment in this study can induce emotional arousal and increase heart rate of the participants immersed in the virtual environment. Furthermore, compared to the controller, the walk-in-place technique resulted in a higher emotional arousal in terms of negative emotions and a stronger sense of presence. The study presents a foundation for future active shooter experiments as it supports the ecological validity using VR for active shooter incident related work for the purposes of training or research.     

DEAR-MULSEMEDIA: Dataset for emotion analysis and recognition in response to multiple sensorial media

Traditionally, emotion recognition is performed in response to stimuli that engage either one (vision: image or hearing: audio) or two (vision and hearing: video) human senses. An immersive environment can be generated by engaging more than two human senses while interacting with multimedia content and is known as MULtiple SEnsorial media (mulsemedia). This study aims to create a new dataset of multimodal physiological signals to recognize emotions in response to such content. To this end, four multimedia clips are selected and synchronized with fan, heater, olfaction dispenser, and haptic vest to augment cold air, hot air, olfaction, and haptic effects respectively. Furthermore, physiological responses including electroencephalography (EEG), galvanic skin response (GSR), and photoplethysmography (PPG) are observed to analyze human emotional responses while experiencing mulsemedia content. A t-test applied using arousal and valence scores show that engaging more than two human senses evokes significantly different emotions. Statistical tests on EEG, GSR, and PPG responses also show a significant difference between multimedia and mulsemedia content. Classification accuracy of 85.18% and 76.54% is achieved for valence and arousal, respectively, using K-nearest neighbor classifier and feature-level fusion strategy.     

一种对时间连续数据进行分析查询的SQL扩展语言

在家庭电子医疗平台中,存在生理学时间连续数据,实现对其分析和查询是数据利用的基础。针对这类数据的特点,提出以关系型数据库结构化查询语言SQL为基础,定义相似查询算法,快速有效地从给定信号序列中找出符合某一相似度等级的相似子序列。相似匹配使用了分段聚合近似法和小波变换两种算法,易于进行子序列的相似度分级。实验结果表明,该试验系统能够高效、准确地完成设计功能。     

A H-QoS-demand personalized home physiological monitoring system over a wireless multi-hop relay network for mobile home healthcare applications

For the elderly and chronic patients with cardiovascular disease who live alone, it is necessary to constantly monitor their physiological parameters, especially the electrocardiogram (ECG), to effectively prevent and control their health condition and even to provide urgent treatment or care while an emergency such as the abnormal variation of heart rate (HR) occurs. In this paper, a wireless in-home physiological monitoring system, based on multi-hop relay communications, which can ubiquitously and continuously monitor the patient's ECG at any time or any place at home without space limit and the “dead spot” due to the extended communication coverage by multi-hop wireless connectivity, is proposed. The system consists of a mobile-care device, which is responsible for capturing and wirelessly sending the patient's ECG data, a wireless multi-hop relay network (WMHRN) that is in charge of relaying the data sent by the former, and a residential gateway (RG), which is responsible for gathering and uploading the received ECG data to the remote care server through the Internet to carry out the patient's health condition monitoring and the management of pathological data. However, in order to assure that the ECG data can be effectively and timely forwarded, from the mobile-care device to the RG through the WMHRN, to meet the healthcare quality of service (H-QoS) demand for reliable and real-time end-to-end ECG transmission, the analysis of WMHRN latency in data-forwarding stage and the deployment consideration of wireless relay nodes are investigated in detail in this work. Moreover, an emergency alert service using short message service (SMS), based on the detection of abnormal variation of HR, is also used in the RG to further enhance the healthcare service quality. A prototype of this system has been developed and implemented. Finally, the experimental results are presented to verify the feasibility of the proposed system.     

Multimodal focus attention and stress detection and feedback in an augmented driver simulator

This paper presents a driver simulator, which takes into account the information about the user’s state of mind (level of attention, fatigue state, stress state). The user’s state of mind analysis is based on video data and biological signals. Facial movements such as eyes blinking, yawning, head rotations, etc., are detected on video data: they are used in order to evaluate the fatigue and the attention level of the driver. The user’s electrocardiogram and galvanic skin response are recorded and analyzed in order to evaluate the stress level of the driver. A driver simulator software is modified so that the system is able to appropriately react to these critical situations of fatigue and stress: some audio and visual messages are sent to the driver, wheel vibrations are generated and the driver is supposed to react to the alert messages. A multi-threaded system is proposed to support multi-messages sent by the different modalities. Strategies for data fusion and fission are also provided. Some of these components are integrated within the first prototype of OpenInterface: the multimodal similar platform.     

Reliability of physiological and subjective responses to physical and psychosocial exposures during a simulated manufacturing task

Responses to physical and psychosocial exposures can be measured using diverse methods, but their reliability, particularly under multiple exposures, is largely unknown. Five classes of methods were used to assess physiological and subjective responses among 24 participants to four combinations of physical and psychosocial exposures while performing two identical sessions of a simulated overhead manufacturing task. As an exploratory analysis, test–retest reliability was quantified using intraclass correlation coefficients (ICC) and coefficients of variation (CV). Discomfort ratings were reliable under less favorable exposures, and ratings of the psychosocial environment were most reliable under favorable social support. Workload ratings were most reliable with high physical exposure and favorable social support, and task performance was reliable overall. EMG and heart rate had relatively low reliability. Slightly less than half of the variables were considered reliable, but reliability depended on exposure conditions.Relevance to industry: The study provides information on the reliability of commonly used exposure measurement methods. The results can guide the selection of physiological and psychological work outcome measurements in future studies and work evaluations.     

Autonomic nervous system and subjective ratings of strain in air-traffic control

The paper is aimed at studying the perceived strain in professional air-traffic controllers both through self-evaluation and physiological indicators from the autonomic nervous system (ANS). The number of aircraft to be monitored was the main independent variable and could evolve at random within 1 and 10. Five ANS variables were recorded continuously in 25 participants while they handled real traffic: skin potential, skin conductance, skin blood flow, skin temperature and instantaneous heart rate. The tonic level of each physiological variable was averaged to match the times spent monitoring a constant number of aircraft. After the session, participants reacted in compliance with the NASA-TLX rating scale. Subjective ratings and physiological values were closely correlated to the number of aircraft, especially when data were standardized thus reducing inter-subjects differences in baseline levels. Results provide objective information to prevent air-traffic controllers from overloaded situations as well as to improve passengers’ safety.     

Comparative analysis of the workload in seated and standing horizontal submaximal lifting tasks

The objective of the present laboratory study was to analyse physiological responses of horizontal lifting tasks when they were performed in sitting and standing positions. Heart rate and blood pressure were used as indices of circulatory strain. Lifting tasks were performed under four lifting positions: sitting-forward lift, sitting-twist lift, standing-forward lift, and standing-twist lift. The weights of the loads were 3, 5 and 7 kg and the frequencies of handling were 1, 4 and 6 lifts/min. This study supports the idea that heart rate is a sensitive measure for evaluating the effects of seated horizontal lifting tasks. The lifting positions and workload (frequency × load × distance) are important parameters in the design of these types of tasks. It appears that within the experimental values examined in this study, a seated position could be recommended while performing horizontal lifting tasks at workloads ≤4·6 kg.m.min ^?1;. The results are supported by smaller physiological responses.