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Advances in Wireless,Batteryless,Implantable Electronics for Real‑Time,Continuous Physiological Monitoring
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作者 Hyeonseok Kim Bruno Rigo +2 位作者 Gabriella Wong Yoon Jae Lee Woon‑Hong Yeo 《Nano-Micro Letters》 SCIE EI CSCD 2024年第3期254-302,共49页
This review summarizes recent progress in developing wireless,batteryless,fully implantable biomedical devices for real-time continuous physiological signal monitoring,focusing on advancing human health care.Design co... This review summarizes recent progress in developing wireless,batteryless,fully implantable biomedical devices for real-time continuous physiological signal monitoring,focusing on advancing human health care.Design considerations,such as biological constraints,energy sourcing,and wireless communication,are discussed in achieving the desired performance of the devices and enhanced interface with human tissues.In addition,we review the recent achievements in materials used for developing implantable systems,emphasizing their importance in achieving multi-functionalities,biocompatibility,and hemocompatibility.The wireless,batteryless devices offer minimally invasive device insertion to the body,enabling portable health monitoring and advanced disease diagnosis.Lastly,we summarize the most recent practical applications of advanced implantable devices for human health care,highlighting their potential for immediate commercialization and clinical uses. 展开更多
关键词 Implantable electronics Biomedical systems Batteryless devices Wireless electronics physiological signal monitoring
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RFID Positioning and Physiological Signals for Remote Medical Care 被引量:3
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作者 Wen-Tsai Sung Sung-Jung Hsiao 《Computer Systems Science & Engineering》 SCIE EI 2022年第4期289-304,共16页
The safety of patients and the quality of medical care provided to them are vital for their wellbeing.This study establishes a set of RFID(Radio Fre-quency Identification)-based systems of patient care based on physiol... The safety of patients and the quality of medical care provided to them are vital for their wellbeing.This study establishes a set of RFID(Radio Fre-quency Identification)-based systems of patient care based on physiological sig-nals in the pursuit of a remote medical care system.The RFID-based positioning system allows medical staff to continuously observe the patient's health and location.The staff can thus respond to medical emergencies in time and appropriately care for the patient.When the COVID-19 pandemic broke out,the proposed system was used to provide timely information on the location and body temperature of patients who had been screened for the disease.The results of experiments and comparative analyses show that the proposed system is superior to competing systems in use.The use of remote monitoring technology makes user interface easier to provide high-quality medical services to remote areas with sparse populations,and enables better care of the elderly and patients with mobility issues.It can be found from the experiments of this research that the accuracy of the position sensor and the ability of package delivery are the best among the other related studies.The presentation of the graphical interface is also the most cordial among human-computer interaction and the operation is simple and clear. 展开更多
关键词 Remote medical care active RFID POSITIONING physiological signal
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Breathable Electronic Skins for Daily Physiological Signal Monitoring 被引量:1
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作者 Yi Yang Tianrui Cui +5 位作者 Ding Li Shourui Ji Zhikang Chen Wancheng Shao Houfang Liu Tian-Ling Ren 《Nano-Micro Letters》 SCIE EI CAS CSCD 2022年第10期108-135,共28页
With the aging of society and the increase in people’s concern for personal health,long-term physiological signal monitoring in daily life is in demand.In recent years,electronic skin(e-skin)for daily health monitori... With the aging of society and the increase in people’s concern for personal health,long-term physiological signal monitoring in daily life is in demand.In recent years,electronic skin(e-skin)for daily health monitoring applications has achieved rapid development due to its advantages in high-quality physiological signals monitoring and suitability for system integrations.Among them,the breathable e-skin has developed rapidly in recent years because it adapts to the long-term and high-comfort wear requirements of monitoring physiological signals in daily life.In this review,the recent achievements of breathable e-skins for daily physiological monitoring are systematically introduced and discussed.By dividing them into breathable e-skin electrodes,breathable e-skin sensors,and breathable e-skin systems,we sort out their design ideas,manufacturing processes,performances,and applications and show their advantages in long-term physiological signal monitoring in daily life.In addition,the development directions and challenges of the breathable e-skin are discussed and prospected. 展开更多
关键词 Electronic skin Breathable physiological signal monitoring Wearable systems
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Wearable Wireless Body Area Nodes for Remote Physiological Signal Monitoring System
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作者 M. G. Srinivasa P. S. Pandian 《Journal of Biomedical Science and Engineering》 2019年第2期151-182,共32页
Wearable remote health monitoring systems have gained significant prominence in the recent years due to their growth in technological advances. One form of the Wearable Physiological Monitoring System (WPMS) is the We... Wearable remote health monitoring systems have gained significant prominence in the recent years due to their growth in technological advances. One form of the Wearable Physiological Monitoring System (WPMS) is the Wearable Body Area Networks (WBAN) used to monitor the health status of the wearer for long durations. The paper discusses a prototype WBAN based wearable physiological monitoring system to monitor physiological parameters such as Electrocardiogram (ECG) and Electroencephalogram (EEG) acquired using a textile electrode, Photoplethysmogram (PPG), Galvanic Skin Response (GSR), Blood Pressure derived from analysis of Pulse Transmit Time (PTT) and body temperature. The WBAN consists of three sensor nodes that are placed strategically to acquire the physiological signals and the sensor nodes communicate to a chest/wrist worn sink node also known as wearable data acquisition hardware. The sink node receives physiological data from the sensor nodes and is transmitted to a remote monitoring station. The remote monitoring station receives the raw data and it is processed to remove noises, such as power line interference, baseline wander and tremor in the signals and the information is extracted and displayed. The WBANs are designed using the ZigBee wireless communication modules to transmit and receive the data. At the remote monitoring station the physiological parameters such as heart rate, pulse rate, systolic, diastolic blood pressure, GSR and body temperature are continuously monitored from the wearer. The data acquired from the wearable monitoring system is statically validated using a qualified medical device on 34 subjects. 展开更多
关键词 WPMS WBAN TEXTILE Electrode Sensor NODE physiologICAL signals ZigBee
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Detecting Human Mood from Physiological Signal and Data Usage
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作者 Iftakhar Hossain Tanzila Islam Mohammad Raihan Ruhin 《Journal of Computer and Communications》 2018年第12期15-33,共19页
As the days go by, there are technologies that are being introduced everyday, whether it is a tiny music player iPod nano or a robot “Asimo” that runs 6 kilometers per hour. These technologies entertain, facilitate ... As the days go by, there are technologies that are being introduced everyday, whether it is a tiny music player iPod nano or a robot “Asimo” that runs 6 kilometers per hour. These technologies entertain, facilitate and make the day easier for the human being. It is not arguable anymore that the people need these technologies with the smart systems to lead their regular life smoothly. The smarter the system is;the more people like to use it. One major part of this smartness of the system depends on how well the system can interact with the person or the user. It is not a dream anymore that a system will be able to interact with a human just the way that one human interacts with another. To make that happen, it is obvious that the system must be intelligent enough to understand a human being. For example, if we need a Robot that can have a random conversation with a human, the system must recognize and understand the spoken word to reply the human. And the reply will be based on the current mood and behavior of the human. In this scenario, a human uses his senses to receive the inputs such as voice through the hearing senses, behavior and movement of the body parts, and facial expression through seeing sense from the speaking human. And it is now apparently possible to take such inputs for a system which can be stored as data;later it is possible to analyze the data using various algorithms and also to teach the system through Machine Learning algorithms. We will briefly discuss issues related to the relevance and the possible impact of research in the field of Artificial Intelligence, with special attention to the Computer Vision and Pattern Recognition, Natural Language Processing, Human Computer Interaction, Data Warehouse and Data Mining that is used to identify and analyze data like psychological signals, voice, conversation, geo location, and geo weather, etc. In our research, we have used heart rate that is a successful physiological signal to detect human mood and used smartphone usage data to train the system and detect mood more accurately than other methods. 展开更多
关键词 MOOD Detection Pattern Recognition Euclidian FORMULA physiologICAL signals Machine Learning DATA Mining Natural LANGUAGE
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Physiological signal processing in heart rate variability measurement:A focus on spectral analysis
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作者 Amin Gasmi 《Life Research》 2022年第4期36-45,共10页
Human physiological(biological)systems function in such a way that their complexity requires mathematical analysis.The functioning of the brain,heart and other parts are so complex to be easily comprehended.Under cond... Human physiological(biological)systems function in such a way that their complexity requires mathematical analysis.The functioning of the brain,heart and other parts are so complex to be easily comprehended.Under conditions of rest or work,the temporal distances of successive heartbeats are subject to fluctuations,thereby forming the basis of Heart Rate Variability(HRV).In normal conditions,the human is persistently exposed to highly changing and dynamic situational demands.With these demands in mind,HRV can,therefore,be considered as the human organism’s ability to cope with and adapt to continuous situational requirements,both physiologically and emotionally.Fast Fourier Transform(FFT)is used in various physiological signal processing,such as heart rate variability.FFT allows a spectral analysis of HRV and is great help in HRV analysis and interpretation. 展开更多
关键词 Fast Fourier Transform heart rate variability spectral analysis frequency domain physiological signals processing
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Mood States Recognition of Rowing Athletes Based on Multi-Physiological Signals Using PSO-SVM
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作者 Jing Wang Pei Lei +2 位作者 Kun Wang Lijuan Mao Xinyu Chai 《E-Health Telecommunication Systems and Networks》 2014年第2期9-17,共9页
Athletes have various emotions before competition, and mood states have impact on the competi- tion results. Recognition of athletes’ mood states could help athletes to have better adjustment before competition, whic... Athletes have various emotions before competition, and mood states have impact on the competi- tion results. Recognition of athletes’ mood states could help athletes to have better adjustment before competition, which is significant to competition achievements. In this paper, physiological signals of female rowing athletes in pre- and post-competition were collected. Based on the multi-physiological signals related to pre- and post-competition, such as heart rate and respiration rate, features were extracted which had been subtracted the emotion baseline. Then the particle swarm optimization (PSO) was adopted to optimize the feature selection from the feature set, and combined with the least squares support vector machine (LS-SVM) classifier. Positive mood states and negative mood states were classified by the LS-SVM with PSO feature optimization. The results showed that the classification accuracy by the LS-SVM algorithm combined with PSO and baseline subtraction was better than the condition without baseline subtraction. The combination can contribute to good classification of mood states of rowing athletes, and would be informative to psychological adjustment of athletes. 展开更多
关键词 Affective Computing MOOD States RECOGNITION Multi-physiological signals PSO SVM
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A Preliminary Investigation of Adult Defence Style and Physiological Reactivity to Infant Distress Signals
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作者 Emma L. Gould Tammy Lane Andrew J. Lewis 《Psychology Research》 2011年第6期410-421,共12页
关键词 生理反应 防御方式 遇险信号 婴儿 成人 生物响应 加速度响应 GSR
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基于GA-BLS方法的手势识别研究 被引量:2
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作者 杜义浩 曹添福 +1 位作者 范强 王孝冉 《计量学报》 CSCD 北大核心 2024年第1期121-127,共7页
为进一步提升人机交互领域中手势识别的精度和速度,探究肌肉疲劳对手势识别的影响规律,提出了改进的GA-BLS方法,利用遗传算法(genetic algorithms,GA)优化宽度学习(broad learning system,BLS)模型参数,并使用弹性网络回归改进传统的BL... 为进一步提升人机交互领域中手势识别的精度和速度,探究肌肉疲劳对手势识别的影响规律,提出了改进的GA-BLS方法,利用遗传算法(genetic algorithms,GA)优化宽度学习(broad learning system,BLS)模型参数,并使用弹性网络回归改进传统的BLS模型。利用所提模型对8种手势下的A型超声信号和肌电信号进行手势识别分析,并与SVM、KNN、RF、LDA等方法进行对比,以验证所研究方法的有效性;将长时间段下的A型超声信号和肌电信号切分成4个数据段,发现随着肌肉疲劳程度的增加,手势识别的准确率均呈现出明显下降的趋势,而且A型超声信号相较于肌电信号具有更好的抗疲劳特性。 展开更多
关键词 手势识别 生理信号 遗传算法 宽度学习 肌肉疲劳 弹性网络回归
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基于能量阈值的双参数阈值函数在生理信号降噪中的应用
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作者 赵薇 卓智海 张月霞 《兵工学报》 EI CAS CSCD 北大核心 2024年第4期1264-1272,共9页
针对弱生理信号在采集过程中易被噪声淹没,传统小波去噪算法存在去噪效果差和信号提取失真的问题,根据小波系数的能量分布特点,提出一种改进的小波阈值去噪算法。通过计算各层小波系数的能量来确定阈值,避免阈值计算的不平衡性,同时提... 针对弱生理信号在采集过程中易被噪声淹没,传统小波去噪算法存在去噪效果差和信号提取失真的问题,根据小波系数的能量分布特点,提出一种改进的小波阈值去噪算法。通过计算各层小波系数的能量来确定阈值,避免阈值计算的不平衡性,同时提高自适应性和弱信号的保真度;采用一种改进的可调节的双参数阈值函数对小波系数进行处理,在小波系数压缩程度可控的同时可以自由调节阈值函数的变化趋势。实验结果表明:改进的小波阈值去噪算法相较于两种传统去噪算法(经验模态分解算法和滤波器算法)以及12种传统小波阈值和阈值函数组合算法,在信噪比、均方根百分比和均方根误差上都具有明显的优势,并且在实测生理信号中取得了最小的平均相对误差和最小的波动性。 展开更多
关键词 小波变换 能量梯度阈值 改进阈值函数 生理信号 去噪
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面向睡眠研究的生理信号开源数据集综述
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作者 陆敬怡 颜昌 +2 位作者 于广义 李建清 刘澄玉 《中国生物医学工程学报》 CAS CSCD 北大核心 2024年第3期358-368,共11页
临床多导睡眠数据的采集和标注耗时长且成本高,被测人群、采集设备和标注专家等因素的不同,使得采集的数据存在差异,增加了睡眠相关研究的难度和复杂度。与众多其他临床开源数据资源相同,面向睡眠研究的生理信号开源数据集的建立为全球... 临床多导睡眠数据的采集和标注耗时长且成本高,被测人群、采集设备和标注专家等因素的不同,使得采集的数据存在差异,增加了睡眠相关研究的难度和复杂度。与众多其他临床开源数据资源相同,面向睡眠研究的生理信号开源数据集的建立为全球相关研究者提供了丰富的数据资源和统一的对比平台,促进了睡眠医学领域研究的深入发展。为此,综述了在睡眠领域中常见的18个开源数据集的概况、特点及应用,这些数据集包括脑电图(EEG)、心电图(ECG)、眼电图(EOG)和肌电图(EMG)等生理信号以及涵盖睡眠障碍、心血管疾病和肥胖症等多个临床领域;总结了现有睡眠开源数据集在数据质量、数据标准、数据安全、样本代表性和外部有效性等方面存在的局限,提出了针对性的建议与展望。 展开更多
关键词 多模态生理信号 睡眠 开源数据集 生理测量
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基于生理信号的危险作业人员心理负荷识别研究
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作者 郝锐 郑欣 李怡霖 《东北大学学报(自然科学版)》 EI CAS CSCD 北大核心 2024年第4期600-608,共9页
为识别危险作业岗位作业人员的心理负荷,提高人机系统可靠性,以含能材料起爆作业诱导被试人员心理负荷,采集30名被试人员在静息状态和心理负荷下的心率、脑电图和眼动信号进行心理负荷识别研究.首先,采用配对t检验与秩和检验对采集的心... 为识别危险作业岗位作业人员的心理负荷,提高人机系统可靠性,以含能材料起爆作业诱导被试人员心理负荷,采集30名被试人员在静息状态和心理负荷下的心率、脑电图和眼动信号进行心理负荷识别研究.首先,采用配对t检验与秩和检验对采集的心率、脑电图和眼动信号进行统计分析,8种脑电、3种眼动及9种心率特征在静息状态和心理负荷下具有显著变化;其次,对初选获得的生理指标分别采用Pearson相关分析、最大相关最小冗余(MRMR)算法和主成分分析(PCA)进行特征降维;最后,基于上述3种方法降维处理后得到生理指标采用Logistic Regression,KNN,SVM,XG-Boost,Decision Tree和Random Forest机器学习方法进行心理负荷识别.结果表明,基于MRMR的心理负荷特征选择结果,采用Random Forest机器学习方法具有更好的识别性能(ACC=0.917,SN=1.0,SP=0.857,F1=0.909,AUC=0.971).本研究为有效识别危险作业人员心理负荷提供了理论依据. 展开更多
关键词 危险作业 心理负荷识别 生理信号 机器学习
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生理性拉应力通过Nell-1/Ihh信号通路对ATDC5软骨细胞分化的调控作用
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作者 董紫薇 齐慧川 +4 位作者 马俊 薛晴 聂瑾涵 于航 胡敏 《吉林大学学报(医学版)》 CAS CSCD 北大核心 2024年第1期1-9,共9页
目的:探讨生理性拉应力对软骨细胞分化的调控作用,并阐明其相关信号通路机制。方法:体外培养软骨ATDC5细胞,应用四点弯曲细胞力学加载仪对其施加生理性拉应力,首先分为对照组和拉应力组(2 000μstrain/2 h组),另分为不同力值(1 000、2 ... 目的:探讨生理性拉应力对软骨细胞分化的调控作用,并阐明其相关信号通路机制。方法:体外培养软骨ATDC5细胞,应用四点弯曲细胞力学加载仪对其施加生理性拉应力,首先分为对照组和拉应力组(2 000μstrain/2 h组),另分为不同力值(1 000、2 000和3 000μstrain)加力时间为2 h和力值为2 000μstrain不同加力时间(1、2和4 h)组,同时设未加力的细胞为对照组,采用实时荧光定量PCR (RT-qPCR)法检测各组细胞中Ⅱ型胶原(Col-Ⅱ)、Ⅹ型胶原(Col-Ⅹ)、聚集蛋白聚糖(Aggrecan)、性别决定区Y框蛋白9 (SOX9)、血管内皮生长因子(VEGF)、增殖细胞核抗原(PCNA)、Nel样1型分子(Nell-1)、Runt相关转录因子2 (Runx2)、印度刺猬因子(Ihh)、补缀同源物1 (Ptch-1)、GLI家族锌指蛋白1 (Gli-1)和刺猬因子相互作用蛋白1 (Hhip-1) mRNA表达水平,采用Western blotting法检测各组细胞中Nell-1、Runx2和Ihh蛋白表达水平。ATDC5细胞分为对照组、环巴胺组、拉应力组和环巴胺+拉应力组,采用RT-qPCR法检测各组细胞中Nell-1、Ihh、Ptch-1、Gli-1和Hhip-1 mRNA表达水平,采用Western blotting法检测各组细胞中Nell-1和Ihh蛋白表达水平。结果:与对照组比较,2 000μstrain/2 h组细胞中Col-Ⅱ、 Col-Ⅹ、 Aggrecan、 SOX9、VEGF和PCNA mRNA表达水平均明显升高(P<0.01)。在对细胞施加2 000μstrain不同加力时间(1、2和4 h)或不同力值(1 000、2 000和3 000μstrain) 2 h的拉应力后,与对照组比较,随时间的延长或力值的增加其他各组细胞中Runx2 mRNA表达水平逐渐升高(P<0.01),Nell-1、Ihh、 Ptch-1、 Gli-1和Hhip-1 mRNA表达水平逐渐升高(P<0.01),且在2 000μstrain/2 h时达到最高,随后出现回落但仍明显高于对照组(P<0.01)。Western blotting检测,各组细胞中Nell-1、Runx2和Ihh蛋白表达水平与mRNA表达水平变化趋势一致。环巴胺预处理后,与对照组比较,环巴胺组细胞中Ihh、Ptch-1、Gli-1和Hhip-1 mRNA表达水平均明显降低(P<0.01),拉应力组和环巴胺+拉应力组细胞中Nell-1、Ihh、Ptch-1、Gli-1和Hhip-1 mRNA表达水平明显升高(P<0.01);与环巴胺组比较,环巴胺+拉应力组细胞中Nell-1、Ihh、Ptch-1、Gli-1和Hhip-1 mRNA表达水平明显升高(P<0.01);与拉应力组比较,环巴胺+拉应力组细胞中Ihh、Ptch-1、Gli-1和Hhip-1 mRNA表达水平明显降低(P<0.01)。与对照组比较,环巴胺组细胞中Ihh蛋白表达水平明显降低(P<0.01),Nell-1蛋白表达水平差异无统计学意义(P>0.05),拉应力组和环巴胺+拉应力组细胞中Nell-1和Ihh蛋白表达水平明显升高(P<0.01);与环巴胺组比较,拉应力组和环巴胺+拉应力组细胞中Nell-1和Ihh蛋白表达水平明显升高(P<0.01);与拉应力组比较,环巴胺+拉应力组细胞中Nell-1和Ihh蛋白表达水平差异均无统计学意义(P>0.05)。结论:在生理性拉应力刺激下,Nell-1可在上游激活Ihh信号通路,进而调控ATDC5软骨细胞的分化。 展开更多
关键词 生理性拉应力 软骨细胞 Nel样1型分子 印度刺猬因子信号通路 Runt相关转录因子2
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基于嗅觉和听觉刺激的驾驶员疲劳唤醒方法研究
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作者 朱明鑫 唐帮备 +4 位作者 胡志安 何超 陈昊 陈胜男 曾启航 《汽车工程学报》 2024年第3期404-411,共8页
针对驾驶员在疲劳状态下易引发交通事故的问题,提出一种基于嗅觉和听觉刺激的驾驶员疲劳唤醒方法,研究以薄荷气体和阿尔法脑波音乐作为刺激源的唤醒效果,采用主观疲劳问卷和心电(ECG)、脉搏(PPG)以及呼吸(RESP)生理信号作为疲劳唤醒有... 针对驾驶员在疲劳状态下易引发交通事故的问题,提出一种基于嗅觉和听觉刺激的驾驶员疲劳唤醒方法,研究以薄荷气体和阿尔法脑波音乐作为刺激源的唤醒效果,采用主观疲劳问卷和心电(ECG)、脉搏(PPG)以及呼吸(RESP)生理信号作为疲劳唤醒有效性判断指标。结果表明,两种方案的心电、脉搏以及呼吸生理数据均显示能有效干预驾驶疲劳,与主观疲劳问卷调查结果相一致,验证了基于嗅觉和听觉刺激的驾驶员疲劳唤醒方法的有效性,且基于听觉刺激的唤醒方案唤醒效果更佳。 展开更多
关键词 疲劳驾驶 脑波音乐 薄荷气味 生理信号 疲劳唤醒
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基于生理信号的PAD多维情感预测方法研究
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作者 何佳乐 张建敏 《软件工程》 2024年第6期48-52,共5页
针对人机交互中用户认知模糊与表达不准确等问题,提出一种基于生理信号的PAD(Pleasure,Arousal,Dominance)多维情感预测方法对用户情感进行预测。首先,确定眼动信号指标和PAD情感量表,以门户网站为实验样本开展情感测量实验,被试者需按... 针对人机交互中用户认知模糊与表达不准确等问题,提出一种基于生理信号的PAD(Pleasure,Arousal,Dominance)多维情感预测方法对用户情感进行预测。首先,确定眼动信号指标和PAD情感量表,以门户网站为实验样本开展情感测量实验,被试者需按要求完成浏览任务,并记录眼动数据。其次,通过PAD情感量表获取被试者在网页界面中的多维情感值。最后,利用偏最小二乘回归法建立关系模型,探索眼动数据与PAD多维情感值之间的关系,并验证模型的有效性和适用性。研究结果表明,该情感预测模型的Sig.值均大于0.05,具有较高的预测能力,能准确预测用户对网页界面的情感偏好。 展开更多
关键词 生理信号 PAD情感 偏最小二乘回归 情感预测
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基于对比学习的心电信号情绪识别方法
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作者 龙锦益 方景龙 +2 位作者 刘斯为 吴汉瑞 张佳 《计算机应用研究》 CSCD 北大核心 2024年第4期1123-1130,共8页
现有的机器学习和深度学习在解决基于心电信号的情绪识别问题时主要使用全监督的学习方法。这种方法的缺点在于需要大量的有标签数据和计算资源。同时,全监督方法学习到的特征表示通常只能针对特定任务,泛化性较差。针对这些问题,提出... 现有的机器学习和深度学习在解决基于心电信号的情绪识别问题时主要使用全监督的学习方法。这种方法的缺点在于需要大量的有标签数据和计算资源。同时,全监督方法学习到的特征表示通常只能针对特定任务,泛化性较差。针对这些问题,提出了一种基于对比学习的心电信号情绪识别方法,该方法分为预训练和微调两步。预训练的目的是从未标记的心电数据中学习特征表示,具体为:设计了两种简单高效的心电信号增强方式,将原始数据通过这两种数据增强转换成两个相关但不同的视图;接着这两种视图在时间对比模块中学习鲁棒的时间特征表示;最后在上下文对比模块中学习具有判别性的特征表示。微调阶段则使用带标记数据来学习情绪识别任务。在三个公开数据集上的实验表明,该方法在心电信号情绪识别准确率上与现有方法相比提高了0.21%~3.81%。此外,模型在半监督设定场景中表现出高有效性。 展开更多
关键词 心电信号 情绪识别 对比学习 自监督学习 深度学习 生理信号 数据增强 自注意力机制
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生理信号监测在飞行员抗荷能力训练中的应用
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作者 秦聪聪 李心航 +2 位作者 李曦 王永春 李卓 《空军军医大学学报》 CAS 2024年第2期216-220,共5页
飞行员在驾驶高性能战斗机时常常受到持续高加速度负载,这对飞行员抗荷能力要求较高,飞行员必须经过系统的抗荷能力训练以应对这一负荷,抗荷能力不足极易发生黑视或意识丧失,威胁飞行员生命安全。抗荷训练是飞行人员的必修科目,随着各... 飞行员在驾驶高性能战斗机时常常受到持续高加速度负载,这对飞行员抗荷能力要求较高,飞行员必须经过系统的抗荷能力训练以应对这一负荷,抗荷能力不足极易发生黑视或意识丧失,威胁飞行员生命安全。抗荷训练是飞行人员的必修科目,随着各种无创生理监测设备的应用,对飞行员抗荷训练进行医务监督,对提高训练效果、预防损伤等有重要指导意义。本文将以飞行员抗荷训练为背景,解读心率、血压、血氧、呼吸机能、肌电肌力等生理参数在抗荷训练过程中的意义,对医务监督和抗荷训练的具体应用、未来发展及目前存在的问题进行梳理,旨在为飞行员科学高效的抗荷训练提供理论依据,为抗荷训练及飞行员生理变化等相关研究提供参考。 展开更多
关键词 抗荷训练 抗荷动作 飞行员 医务监督 生理信号
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基于KDCCA的脑电信号辅助外周信号的情感识别研究
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作者 赵文萍 《自动化应用》 2024年第10期160-164,共5页
多信号融合是生理信号情感识别中的重点,其中,生理信号和脑电信号(EEG)被广泛使用。但EEG信号获取困难、成本高,为更有效地使用EEG信号,提出了一种基于核化的判别型典型相关分析(KDCCA)的脑电信号辅助生理信号的情感分类方法。训练时先... 多信号融合是生理信号情感识别中的重点,其中,生理信号和脑电信号(EEG)被广泛使用。但EEG信号获取困难、成本高,为更有效地使用EEG信号,提出了一种基于核化的判别型典型相关分析(KDCCA)的脑电信号辅助生理信号的情感分类方法。训练时先提取各种信号,在EEG信号的辅助下使用KDCCA创建新的判别空间,然后采用多种机器学习方法构建情感模型,最后在测试时只使用EEG信号。经实验验证,所提方法取得了更好的分类效果。 展开更多
关键词 情感识别 生理信号 脑电信号
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不同热环境下佩戴医用外科口罩对人体舒适性的影响研究
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作者 杨亚龙 杨畅 张睿 《安徽建筑大学学报》 2024年第2期33-39,48,共8页
为研究医用外科口罩在不同温度下对人体热舒适和呼吸舒适的影响,设计了包括三种温度以及三种不同活动水平的实验工况。总计15名受试者构成了佩戴医用外科口罩的实验组和不佩戴医用外科口罩的对照组,并完成热舒适投票(TCV)、热感觉投票(T... 为研究医用外科口罩在不同温度下对人体热舒适和呼吸舒适的影响,设计了包括三种温度以及三种不同活动水平的实验工况。总计15名受试者构成了佩戴医用外科口罩的实验组和不佩戴医用外科口罩的对照组,并完成热舒适投票(TCV)、热感觉投票(TSV)和呼吸舒适投票(BCV),采集其心电图(ECG)以分析心率变异性(HRV)。结果表明,短时间佩戴医用外科口罩对人体整体热感觉没有影响;在热舒适环境下,医用外科口罩对热舒适的影响显著,而热不适环境下,温度对热舒适的影响较大;医用外科口罩影响呼吸舒适,站立时佩戴医用外科口罩增加了呼吸不适的温度范围;HRV频域分析指标LF/HF通常可作为评价热感觉的指标,但佩戴医用外科口罩后HRV与热感觉无相关性。 展开更多
关键词 热环境 热舒适 HRV 医用外科口罩 生理信号
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Salt tolerance in rice:Physiological responses and molecular mechanisms 被引量:14
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作者 Citao Liu Bigang Mao +2 位作者 Dingyang Yuan Chengcai Chu Meijuan Duan 《The Crop Journal》 SCIE CSCD 2022年第1期13-25,共13页
Crop yield loss due to soil salinization is an increasing threat to agriculture worldwide.Salt stress drastically affects the growth,development,and grain productivity of rice(Oryza sativa L.),and the improvement of r... Crop yield loss due to soil salinization is an increasing threat to agriculture worldwide.Salt stress drastically affects the growth,development,and grain productivity of rice(Oryza sativa L.),and the improvement of rice tolerance to salt stress is a desirable approach for meeting increasing food demand.The main contributors to salt toxicity at a global scale are Na^(+)and Cl^(-)ions,which affect up to 50%of irrigated soils.Plant responses to salt stress occur at the organismic,cellular,and molecular levels and are pleiotropic,involving(1)maintenance of ionic homeostasis,(2)osmotic adjustment,(3)ROS scavenging,and(4)nutritional balance.In this review,we discuss recent research progress on these four aspects of plant physiological response,with particular attention to hormonal and gene expression regulation and salt tolerance signaling pathways in rice.The information summarized here will be useful for accelerating the breeding of salt-tolerant rice. 展开更多
关键词 Salt stress Rice(Oryza sativa L.) Salt tolerance genes physiological response Salt signal transduction
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