Fusing Near-Infrared Spectroscopy with Wearable Hemodynamic Measurements Improves Classification of Mental Stress.
Fusing Near-Infrared Spectroscopy with Wearable Hemodynamic Measurements Improves Classification of Mental Stress.
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DOI：
10.1109/jsen.2018.2872651
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发表时间：
2019-10-01
影响因子：
4.3
通讯作者：
Inan OT
中科院分区：
文献类型：
--
作者：
Gurel NZ;Jung H;Hersek S;Inan OT
人机交互（HCI）技术和对人的精神状态的自动分类受到多个行业的关注。在这项工作中，融合的传感模式，监测人类前额叶皮层（PFC）和心血管生理的氧合进行了评估，以区分休息，心算和N-back记忆任务。设计了一种柔性头带，用于测量近红外光谱（NIRS）以量化PFC氧合，以及用于评估外周心血管活动的前额光电体积描记（PPG）。收集生理信号，如心电图（ECG）和心震图（SCG），沿着使用头带获得的测量结果。该设置进行了测试和验证，共有16名人类受试者执行一系列算术和N-back记忆任务。提取的特征与心脏和外周交感神经活动、血管紧张度、脉搏波传播和氧合有关。利用机器学习技术对休息、算术和N-back任务进行分类，使用留一主题交叉验证。从三种状态的分类中获得的宏观平均准确率为85%，精确率为84%，召回率为83%，F1得分为80%。对基于受试者的结果进行的统计分析表明，与单独使用NIRS传感相比，NIRS和外周心血管传感的融合显著提高了准确度、精确度、召回率和F1评分。此外，与单独的外周心血管感测相比，融合显著提高了精度。这项工作的结果可以在未来用于设计一个多模式的可穿戴传感系统，用于分类的应用，如急性压力检测的精神状态。
Human-computer interaction (HCI) technology, and the automatic classification of a person’s mental state, are of interest to multiple industries. In this work, the fusion of sensing modalities that monitor the oxygenation of the human prefrontal cortex (PFC) and cardiovascular physiology was evaluated to differentiate between rest, mental arithmetic and N-back memory tasks. A flexible headband to measure near-infrared spectroscopy (NIRS) for quantifying PFC oxygenation, and forehead photoplethysmography (PPG) for assessing peripheral cardiovascular activity was designed. Physiological signals such as the electrocardiogram (ECG) and seismocardiogram (SCG) were collected, along with the measurements obtained using the headband. The setup was tested and validated with a total of 16 human subjects performing a series of arithmetic and N-back memory tasks. Features extracted were related to cardiac and peripheral sympathetic activity, vasomotor tone, pulse wave propagation, and oxygenation. Machine learning techniques were utilized to classify rest, arithmetic, and N-back tasks, using leave-one-subject-out cross validation. Macro-averaged accuracy of 85%, precision of 84%, recall rate of 83%, and F1 score of 80% were obtained from the classification of the three states. Statistical analyses on the subject-based results demonstrate that the fusion of NIRS and peripheral cardiovascular sensing significantly improves the accuracy, precision, recall, and F1 scores, compared to using NIRS sensing alone. Moreover, the fusion significantly improves the precision compared to peripheral cardiovascular sensing alone. The results of this work can be used in the future to design a multi-modal wearable sensing system for classifying mental state for applications such as acute stress detection.
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影响因子：
4.3
作者：
Blankertz B;Tangermann M;Vidaurre C;Fazli S;Sannelli C;Haufe S;Maeder C;Ramsey L;Sturm I;Curio G;Müller KR
通讯作者：
Müller KR
影响因子：
3.7
作者：
Kelsey, Robert M.;Ornduff, Sidney R.;Alpert, Bruce S.
通讯作者：
Alpert, Bruce S.
影响因子：
3.2
作者：
Charlton, Peter H.;Celka, Patrick;Alastruey, Jordi
通讯作者：
Alastruey, Jordi
DOI：
10.1016/j.cortex.2012.05.022
发表时间：
2013-05
期刊：
Cortex; a journal devoted to the study of the nervous system and behavior
影响因子：
--
作者：
Barbey AK;Koenigs M;Grafman J
通讯作者：
Grafman J
影响因子：
3.7
作者：
Goedhart, Annebet D.;Willemsen, G.;De Geus, Eco J. C.
通讯作者：
De Geus, Eco J. C.