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1.
Sensors (Basel) ; 22(12)2022 Jun 10.
Article in English | MEDLINE | ID: mdl-35746182

ABSTRACT

As vehicles provide various services to drivers, research on driver emotion recognition has been expanding. However, current driver emotion datasets are limited by inconsistencies in collected data and inferred emotional state annotations by others. To overcome this limitation, we propose a data collection system that collects multimodal datasets during real-world driving. The proposed system includes a self-reportable HMI application into which a driver directly inputs their current emotion state. Data collection was completed without any accidents for over 122 h of real-world driving using the system, which also considers the minimization of behavioral and cognitive disturbances. To demonstrate the validity of our collected dataset, we also provide case studies for statistical analysis, driver face detection, and personalized driver emotion recognition. The proposed data collection system enables the construction of reliable large-scale datasets on real-world driving and facilitates research on driver emotion recognition. The proposed system is avaliable on GitHub.


Subject(s)
Automobile Driving , Accidents, Traffic/prevention & control , Automobile Driving/psychology , Data Collection , Emotions
2.
Sensors (Basel) ; 21(6)2021 Mar 19.
Article in English | MEDLINE | ID: mdl-33808922

ABSTRACT

In intelligent vehicles, it is essential to monitor the driver's condition; however, recognizing the driver's emotional state is one of the most challenging and important tasks. Most previous studies focused on facial expression recognition to monitor the driver's emotional state. However, while driving, many factors are preventing the drivers from revealing the emotions on their faces. To address this problem, we propose a deep learning-based driver's real emotion recognizer (DRER), which is a deep learning-based algorithm to recognize the drivers' real emotions that cannot be completely identified based on their facial expressions. The proposed algorithm comprises of two models: (i) facial expression recognition model, which refers to the state-of-the-art convolutional neural network structure; and (ii) sensor fusion emotion recognition model, which fuses the recognized state of facial expressions with electrodermal activity, a bio-physiological signal representing electrical characteristics of the skin, in recognizing even the driver's real emotional state. Hence, we categorized the driver's emotion and conducted human-in-the-loop experiments to acquire the data. Experimental results show that the proposed fusing approach achieves 114% increase in accuracy compared to using only the facial expressions and 146% increase in accuracy compare to using only the electrodermal activity. In conclusion, our proposed method achieves 86.8% recognition accuracy in recognizing the driver's induced emotion while driving situation.


Subject(s)
Automobile Driving , Deep Learning , Emotions , Facial Expression , Humans , Neural Networks, Computer
3.
J Clin Ultrasound ; 48(2): 89-96, 2020 Feb.
Article in English | MEDLINE | ID: mdl-31609460

ABSTRACT

PURPOSE: To evaluate the prenatal sonographic predictive markers of the outcome in fetuses with bronchopulmonary sequestration (BPS). METHODS: BPS size and diameter of the feeding artery (FA) were measured prenatally and postnatally. Velocity of the FA and the left ventricular-modified myocardial performance index (LV mod-MPI) were also evaluated prenatally. RESULTS: Forty-seven women were included in the study. Mean gestational age, mass size, diameter and velocity of the FA, and LV mod-MPI at prenatal diagnosis were 23.5 ± 2.2 weeks, 3.6 ± 8.3 cm, 2.3 ± 0.6 mm, 46.6 ± 15.4 cm/s, and 0.46 ± 0.06, respectively. Mean mass diameter and FA diameter measured on postnatal CT examinations were 3.8 ± 1.0 cm and 2.3 ± 0.7 mm, respectively. Five patients had respiratory symptoms after birth. Twenty children (43%) underwent or were scheduled to undergo mass excision, and the remaining 27 (57%) were doing well without any intervention. There was no neonatal death. LV mod-MPI at diagnosis, the FA diameter after birth and the serial change in the FA size were significantly associated with postnatal mass excision. CONCLUSION: The FA diameter and LV mod-MPI may be additional markers for predicting whether fetuses with BPS should undergo mass excision in early childhood or conservative care.


Subject(s)
Bronchopulmonary Sequestration/diagnostic imaging , Bronchopulmonary Sequestration/embryology , Ultrasonography, Prenatal/methods , Adult , Female , Humans , Pregnancy
4.
Obstet Gynecol Sci ; 61(3): 417-420, 2018 May.
Article in English | MEDLINE | ID: mdl-29780786

ABSTRACT

The ex utero intrapartum treatment (EXIT) procedure was introduced to reduce fetal hypoxic damage while establishing an airway in fetuses with upper and lower airway obstruction. Delivery of the fetal head and shoulders while maintaining the uteroplacental circulation offers time to secure the fetal airway. Here, we report two cases of EXIT procedure for fetal airway obstruction, which were successfully managed with extensive preoperative planning by a professional multidisciplinary team.

5.
Acute Crit Care ; 33(4): 238-245, 2018 Nov.
Article in English | MEDLINE | ID: mdl-31723891

ABSTRACT

BACKGROUND: Infection by multidrug-resistant (MDR) pathogens leads to poor patient outcomes in intensive care units (ICUs). Contact precautions are necessary to reduce the transmission of MDR pathogens. However, the importance of the surrounding environment is not well known. We studied the effects of ICU relocation on MDR respiratory pathogen detection rates and patient outcomes. METHODS: Patients admitted to the ICU before and after the relocation were retrospectively analyzed. Baseline patient characteristics, types of respiratory pathogens detected, antibiotics used, and patient outcomes were measured. RESULTS: A total of 463 adult patients admitted to the ICU, 4 months before and after the relocation, were included. Of them, 234 were admitted to the ICU before the relocation and 229 afterward. Baseline characteristics, including age, sex, and underlying comorbidities, did not differ between the two groups. After the relocation, the incidence rate of MDR respiratory pathogen detection decreased from 90.0 to 68.8 cases per 1,000 patient-days, but that difference was statistically insignificant. The use of colistin was significantly reduced from 53.5 days (95% confidence interval [CI], 20.3 to 86.7 days) to 18.7 days (95% CI, 5.6 to 31.7 days). Furthermore, the duration of hospital stay was significantly reduced from a median of 29 days (interquartile range [IQR], 14 to 50 days) to 21 days (IQR, 11 to 39 days). CONCLUSIONS: Incidence rates of MDR respiratory pathogen detection were not significantly different before and after ICU relocation. However, ICU relocation could be helpful in reducing the use of antibiotics against MDR pathogens and improving patient outcomes.

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