• 제어로봇시스템학회논문지
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• 제8권12호
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• pp.1061-1065
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• 2002

Sensors need to be implanted to obtain necessary information for LVAS (Left Ventricular Assist System) operations. Size of the sensors can prevent them from being implanted in a patient and reliabilities of the sensors are questionable for a long term use. In this wort we utilize a developed pump model to estimate flow and pressure difference across the pump without implanted sensors and present a method to obtain the physiological variables as aorta pressure and left ventricle pressure from the pump model and pulsatility of flow estimate or pressure difference estimate. These estimated variables can be used for LVAS control as an index or indices.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권3호
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• pp.1076-1094
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• 2022

Technology for emotion recognition is an essential part of human personality analysis. To define human personality characteristics, the existing method used the survey method. However, there are many cases where communication cannot make without considering emotions. Hence, emotional recognition technology is an essential element for communication but has also been adopted in many other fields. A person's emotions are revealed in various ways, typically including facial, speech, and biometric responses. Therefore, various methods can recognize emotions, e.g., images, voice signals, and physiological signals. Physiological signals are measured with biological sensors and analyzed to identify emotions. This study employed two sensor types. First, the existing method, the binary arousal-valence method, was subdivided into four levels to classify emotions in more detail. Then, based on the current techniques classified as High/Low, the model was further subdivided into multi-levels. Finally, signal characteristics were extracted using a 1-D Convolution Neural Network (CNN) and classified sixteen feelings. Although CNN was used to learn images in 2D, sensor data in 1D was used as the input in this paper. Finally, the proposed emotional recognition system was evaluated by measuring actual sensors.

• 한국멀티미디어학회논문지
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• 제23권9호
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• pp.1147-1154
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• 2020

Nowadays, one of the most common diseases is chronic mental fatigue syndrome. This can be caused by many factors, such as busy life, heavy workload, high population density, and adverse technological impact. Most office workers and students who are sitting all day long while being exposed to this kind of environments are likely to be involved in the mental illness. Therefore, to prevent the illness, it has been highly required to design a device that enables mental fatigue to be monitored continuously without human intervention. This paper proposes a linear regression method to reliably estimating the level of human mental fatigue using wearable physiological sensors, with an estimation error of 0.852. Also, this paper presents an Android application that is able to check mental health conditions in daily life.

• 융합신호처리학회논문지
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• 제20권1호
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• pp.9-15
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• 2019

As the human population increases in the world, the ratio of health doctors is rapidly decreasing. Therefore, it is an urgent need to create new technologies to monitor the physical and mental health of people during their daily life. In particular, negative mental states like depression and anxiety are big problems in modern societies. Usually this happens due to stressful situations during everyday activities including work. This paper presents a machine learning approach to reliably estimating the level of human mental stress using wearable physiological sensors. And also, this paper presents an Android- and Arduino-based stress monitoring and relief system.

• 전기학회논문지P
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• 제58권4호
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• pp.619-622
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• 2009

Multi Cultivation Remote-control System(MCRS) for crpos through characteristics of multi-safe sensors was realized. It was carried out to investigate into the effect of LED Control with the physiological activity of crops(for examples, sprouts). We have also composed a Combined Automatic Control System possible for the control of temperature and humidity at the same time. The applied multi-safe sensors for measurement are blue, green, red, white, yellow leds and humidity sensors, web camera sensors under safe conditions for crops cultivation. And we producted the remote control OS using Linux and defined the characteristics of automatic control about sprouts.

• 정보처리학회논문지B
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• 제14B권2호
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• pp.119-126
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• 2007

가상환경에서 학습 방식에 따른 학습 효과를 학습자의 주의와 기억량 분석을 중심으로 연구하였다. 교안유도 방식(Guided learning)과 고안 비유도 방식(Unguided learning)의 학습이 주어진 상태에서 뇌파, 심전도, 피부저항과 시선추적 생체신호장비를 사용하여 학습자 주의측정을 하였고, 학습자의 학습태도, 느낌, 기억량 등을 실험시 비디오와 실험 후 설문분석을 이용하여 분석하였다. 실험 결과는 교안유도 방식이 학습자의 주의를 교안으로 끄는 데는 효율적이어서 많은 교안내용을 기억하게 했으나, 교안비유도 방식에 비해 상대적으로 학습자가 느끼는 체감 흥미는 떨어진 것으로 나타났다. 그와는 대조적으로 교안비유도 방식에서 학습자들은 교안과 교안외 내용을 모두 비교적 광범위하게 기억하고 있었고, 능동적이며 자율적인 학습을 하였다. 또한 교안비유도 후 교안유도 방식의 학슬을 했을 경우 그 반대의 경우보다 훨씬 더 학습호과가 좋았다. 이는 교안비유도 방식이 사전 예비학습 효과를 주었기 때문으로 해석된다. 실험결과를 통해 본 논문에서는 교안비유도 방식을 먼저 학습한 후에 교안유도방식으로 학습을 진행하는 것이 학습자의 학습 효과와 체감흥미에서 더욱 효율적임을 제시하였다.

• 국제학술발표논문집
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• The 9th International Conference on Construction Engineering and Project Management
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• pp.760-767
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• 2022

This paper introduces alert fatigue and presents methods to measure alert fatigue by using physiological signals. Alert fatigue is a phenomenon that which an individual is constantly exposed to frequent alarms and becomes desensitized to them. Blind spots are one leading cause of struck-by accidents, which is one most common causes of fatal accidents on construction sites. To reduce such accidents, construction equipment is equipped with an alarm system. However, the frequent alarm is inevitable due to the dynamic nature of construction sites and the situation can lead to alert fatigue. This paper introduces alert fatigue and proposes methods to use physiological signals such as electroencephalography, electrodermal activity, and event-related potential for the measurement of alert fatigue. Specifically, this paper presents how raw data from the physiological sensors measuring such signals can be processed to measure alert fatigue. By comparing the processed physiological data to behavioral data, validity of the measurement is tested. Using preliminary experimental results, this paper validates that physiological signals can be useful to measure alert fatigue. The findings of this study can contribute to investigating alert fatigue, which will lead to lowering the struck-by accidents caused by blind spots.

• 전자공학회논문지B
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• 제31B권8호
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• pp.172-180
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• 1994

Implantable biotelemetry systems are indispensable tools not only in animal research but also in clinical medicine as such systems enable the acquisition of otherwise unavailable physiological data. We present the manufacture of CMOS IC and its system for implantable multichannel biotelemeter system. The internal circuits of this system are designed not only to achieve as multiple functions and low power dissipation as possible but also to enable continuous measurement of physiological data. Its main functions are to enable continuous measurement of physiological data and to accomplish on-off power swiching of an implantable battery by receiving appropriate commanc signals from an external circuit. The implantable circuits of this system are designed and fabricated on a single silicon chip using $1.5\mu$m n-well CMOS process technology. The total power dissipation of implantable circuits for a continuous operation was 6.7mW and for a stand-by operation was 15.2$\mu$ W. This system used together with approriate sensors is expected to contribute to clinical medicine telemetry system of measuring and wireless transmitting such significant physiological parameters as pressure pH and temperature.

• 센서학회지
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• 제31권5호
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• pp.293-300
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• 2022

Flexible, wearable, and implantable electronic sensors have started to gain popularity in improving the quality of life of sick and healthy people, shifting the future paradigm with high sensitivity. However, conventional technologies with a limited lifespan occasionally limit their continued usage, resulting in a high cost. In addition, traditional battery technologies with a short lifespan frequently limit operation, resulting in a substantial challenge to their growth. Subsequently, utilizing human biomechanical energy is extensively preferred motion for biologically integrated, self-powered, functioning devices. Ideally suited for this purpose are piezoelectric energy harvesters. To convert mechanical energy into electrical energy, devices must be mechanically flexible and stretchable to implant or attach to the highly deformable tissues of the body. A systematic analysis of piezoelectric nanogenerators (PENGs) for personalized healthcare is provided in this article. This article briefly overviews PENGs as self-powered sensor devices for energy harvesting, sensing, physiological motion, and healthcare.

• Journal of Electrical Engineering and Technology
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• 제9권1호
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• pp.324-333
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• 2014

In this study, physiological status of locomotive engineers were measured through EEG, ECG, EDA, PPG and respiration signals from 6 subjects to evaluate their arousal status during train operating. Existence of tunnels and mechanical vibration of train using 3-axes acceleration sensors were recorded simultaneously and were correlated with operator's physiological status. As the result of the analyzed subjects' physiological signals, mean SCR was increased in the section where more body movement is required. The RR interval was decreased before and after train stop due to the higher level of mental tension. The intensity of beta wave of EEG was found to be higher before and after train stop and tunnel section due to the increased mental arousal and tension. Therefore, it is expected that the outcomes of the physiological signals explored in this study can be utilized as the quantitative assessment methods for the arousal status to be used for sleepiness prevention system for vehicles operators which can greatly contribute to public transportation system safety.