Miran Lee

Miran Lee
Daegu University · Department of Computer and Information Engineering

Doctor of Engineering

About

23
Publications
2,775
Reads
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169
Citations
Introduction
Miran Lee is the Postdoctoral Researcher, and currently works at the Department of Precision Engineering, The University of Tokyo. Miran does research in Bio-signal processing (EEC, ECG, EMG, and EOG), Pattern recognition, Human-Robot Interaction, Robotic Mood Transition, Pain Expression, and Sports Medicine. Personal Homepage: https://sites.google.com/view/miran-page/home
Additional affiliations
October 2021 - October 2021
The University of Tokyo
Position
  • PostDoc Position
June 2016 - March 2018
Korea Institute of Science and Technology
Position
  • Researcher
Education
September 2018 - September 2021
Ritsumeikan University
Field of study
  • Graduate School of Information Science and Engineering
March 2014 - February 2016
Inha University
Field of study
  • Electronic Engineering

Publications

Publications (23)
Article
Full-text available
With the development of the portable electrocardiogram (ECG) sensor, R peaks can be monitored during various physical activities in mobile environment. However, such ECG signals contain real-world noise, complicating the accurate detection of R peak. In this paper, we propose a novel approach for R peak detection in ECG signals with real-world nois...
Article
An automatic heartbeat classification method using electrocardiogram is important in assisting doctors and experts with the diagnosis of cardiac diseases. In this study, we introduce a novel algorithm based on a local transform pattern (LTP) with a hybrid neural fuzzy-logic system with a self-organizing map (NF). We extracted a histogram feature wi...
Article
Full-text available
As the elderly population increases, the importance of the caregiver's role in the quality of life of the elderly has increased. To achieve effective feedback in terms of care and nursing education, it is important to design a robot that can express emotions or feel pain like an actual human through visual-based feedback. This study proposes a care...
Article
Full-text available
R-peakdetection and heartbeat recognition methods are important techniques used to diagnose cardiac diseases. We introduce novel approaches for R-peak detection and heartbeat recognition based on the local binary pattern (1DLBP). The proposed R-peak detection method is based on the modified 1DLBP with an adaptive threshold (1DLBPAT). In addition, t...
Article
This study aims to propose a novel approach for gender recognition using best feature subset based on recursive feature elimination (RFE) in normal walking. This study has focused on the analysis of gait characteristics by distinguishing the gait phases as initial contact (IC), Mid-stance (MS), Pre-swing, and swing (SW), and collected the large num...
Conference Paper
A human patient simulator (HPS) can achieve effective visual-, auditory-, text-, and alarm-based feedback methods in care or nursing education. Among these, the method of visual feedback is important to design an HPS that can express emotions or feelings of pain like an actual human does because this method allows an immediate reaction between robo...
Conference Paper
This paper proposes the system of a care training assistant robot (CaTARo) with 3D facial pain expression for improving the care skills in elderly care education. To ensure accurate and efficient elderly care training, this study focuses on the development of a care training assessment method based on fuzzy-logic for calculating the pain level for...
Conference Paper
Full-text available
This paper aims to propose a novel approach for gait phase recognition using an optimal feature subset based on recursive feature elimination. This study has collected a large number of gait data to improve the reliability of quantitative assessment of natural variability associated with muscle activity during free walking. The gait system was desi...
Conference Paper
With the recent expansion of the geriatric population , caregivers and therapists have become increasingly important for improving the quality of life of elderly persons; therefore, having properly trained professionals in these fields is critical. To ensure accurate and efficient elderly care training, this study focuses on the development of an a...
Patent
Full-text available
An Internet - of - things ( IoT ) -based impact pattern analysis system for a smart security window includes : an ultra - small IoT device attached to a security window and detecting an impact ; a station processing a signal obtained from the ultra - small IoT device and analyzing an impact pattern ; and a user terminal outputting information relat...
Article
Full-text available
As the geriatric population expands, caregivers require more accurate training to handle and care for the elderly. However, students lack methods for acquiring the necessary skill and experience, as well as sufcient opportunities to practice on real human beings. To investigate the necessity and feasibility of care training assistant robots in care...
Article
Long‐term electroencephalography (EEG) monitoring is time‐consuming, and re- quires experts to interpret EEG signals to detect seizures in patients. In this paper, we propose a novel automated method called adaptive slope of wavelet coefficient counts over various thresholds (ASCOT) to classify patient episodes as seizure wave- forms. ASCOT involve...
Article
Full-text available
A robotic simulator for elderly caregiver training has an important role with the continuous increase in the proportion of the elderly in the society. Caregivers or therapists, especially the novices, need training in caregiving skills. While one of the best methods is to practice the skills with a real elderly person, there are obstacles such as r...
Conference Paper
The development of elderly robotic simulators for care training is significantly important as the proportion of elderly people continues to increase in the world. Caregivers or therapists, especially the novices, need to be trained in care training skill. The best methodology is to make use of the elderly person for accumulating skill for care...
Article
This paper presents a new method to remove baseline drift and noise by using a differential electrooculography (EOG) signal based on a fixation curve (DOSbFC) and a new electrode positioning scheme based on eyeglasses for user convenience. In addition, a desktop application and mobile applications to control the human–computer interface were implem...
Conference Paper
Stress management is particularly important for healthcare of modern people. In stress research, heart-rate variability (HRV), indicating the change of time intervals in successive heart beats, significantly contributed due to its close relationship with autonomic nervous system. However, the adaptive response to stress, also known as stress resili...
Article
Full-text available
Routine stress monitoring in daily life can predict potentially serious health impacts. Effective stress monitoring in medical and healthcare fields is dependent upon accurate determination of stress-related features. In this study, we determined the optimal stress-related features for effective monitoring of cumulative stress. We first investigate...
Article
Full-text available
Human-activity recognition (HAR) and energy-expenditure (EE) estimation are major functions in the mobile healthcare system. Both functions have been investigated for a long time; however, several challenges remain unsolved, such as the confusion between activities and the recognition of energy-consuming activities involving little or no movement....
Article
In this paper, we propose Korean monophthong recognition method optimizing muscle mixing based on facial surface EMG signals. We observed that EMG signal patterns and muscle activity may vary according to Korean monophthong pronunciation. We use RMS, VAR, MMAV1, MMAV2 which were shown high recognition accuracy in previous study and Cepstral Coeffic...
Article
Powered prosthesis is used to assist walking of people with an amputated lower limb and/or weak leg strength. The accurate gait phase classification is indispensable in smooth movement control of the powered prosthesis. In previous gait phase classification using physical sensors, there is limitation that powered prosthesis should be simulated as s...

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