Sunghoon Ivan Lee

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The development of wearable sensors has opened the door for long-term assessment of movement disorders. However, there is still a need for developing methods suitable to monitor motor symptoms in and outside the clinic. The purpose of this paper was to investigate deep learning as a method for this monitoring. Deep learning recently broke records in speech(More)
Due to the exploding costs of chronic diseasesstemming from physical inactivity, wearable sensor systems toenable remote, continuous monitoring of individuals has increasedin popularity. Many research and commercial systems exist inorder to track the activity levels of users from general dailymotion to detailed movements. This work examines this problemfrom(More)
The use of accelerometers to approximate energy expenditure and serve as inputs for exergaming, have both increased in prevalence in response to the worldwide obesity epidemic. Exergames have a need to show energy expenditure values to validate their results, often using accelerometer approximations applied to general daily-living activities. This work(More)
This paper presents SoccAR, a wearable exergame with fine-grain activity recognition; the exergame involves high-intensity movements as the basis for control. A multiple model approach was developed for a generalized, large, multiclass recognition algorithm, with an F Score of a leave-one-subject-out cross-validation greater than 0.9 using various features,(More)
Exergaming is expanding as an option for sedentary behavior in childhood/adult obesity and for extra exercise for gamers. This paper presents the development process for a mobile active sports exergame with near-realistic motions through the usage of body-wearable sensors. The process begins by collecting a dataset specifically targeted to mapping(More)
We envision that diverse social exercising games, or exergames, will emerge, featuring much richer interactivity with immersive game play experiences. Further, the recent advances of mobile devices and wireless networking will make such social engagement more pervasive - people carry portable exergame devices (e.g., jump ropes) and interact with remote(More)
While significant effort has been made on designing Remote Monitoring Systems (RMS), limited research has been conducted on the potential cost savings that these systems offer in terms of reduction in readmission costs, as well as the costs associated with human resources involved in the intervention process. This paper is particularly interested in(More)
In this paper, we present a mechanism for estimating data quality of BANs composed of cardiac sensors. Currently available cardiac monitoring sensors suffer from high level of noise generated from loose physical contact of the sensor node due to the highly mobile and pervasive environment of the BAN (e.g., at-home remote health care applications).(More)
Accurate estimation of energy expenditure during exercise is important for professional athletes and casual users alike, for designing training programs and meeting their fitness goals. However, producing an accurate estimate in a mobile, wearable health-monitoring system is challenging because most calculations require knowledge of the subject's movement(More)
Exergaming as a tool to combat obesity yields an interesting take on the problem of design and implementation of activity recognition systems for truly mobile games that achieve moderate levels of intensity. This work presents SoccAR, a mobile, sensor-based wearable exergaming system with fine-grain activity recognition. The system in this paper presents a(More)