Sung Q Lee

Dr. Sung Q Lee

orcid

Research Focus & Metrics

Academic Career Length

23Years (2004-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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3 January 2020 in IEEE Access
Verified
Journal Article
Open access
RLRan Lee
Ran Lee
MKMin-Seok Kang
Min-Seok Kang
BKBo-Hyun Kim
Bo-Hyun Kim
KPKang-Ho Park
Kang-Ho Park
SLSung Q Lee
Sung Q Lee
HPHyung-Min Park
Hyung-Min Park
Although sound source localization is a desirable technique in many communication systems and intelligence applications, the distortion caused by diffuse noise or reverberation makes the time delay estimation (TDE) between signals acquired by a pair of microphones a complicated and challenging problem. In this paper, we describe a method that can efficiently achieve sound source localization in noisy and reverberant environments. This method is based on the generalized cross-correlation (GCC) function with phase transform (PHAT) weights (GCC-PHAT) to achieve robustness against reverberation. In addition, to estimate the time delay robust to diffuse components and to further improve the robustness of the GCC-PHAT against reverberation, time-frequency(t-f) components of observations directly emitted by a point source are chosen by “inversed” diffuseness. The diffuseness that can be estimated from the coherent-to-diffuse power ratio (CDR) based on spatial coherence between two microphones represents the contribution of diffuse components on a scale of zero to one with direct sounds from a source modeled to be fully coherent. In particular, the “inversed” diffuseness is binarized with a very rigorous threshold to select highly reliable components for accurate TDE even in noisy and reverberant environments. Experimental results for both simulated and real-recorded data consistently demonstrated the robustness of the presented method against diffuse noise and reverberation.

29 July 2023 in Sensors
Verified
Journal Article
Open access
PDF file
KMKee S. Moon
Kee S. Moon
SLSung Q Lee
Sung Q Lee
Wireless sensing systems are required for continuous health monitoring and data collection. It allows for patient data collection in real time rather than through time-consuming and expensive hospital or lab visits. This technology employs wearable sensors, signal processing, and wireless data transfer to remotely monitor patients’ health. The research offers a novel approach to providing primary diagnostics remotely with a digital health system for monitoring pulmonary health status using a multimodal wireless sensor device. The technology uses a compact wearable with new integration of acoustics and biopotentials sensors to monitor cardiovascular and respiratory activity to provide comprehensive and fast health status monitoring. Furthermore, the small wearable sensor size may stick to human skin and record heart and lung activities to monitor respiratory health. This paper proposes a sensor data fusion method of lung sounds and cardiograms for potential real-time respiration pattern diagnostics, including respiratory episodes like low tidal volume and coughing. With a p-value of 0.003 for sound signals and 0.004 for electrocardiogram (ECG), preliminary tests demonstrated that it was possible to detect shallow breathing and coughing at a meaningful level.

17 December 2017 in Sensors
Verified
Journal Article
Open access
PDF file
AGApoorva Gaidhani
Apoorva Gaidhani
KMKee Moon
Kee Moon
Yusuf OzturkYusuf Ozturk
Yusuf Ozturk
SLSung Q Lee
Sung Q Lee
WYWoosub Youm
Woosub Youm
Respiratory activity is an essential vital sign of life that can indicate changes in typical breathing patterns and irregular body functions such as asthma and panic attacks. Many times, there is a need to monitor breathing activity while performing day-to-day functions such as standing, bending, trunk stretching or during yoga exercises. A single IMU (inertial measurement unit) can be used in measuring respiratory motion; however, breathing motion data may be influenced by a body trunk movement that occurs while recording respiratory activity. This research employs a pair of wireless, wearable IMU sensors custom-made by the Department of Electrical Engineering at San Diego State University. After appropriate sensor placement for data collection, this research applies principles of robotics, using the Denavit-Hartenberg convention, to extract relative angular motion between the two sensors. One of the obtained relative joint angles in the “Sagittal” plane predominantly yields respiratory activity. An improvised version of the proposed method and wearable, wireless sensors can be suitable to extract respiratory information while performing sports or exercises, as they do not restrict body motion or the choice of location to gather data.

4 December 2009 in ETRI Journal
Verified
Journal Article
Open access
PDF file
HKHye Jin Kim
Hye Jin Kim
KKKunmo Koo
Kunmo Koo
SLSung Q Lee
Sung Q Lee
KPKang-Ho Park
Kang-Ho Park
JKJongdae Kim
Jongdae Kim
This paper reports on an improved piezoelectric microspeaker with a high sound pressure level of 90 dB, a total harmonic distortion of less than 15%, and coherence higher than 0.9. The fabricated Pb(Zr,Ti)O3 (PZT) microspeakers have a thickness of only 1 mm including the speaker frame and an active area of 18 mm×20 mm. To achieve higher sound pressure and lower distortion, the PZT piezoelectric microspeaker has a well-designed speaker frame and a piezoelectric diaphragm consisting of a tilted PZT membrane and silicone buffer layer. From the simulation and measurement results, we confirmed that the silicon buffer layer can lower the first resonant frequency, which enhances the microspeaker's sound pressure at a low frequency range and can also reduce useless distortion generated by the harmonics. The fabricated PZT piezoelectric microspeakers are implemented on a multichannel speaker array system for personal acoustical space generation. The output sound pressure at a 30 cm distance away from the center of the speaker line array is 15 dB higher than the sound pressure at the neighboring region 30 degrees from the vertical axis.

24 September 2016 in Sensors
Verified
Journal Article
Open access
PDF file
YSYi Su
Yi Su
SRSudhamayee Routhu
Sudhamayee Routhu
KMKee Moon
Kee Moon
SLSung Q Lee
Sung Q Lee
WYWooSub Youm
WooSub Youm
Yusuf OzturkYusuf Ozturk
Yusuf Ozturk
All neural information systems (NIS) rely on sensing neural activity to supply commands and control signals for computers, machines and a variety of prosthetic devices. Invasive systems achieve a high signal-to-noise ratio (SNR) by eliminating the volume conduction problems caused by tissue and bone. An implantable brain machine interface (BMI) using intracortical electrodes provides excellent detection of a broad range of frequency oscillatory activities through the placement of a sensor in direct contact with cortex. This paper introduces a compact-sized implantable wireless 32-channel bidirectional brain machine interface (BBMI) to be used with freely-moving primates. The system is designed to monitor brain sensorimotor rhythms and present current stimuli with a configurable duration, frequency and amplitude in real time to the brain based on the brain activity report. The battery is charged via a novel ultrasonic wireless power delivery module developed for efficient delivery of power into a deeply-implanted system. The system was successfully tested through bench tests and in vivo tests on a behaving primate to record the local field potential (LFP) oscillation and stimulate the target area at the same time.

4 December 2020 in Science Advances
Verified
Journal Article
Open access
PDF file
JKJisoo Kim
Jisoo Kim
CKChaewoo Kim
Chaewoo Kim
HHHio-Been Han
Hio-Been Han
CCCheol Jun Cho
Cheol Jun Cho
WYWooseob Yeom
Wooseob Yeom
JCJee Hyun Choi
Jee Hyun Choi
Illuminating neural event of interests on the head shows the direct link between brain activity and behaviors in group of mice.