This page has only limited features, please log in for full access.

Prof. Jongshill Lee
Department of Biomedical Engineering, Hanyang University, Seoul 04763, Korea

Basic Info

Basic Info is private.

Research Keywords & Expertise

0 Healthcare
0 Wearable Devices
0 Cardiovascular system
0 Biometric authentication
0 biosignal monitoring

Honors and Awards

The user has no records in this section


Career Timeline

The user has no records in this section.


Short Biography

The user biography is not available.
Following
Followers
Co Authors
The list of users this user is following is empty.
Following: 0 users

Feed

Journal article
Published: 19 May 2021 in International Journal of Environmental Research and Public Health
Reads 0
Downloads 0

This study aimed to assess the effectiveness of a novel chest compression (CC) smart-ring-based feedback system in a manikin simulation. In this randomized, crossover, controlled study, we evaluated the effect of smart-ring CC feedback on cardiopulmonary resuscitation (CPR). The learnability and usability of the tool were evaluated with the System Usability Scale (SUS). Participants were divided into two groups and each performed CCs with and without feedback 2 weeks apart, using different orders. The primary outcome was compression depth; the proportion of accurate-depth (5–6 cm) CCs, CC rate, and the proportion of complete CCs (≤1 cm of residual leaning) were assessed additionally. The feedback group and the non-feedback group showed significant differences in compression depth (52.1 (46.3–54.8) vs. 47.1 (40.5–49.9) mm, p = 0.021). The proportion of accurate-depth CCs was significantly higher in the interventional than in the control condition (88.7 (30.0–99.1) vs. 22.6 (0.0–58.5%), p = 0.033). The mean SUS score was 83.9 ± 8.7 points. The acceptability ranges were ‘acceptable’, and the adjective rating was ‘excellent’. CCs with smart-ring feedback could help achieve the ideal range of depth during CPR. The smart-ring may be a valuable source of CPR feedback.

ACS Style

Chiwon Ahn; Seungjae Lee; Jongshill Lee; Jaehoon Oh; Yeongtak Song; In Kim; Hyunggoo Kang. Impact of a Smart-Ring-Based Feedback System on the Quality of Chest Compressions in Adult Cardiac Arrest: A Randomized Preliminary Study. International Journal of Environmental Research and Public Health 2021, 18, 5408 .

AMA Style

Chiwon Ahn, Seungjae Lee, Jongshill Lee, Jaehoon Oh, Yeongtak Song, In Kim, Hyunggoo Kang. Impact of a Smart-Ring-Based Feedback System on the Quality of Chest Compressions in Adult Cardiac Arrest: A Randomized Preliminary Study. International Journal of Environmental Research and Public Health. 2021; 18 (10):5408.

Chicago/Turabian Style

Chiwon Ahn; Seungjae Lee; Jongshill Lee; Jaehoon Oh; Yeongtak Song; In Kim; Hyunggoo Kang. 2021. "Impact of a Smart-Ring-Based Feedback System on the Quality of Chest Compressions in Adult Cardiac Arrest: A Randomized Preliminary Study." International Journal of Environmental Research and Public Health 18, no. 10: 5408.

Accepted manuscript
Published: 01 February 2021 in Physiological Measurement
Reads 0
Downloads 0

Objective: An objective and convenient primary triage procedure is needed for prioritizing patients who need help in mass casualty incident (MCI) situations, where there is a lack of medical staff and available resources. This study aimed to develop an automated remote decision-making algorithm that remotely categorise a patient's emergency level using clinical parameters that can be measured with a wearable device. Approach: The algorithm was developed according to the following procedures. First, we used the National Trauma Data Bank data set, a large open trauma patient data set assembled by the American College of Surgeons (ACS). In addition, we performed pre-processing to exclude data when the vital sign or consciousness indicator value was missing or physiologically in an abnormal range. Second, we selected the T-RTS method, which classifies emergency levels into four classes (Delayed, Urgent, Immediate and Dead), as the primary outcome. Third, three machine learning methods widely used in the medical field, logistic regression, random forest, and deep neural network (DNN), were applied to build the algorithm. Finally, each method was evaluated using quantitative performance indicators including the macro averaged f1 score, macro-averaged mean absolute error (MMAE), and the area under the receiver operating characteristic curve (AUC). Main results: For total sets, the logistic regression had a macro-averaged f1 score of 0.673, an MMAE of 0.387 and an AUC value of 0.844 (95% CI, 0.843–0.845), while the random forest and DNN had macro-averaged f1 scores of 0.783 and 0.784, MMAEs of 0.297 and 0.298 and AUC values of 0.882 (95% CI, 0.881–0.883) and 0.883(95% CI, 0.881–0.884), respectively. Significance: In a comprehensive analysis of these results, our algorithm demonstrated a viable approach that could be practically adopted in an MCI. In addition, it can be employed to transfer patients and to redistribute available resources according to their priorities.

ACS Style

Dohyun Kim; Jewook Chae; Yunjung Oh; Jongshill Lee; In Young Kim. Automated remote decision-making algorithm as a primary triage system using machine learning techniques. Physiological Measurement 2021, 42, 025006 .

AMA Style

Dohyun Kim, Jewook Chae, Yunjung Oh, Jongshill Lee, In Young Kim. Automated remote decision-making algorithm as a primary triage system using machine learning techniques. Physiological Measurement. 2021; 42 (2):025006.

Chicago/Turabian Style

Dohyun Kim; Jewook Chae; Yunjung Oh; Jongshill Lee; In Young Kim. 2021. "Automated remote decision-making algorithm as a primary triage system using machine learning techniques." Physiological Measurement 42, no. 2: 025006.

Journal article
Published: 28 January 2021 in Biosensors
Reads 0
Downloads 0

Recently, a smart-device-based chest compression depth (CCD) feedback system that helps ensure that chest compressions have adequate depth during cardiopulmonary resuscitation (CPR) was developed. However, no CCD feedback device has been developed for infants, and many feedback systems are inconvenient to use. In this paper, we report the development of a smart-ring-based CCD feedback device for CPR based on an inertial measurement unit, and propose a high-quality chest compression depth estimation algorithm that considers the orientation of the device. The performance of the proposed feedback system was evaluated by comparing it with a linear variable differential transformer in three CPR situations. The experimental results showed compression depth errors of 2.0 ± 1.1, 2.2 ± 0.9, and 1.4 ± 1.1 mm in the three situations. In addition, we conducted a pilot test with an adult/infant mannequin. The results of the experiments show that the proposed smart-ring-based CCD feedback system is applicable to various chest compression methods based on real CPR situations.

ACS Style

Seungjae Lee; Yeongtak Song; Jongshill Lee; Jaehoon Oh; Tae Lim; Chiwon Ahn; In Kim. Development of Smart-Ring-Based Chest Compression Depth Feedback Device for High Quality Chest Compressions: A Proof-of-Concept Study. Biosensors 2021, 11, 35 .

AMA Style

Seungjae Lee, Yeongtak Song, Jongshill Lee, Jaehoon Oh, Tae Lim, Chiwon Ahn, In Kim. Development of Smart-Ring-Based Chest Compression Depth Feedback Device for High Quality Chest Compressions: A Proof-of-Concept Study. Biosensors. 2021; 11 (2):35.

Chicago/Turabian Style

Seungjae Lee; Yeongtak Song; Jongshill Lee; Jaehoon Oh; Tae Lim; Chiwon Ahn; In Kim. 2021. "Development of Smart-Ring-Based Chest Compression Depth Feedback Device for High Quality Chest Compressions: A Proof-of-Concept Study." Biosensors 11, no. 2: 35.

Journal article
Published: 19 January 2021 in Scientific Reports
Reads 0
Downloads 0

Inter-joint coordination and gait variability in knee osteoarthritis (KOA) has not been well investigated. Hip-knee cyclograms can visualize the relationship between the hip and knee joint simultaneously. The aim of this study was to elucidate differences in inter-joint coordination and gait variability with respect to KOA severity using hip-knee cyclograms. Fifty participants with KOA (early KOA, n = 20; advanced KOA, n = 30) and 26 participants (≥ 50 years) without KOA were recruited. We analyzed inter-joint coordination by hip-knee cyclogram parameters including range of motion (RoM), center of mass (CoM), perimeter, and area. Gait variability was assessed by the coefficient of variance (CV) of hip-knee cyclogram parameters. Knee RoM was significantly reduced and total perimeter tended to be decreased with KOA progression. KOA patients (both early and advanced) had reduced stance phase perimeter, swing phase area, and total area than controls. Reduced knee CoM and swing phase perimeter were observed only in advanced KOA. Both KOA groups had a greater CV for CoM, knee RoM, perimeter (stance phase, swing phase and total) and swing phase area than the controls. Increased CV of hip RoM was only observed in advanced KOA. These results demonstrate that hip-knee cyclograms can provide insights into KOA patient gait.

ACS Style

Jae Hyeon Park; Hyojin Lee; Jae-Sung Cho; Inyoung Kim; Jongshill Lee; Seong Ho Jang. Effects of knee osteoarthritis severity on inter-joint coordination and gait variability as measured by hip-knee cyclograms. Scientific Reports 2021, 11, 1 -8.

AMA Style

Jae Hyeon Park, Hyojin Lee, Jae-Sung Cho, Inyoung Kim, Jongshill Lee, Seong Ho Jang. Effects of knee osteoarthritis severity on inter-joint coordination and gait variability as measured by hip-knee cyclograms. Scientific Reports. 2021; 11 (1):1-8.

Chicago/Turabian Style

Jae Hyeon Park; Hyojin Lee; Jae-Sung Cho; Inyoung Kim; Jongshill Lee; Seong Ho Jang. 2021. "Effects of knee osteoarthritis severity on inter-joint coordination and gait variability as measured by hip-knee cyclograms." Scientific Reports 11, no. 1: 1-8.

Journal article
Published: 05 November 2020 in Sensors
Reads 0
Downloads 0

Hand functions affect the instrumental activities of daily living. While functional outcome measures, such as a targeted box and block test, have been widely used in clinical settings and provide a useful measure of overall performance, the advent of a wearable Inertial Measurement Unit(IMU)-based system enables the examination of the specific performance and kinematic parameters of hand movements. This study proposed a novel clip-on IMU system to facilitate the clinically fitted measurements of fine-motor finger and wrist joint movements. Clinical validation was conducted with the aim of characterising age-related changes in hand functions, namely grasping, transporting, and releasing blocks. Eighteen young (age 20–31) and sixteen healthy older adults (age 75–89) were evaluated during the box and block test. The results demonstrated that an older age was characterized by slower movements and higher variations and kinematic alterations in the hand functions, such as a larger range of motions at the fingers as well as kinematic trajectories. The proposed IMU system and subsequent validations highlight the value of the performance and kinematics parameters for a more comprehensive understanding of fine-motor finger and wrist movements that could shed light on further implementations in clinical and practical settings.

ACS Style

Seungjae Lee; Hyejeong Lee; Jongshill Lee; Hokyoung Ryu; In Kim; Jieun Kim. Clip-On IMU System for Assessing Age-Related Changes in Hand Functions. Sensors 2020, 20, 6313 .

AMA Style

Seungjae Lee, Hyejeong Lee, Jongshill Lee, Hokyoung Ryu, In Kim, Jieun Kim. Clip-On IMU System for Assessing Age-Related Changes in Hand Functions. Sensors. 2020; 20 (21):6313.

Chicago/Turabian Style

Seungjae Lee; Hyejeong Lee; Jongshill Lee; Hokyoung Ryu; In Kim; Jieun Kim. 2020. "Clip-On IMU System for Assessing Age-Related Changes in Hand Functions." Sensors 20, no. 21: 6313.

Research article
Published: 11 March 2020 in PLOS ONE
Reads 0
Downloads 0

Measuring blood pressure (BP) at home and remote monitoring can improve the patient’s adherence to BP control and vascular outcomes. This study evaluated the feasibility of a trial regarding the effects of an intensive mobile BP management strategy versus usual care in acute ischemic stroke patients. A feasibility-testing, randomized, open-labeled controlled trial was conducted. Remote BP measurement, data transmission, storage, and centralized monitoring system were organized through a Bluetooth-equipped sphygmomanometer paired to the participants’ smartphones. Participants were randomized equally into intensive management (behavioral intensification to measure BP at home by texting, direct telephone call, or breakthrough visit) and control (usual care) groups. The primary feasibility outcomes were: 1) recruitment time for the pre-specified number of participants, 2) retention of participants, 3) frequency of breakthrough visit calls, 4) response to breakthrough visit call, and 5) proportions satisfying BP measurement criteria. Sixty participants were randomly assigned to the intensive management (n = 31) and control (n = 29) groups, of which 57 participants were included in the primary analysis with comparable baseline characteristics. Recruitment time from the first to the last participant was 350 days, and 95% of randomized participants completed the final visit (intensive, 94%; control, 98%). Eight breakthrough visit calls were made to 7 participants (23%), with complete and immediate responses within 3 ± 4 days. The median of half-day blocks fulfilling the BP measurement criteria per patient were 91% in the intensive group and 83% in the control group (difference, 12.2; 95% confidence interval, 2.2–22.2). No adverse events related to the trial procedures were reported. The intensive monitoring, including remote BP measurement, data transfer, and centralized monitoring system, engaged with behavioral intensification was feasible if the patients complied with the intervention. However, the device utilized would need further improvement prior to a large trial.

ACS Style

Beom Joon Kim; Jong-Moo Park; Tai Hwan Park; Joungsim Kim; Jongshill Lee; Keon-Joo Lee; Jisung Lee; Jae Eun Chae; Lehana Thabane; Juneyoung Lee; Hee-Joon Bae. Remote blood pressure monitoring and behavioral intensification for stroke: A randomized controlled feasibility trial. PLOS ONE 2020, 15, e0229483 .

AMA Style

Beom Joon Kim, Jong-Moo Park, Tai Hwan Park, Joungsim Kim, Jongshill Lee, Keon-Joo Lee, Jisung Lee, Jae Eun Chae, Lehana Thabane, Juneyoung Lee, Hee-Joon Bae. Remote blood pressure monitoring and behavioral intensification for stroke: A randomized controlled feasibility trial. PLOS ONE. 2020; 15 (3):e0229483.

Chicago/Turabian Style

Beom Joon Kim; Jong-Moo Park; Tai Hwan Park; Joungsim Kim; Jongshill Lee; Keon-Joo Lee; Jisung Lee; Jae Eun Chae; Lehana Thabane; Juneyoung Lee; Hee-Joon Bae. 2020. "Remote blood pressure monitoring and behavioral intensification for stroke: A randomized controlled feasibility trial." PLOS ONE 15, no. 3: e0229483.

Journal article
Published: 09 March 2020 in Sensors
Reads 0
Downloads 0

Photoplethysmography (PPG) is an easy and convenient method by which to measure heart rate (HR). However, PPG signals that optically measure volumetric changes in blood are not robust to motion artifacts. In this paper, we develop a PPG measuring system based on multi-channel sensors with multiple wavelengths and propose a motion artifact reduction algorithm using independent component analysis (ICA). We also propose a truncated singular value decomposition for 12-channel PPG signals, which contain direction and depth information measured using the developed multi-channel PPG measurement system. The performance of the proposed method is evaluated against the R-peaks of an electrocardiogram in terms of sensitivity (Se), positive predictive value (PPV), and failed detection rate (FDR). The experimental results show that Se, PPV, and FDR were 99%, 99.55%, and 0.45% for walking, 96.28%, 99.24%, and 0.77% for fast walking, and 82.49%, 99.83%, and 0.17% for running, respectively. The evaluation shows that the proposed method is effective in reducing errors in HR estimation from PPG signals with motion artifacts in intensive motion situations such as fast walking and running.

ACS Style

Jongshill Lee; Minseong Kim; Hoon-Ki Park; In Young Kim; Jongshill Lee. Motion Artifact Reduction in Wearable Photoplethysmography Based on Multi-Channel Sensors with Multiple Wavelengths. Sensors 2020, 20, 1493 .

AMA Style

Jongshill Lee, Minseong Kim, Hoon-Ki Park, In Young Kim, Jongshill Lee. Motion Artifact Reduction in Wearable Photoplethysmography Based on Multi-Channel Sensors with Multiple Wavelengths. Sensors. 2020; 20 (5):1493.

Chicago/Turabian Style

Jongshill Lee; Minseong Kim; Hoon-Ki Park; In Young Kim; Jongshill Lee. 2020. "Motion Artifact Reduction in Wearable Photoplethysmography Based on Multi-Channel Sensors with Multiple Wavelengths." Sensors 20, no. 5: 1493.

Journal article
Published: 28 February 2017 in Sensors
Reads 0
Downloads 0

Generalized tonic-clonic seizures (GTCSs) can be underestimated and can also increase mortality rates. The monitoring devices used to detect GTCS events in daily life are very helpful for early intervention and precise estimation of seizure events. Several studies have introduced methods for GTCS detection using an accelerometer (ACM), electromyography, or electroencephalography. However, these studies need to be improved with respect to accuracy and user convenience. This study proposes the use of an ACM banded to the wrist and spectral analysis of ACM data to detect GTCS in daily life. The spectral weight function dependent on GTCS was used to compute a GTCS-correlated score that can effectively discriminate between GTCS and normal movement. Compared to the performance of the previous temporal method, which used a standard deviation method, the spectral analysis method resulted in better sensitivity and fewer false positive alerts. Finally, the spectral analysis method can be implemented in a GTCS monitoring device using an ACM and can provide early alerts to caregivers to prevent risks associated with GTCS.

ACS Style

Hyo Sung Joo; Su-Hyun Han; Jongshill Lee; Dong Pyo Jang; Joong Koo Kang; Jihwan Woo. Spectral Analysis of Acceleration Data for Detection of Generalized Tonic-Clonic Seizures. Sensors 2017, 17, 481 .

AMA Style

Hyo Sung Joo, Su-Hyun Han, Jongshill Lee, Dong Pyo Jang, Joong Koo Kang, Jihwan Woo. Spectral Analysis of Acceleration Data for Detection of Generalized Tonic-Clonic Seizures. Sensors. 2017; 17 (3):481.

Chicago/Turabian Style

Hyo Sung Joo; Su-Hyun Han; Jongshill Lee; Dong Pyo Jang; Joong Koo Kang; Jihwan Woo. 2017. "Spectral Analysis of Acceleration Data for Detection of Generalized Tonic-Clonic Seizures." Sensors 17, no. 3: 481.

Journal article
Published: 30 June 2014 in Journal of Biomedical Engineering Research
Reads 0
Downloads 0
ACS Style

Seohyun Lim; Kyeongran Min; Jongshill Lee; Dongpyo Jang; Inyoung Kim. Identification of Individuals using Single-Lead Electrocardiogram Signal. Journal of Biomedical Engineering Research 2014, 35, 42 -49.

AMA Style

Seohyun Lim, Kyeongran Min, Jongshill Lee, Dongpyo Jang, Inyoung Kim. Identification of Individuals using Single-Lead Electrocardiogram Signal. Journal of Biomedical Engineering Research. 2014; 35 (3):42-49.

Chicago/Turabian Style

Seohyun Lim; Kyeongran Min; Jongshill Lee; Dongpyo Jang; Inyoung Kim. 2014. "Identification of Individuals using Single-Lead Electrocardiogram Signal." Journal of Biomedical Engineering Research 35, no. 3: 42-49.

Journal article
Published: 01 August 2013 in Annals of Emergency Medicine
Reads 0
Downloads 0
ACS Style

Jaehoon Oh; Taeho Lim; Youngjoon Chee; Jongshill Lee. In reply. Annals of Emergency Medicine 2013, 62, 196 -7.

AMA Style

Jaehoon Oh, Taeho Lim, Youngjoon Chee, Jongshill Lee. In reply. Annals of Emergency Medicine. 2013; 62 (2):196-7.

Chicago/Turabian Style

Jaehoon Oh; Taeho Lim; Youngjoon Chee; Jongshill Lee. 2013. "In reply." Annals of Emergency Medicine 62, no. 2: 196-7.

Research article
Published: 22 February 2012 in Journal of Applied Mathematics
Reads 0
Downloads 0

We propose a new method for personal identification using the derived vectorcardiogram (dVCG), which is derived from the limb leads electrocardiogram (ECG). The dVCG was calculated from the standard limb leads ECG using the precalculated inverse transform matrix. Twenty-one features were extracted from the dVCG, and some or all of these 21 features were used in support vector machine (SVM) learning and in tests. The classification accuracy was 99.53%, which is similar to the previous dVCG analysis using the standard 12-lead ECG. Our experimental results show that it is possible to identify a person by features extracted from a dVCG derived from limb leads only. Hence, only three electrodes have to be attached to the person to be identified, which can reduce the effort required to connect electrodes and calculate the dVCG.

ACS Style

Jongshill Lee; Youngjoon Chee; Inyoung Kim. Personal Identification Based on Vectorcardiogram Derived from Limb Leads Electrocardiogram. Journal of Applied Mathematics 2012, 2012, 1 -12.

AMA Style

Jongshill Lee, Youngjoon Chee, Inyoung Kim. Personal Identification Based on Vectorcardiogram Derived from Limb Leads Electrocardiogram. Journal of Applied Mathematics. 2012; 2012 ():1-12.

Chicago/Turabian Style

Jongshill Lee; Youngjoon Chee; Inyoung Kim. 2012. "Personal Identification Based on Vectorcardiogram Derived from Limb Leads Electrocardiogram." Journal of Applied Mathematics 2012, no. : 1-12.

Journal article
Published: 01 October 2010 in Medicine & Science in Sports & Exercise
Reads 0
Downloads 0
ACS Style

Dohyun Kim; Jaesung Cho; Jongshill Lee; Inyoung Kim. Comparison Of ECG Changing Between Exercise And Recovery Period. Medicine & Science in Sports & Exercise 2010, 42, 82 -83.

AMA Style

Dohyun Kim, Jaesung Cho, Jongshill Lee, Inyoung Kim. Comparison Of ECG Changing Between Exercise And Recovery Period. Medicine & Science in Sports & Exercise. 2010; 42 (10):82-83.

Chicago/Turabian Style

Dohyun Kim; Jaesung Cho; Jongshill Lee; Inyoung Kim. 2010. "Comparison Of ECG Changing Between Exercise And Recovery Period." Medicine & Science in Sports & Exercise 42, no. 10: 82-83.

Conference paper
Published: 03 February 2007 in The 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Reads 0
Downloads 0

Hand gesture recognition utilizing image processing relies upon recognition through markers or hand extraction by colors, and therefore is heavily restricted by the colors of clothes or skin. We propose a method to recognize band gestures extracted from images with a complex background for a more natural interface in HCI (human computer interaction). The proposed method obtains the image by subtracting one image from another sequential image, measures the entropy, separates hand region from images, tracks the hand region and recognizes hand gestures. Through entropy measurement, we have color information that has near distribution in complexion for regions that have big values and extracted hand region from input images. We could draw the hand region adaptively in variable lighting or individual differences because entropy offers color information as well as motion information at the same time. The detected contour using chain code for the hand region is extracted, and present centroidal profile method that is improved little more and recognized gesture of hand. In the experimental results for 6 kinds of hand gesture, it shows the recognition rate with more than 95% for person and 90-100% for each gesture at 5 frames/sec.

ACS Style

Jongshill Lee; Youngjoo Lee; Eunghyuk Lee; Seunghong Hong. Hand region extraction and gesture recognition from video stream with complex background through entropy analysis. The 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2007, 2004, 1513 -6.

AMA Style

Jongshill Lee, Youngjoo Lee, Eunghyuk Lee, Seunghong Hong. Hand region extraction and gesture recognition from video stream with complex background through entropy analysis. The 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. 2007; 2004 ():1513-6.

Chicago/Turabian Style

Jongshill Lee; Youngjoo Lee; Eunghyuk Lee; Seunghong Hong. 2007. "Hand region extraction and gesture recognition from video stream with complex background through entropy analysis." The 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2004, no. : 1513-6.