• ETRI Journal
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• v.42 no.1
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• pp.46-53
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• 2020

Gait analysis is an effective clinical tool across a wide range of applications. Recently, inertial measurement units have been extensively utilized for gait analysis. Effective gait analyses require good estimates of heel-strike and toe-off events. Previous studies have focused on the effective device position and type of triaxis direction to detect gait events. This study proposes an effective heel-strike and toe-off detection algorithm using a smart insole with inertial measurement units. This method detects heel-strike and toe-off events through a time-frequency analysis by limiting the range. To assess its performance, gait data for seven healthy male subjects during walking and running were acquired. The proposed heel-strike and toe-off detection algorithm yielded the largest error of 0.03 seconds for running toe-off events, and an average of 0-0.01 seconds for other gait tests. Novel gait analyses could be conducted without suffering from space limitations because gait parameters such as the cadence, stance phase time, swing phase time, single-support time, and double-support time can all be estimated using the proposed heel-strike and toe-off detection algorithm.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.37 no.3
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• pp.1-8
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• 2000

In this paper, we formulate an optimal control problem to obtain the optimal signal strength and detection threshold for tracking with NN filter, First, we predict the tracking performance of NN filter by using the HYCA method. Based on this method, the predicted tracking performance is represented with respect to signal strength and detection threshold. Using this relation, we find the optimal parameters for following three examples： 1) the sequence of optimal detection threshold which minimizes sum of position estimation error； 2) the sequence of optimal detection threshold which minimizes sum of validation gate volume； and 3) the sequence of optimal signal strength and detection threshold which minimizes sum of signal strength.

• Proceedings of the IEEK Conference
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• 2000.06a
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• pp.181-184
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• 2000

In this paper, performance of an optical CDMA system with PCCC and SCCC is simulated and compared. It is assumed that optical channel is an intensity modulated (IM) channel and direct-detection scheme is employed to detect the received optical signal. The modulation scheme used is pulse-position-modulation (PPM). The performance is evaluated in terms of bit error probability. From the simulation results, it is shown that turbo coding offers considerable coding gain with reasonable encoding/decoding complexity.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.10
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• pp.1481-1487
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• 2017

This paper proposes a sensorless speed control algorithm for parallel-connected dual Surface-mounted Permanent Magnet Synchronous Motors fed by a single inverter. For stable parallel operation of synchronous motors with a single inverter, each motor has to be constantly kept in the synchronization state regardless of load torque. If the master motor with the larger load is controlled, the synchronous state will be maintained. Therefore, detection of the master motor is essential. Conventionally, the master motor is determined by comparing the rotor position error from the relation between the back-EMF for torque angle and the flux position. consequently, the position sensor is deemed essential for finding the rotor position. In this paper, we proposed a method that decides the magnitude of the load from the power angle of two motors due to the load variation and selects the motor to control through the sign function for the sensorless speed control without the position sensor. The results of simulation and experiment conducted verify the efficacy of the proposed method.

• Journal of Electrical Engineering and Technology
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• v.10 no.3
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• pp.1048-1057
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• 2015

This paper proposes a sensorless speed control algorithm for parallel-connected dual Surface-mounted Permanent Magnet Synchronous Motors (SPMSMs) fed by a single inverter. For stable parallel operation of synchronous motors with a single inverter, each motor has to be constantly kept in the synchronization state regardless of load torque. If the master motor with the larger load is controlled, the synchronous state will be maintained. Therefore, detection of the master motor is essential. Conventionally, the master motor is determined by comparing the rotor position error from the relation between the back-EMF for torque angle and the flux position; consequently, the position sensor is deemed essential for finding the rotor position. The parallel sensorless speed control method proposed in this paper uses no position sensor, instead it compares the flux-axis current from the connection between the back-EMF for torque angle and current in unbalanced load conditions. The results of simulation and experiment conducted verify the efficacy of the proposed method.

• The KIPS Transactions:PartB
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• v.16B no.3
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• pp.203-214
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• 2009

In this paper, we could simply compute the user's gaze position based on 2D relations between the pupil center and four corneal specular reflections formed by four IR-illuminators attached on each corner of a monitor, without considering the complex 3D relations among the camera, the monitor, and the pupil coordinates. Therefore, the objectives of our paper are to detect the pupil center and four corneal specular reflections exactly and to compensate for error factors which affect the gaze accuracy. In our method, we compensated for the kappa error between the calculated gaze position through the pupil center and actual gaze vector. We performed one time user calibration to compensate when the system started. Also, we robustly detected four corneal specular reflections that were important to calculate gaze position based on Kalman filter irrespective of the abrupt change of eye movement. Experimental results showed that the gaze detection error was about 1.0 degrees though there was the abrupt change of eye movement.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.46 no.12
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• pp.975-985
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• 2018

The drones have been developed for military purposes and are now used in many fields such as logistics, communications, agriculture, disaster, defense and media. As the range of use of drones increases, cases of abuse of drones are increasing. It is necessary to develop anti-drone technology to detect the position of unwanted drones using the physical phenomena that occur when the drones fly. In this paper, we estimate the DOA(direction of arrival) of the drone by using the acoustic signal generated when the drone is flying. In addition, the dynamics model of the drones was applied to the unscented kalman filter to improve the microphone array detection performance and reduce the error of the position estimation. Through simulation, the drone detection performance was predicted and verified through experiments.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.7
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• pp.771-778
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• 2019

The traditional illuminance intensity detection method using a single sensor has a problem that uniformity of illuminance detection is deteriorated depending on the measurement position due to the narrow FOV characteristic. In order to overcome this problem, a method of detecting an average illuminance value through a plurality of illuminance sensors is used, but the complexity and detection error are increased. In this paper, we propose a illuminance intensity detection method based on a single image sensor with wide FOV. The proposed method can solve the problems such as system complexity and error increase of existing illuminance sensor. The test results show that the difference of average value is 12% using a illuminance sensor, 10.7% using five illuminance sensors, and 6.2% using an image sensor compared with the reference value using the color difference illuminometer. It is confirmed that the proposed method can easily and accurately detect the space illuminance with improved uniformity.

• Speech Sciences
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• v.14 no.1
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• pp.37-62
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• 2007

The current study examines the role of post-lexical tonal patterns of a prosodic phrase in word segmentation. In a word spotting experiment, native Korean listeners were asked to spot a disyllabic or trisyllabic word from twelve syllable speech stream that was composed of three Accentual Phrases (AP). Words occurred with various post-lexical intonation patterns. The results showed that listeners spotted more words in phrase-initial than in phrase-medial position, suggesting that the AP-final H tone from the preceding AP helped listeners to segment the phrase-initial word in the target AP. Results also showed that listeners' error rates were significantly lower when words occurred with initial rising tonal pattern, which is the most frequent intonational pattern imposed upon multisyllabic words in Korean, than with non-rising patterns. This result was observed both in AP-initial and in AP-medial positions, regardless of the frequency and legality of overall AP tonal patterns. Tonal cues other than initial rising tone did not positively influence the error rate. These results not only indicate that rising tone in AP-initial and AP_final position is a reliable cue for word boundary detection for Korean listeners, but further suggest that phrasal intonation contours serve as a possible word boundary cue in languages without lexical prominence.

• Transactions on Electrical and Electronic Materials
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• v.14 no.4
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• pp.187-192
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• 2013

Because of the importance of small target detection in infrared images, many studies have been carried out in this area. Using a Kalman filter and mean shift algorithm, this study proposes an algorithm to track multiple small moving targets even in cases of target disappearance and appearance in serial infrared images in an environment with many noises. Difference images, which highlight the background images estimated with a background estimation filter from the original images, have a relatively very bright value, which becomes a candidate target area. Multiple target tracking consists of a Kalman filter section (target position prediction) and candidate target classification section (target selection). The system removes error detection from the detection results of candidate targets in still images and associates targets in serial images. The final target detection locations were revised with the mean shift algorithm to have comparatively low tracking location errors and allow for continuous tracking with standard model updating. In the experiment with actual marine infrared serial images, the proposed system was compared with the Kalman filter method and mean shift algorithm. As a result, the proposed system recorded the lowest tracking location errors and ensured stable tracking with no tracking location diffusion.