• Journal of Biomedical Engineering Research
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• v.38 no.6
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• pp.330-335
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• 2017

Cardiac arrest is owing to the failure of the heart that makes the blood circulation stop. Arrested blood circulation prevents the supply of the oxygen and the glucose and it results the loss of consciousness and, finally, brain death. Many public institution installed the AED for emergency treatment, but, it is not efficient when the patient is alone. In this paper, we made multiplexed wearable device for cardiac arrest detection. With this device, we measure the individual's electrocardiography, heart sound and motion. If the cardiac arrest is detected, the device make a warning horn and transmit the signal for defibrillation. We obtain 98.33% of ECG data, 94.5% of PCG data and 98.38% of IMU data accuracy for each evaluation and 93.33% accuracy for integrated evaluation.

• Journal of Positioning, Navigation, and Timing
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• v.9 no.1
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• pp.33-42
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• 2020

In Integration Approach (IA)-based Pedestrian Dead Reckoning (PDR), it is important to detect the exact zero-velocity of the foot with an Inertial Measurement Unit (IMU). By detecting zero-velocity during the stance phase of the foot touching the ground and executing Zero-velocity UPdaTe (ZUPT) at the exact time, stable navigation information can be provided by the PDR. When the pace is fast, however, it is not easy to accurately detect the zero-velocity because of the small stance phase interval and the large signal variance of the corresponding interval. Incorrect zero-velcity detection greatly causes navigation errors of IA-based PDR. In this paper, we propose a method to detect the zero-velocity stably even at high speed by novel buffering of IMU's output data and signal processing of the buffer. And we design a PDR based on this. By analyzing the performance of the proposed Zero-Velocity Detection (ZVD) algorithm and ZVD-based PDR through experiemnts, we confirm that the proposed method can provide accurate navigation information of pedestrians such as firefighters in the indoor space.

• The Journal of Korean Physical Therapy
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• v.34 no.6
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• pp.321-325
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• 2022

Purpose: Temporomandibular disorder (TMD) is a condition defined as pain and dysfunction of temporomandibular joints and masticatory muscles. Abnormal interconnections between temporomandibular muscles and cervical spine structures can cause the changes of postural alignment and balance ability. The aim of this study was to investigate changes in static balance ability in subjects with painrelated TMD. Methods: This study conducted on 25 subjects with TMD and 25 control subjects with no TMD. Pressure pain thresholds (PPTs) of the masseter and temporalis muscles were measured using a pressure algometer. Static balance ability was assessed during one leg standing using an Inertial Measurement Unit (IMU) sensor. During balance task, the IMU sensors measured motion and transfer movement data for center of mass (COM) motion, ankle sway and hip sway. Results: PPTs of masseter and temporalis muscles were significantly lower in the TMD group than in the control group (p<0.05). One leg standing, hip sway, and COM sway results were significantly greater in the TMD group (p<0.05), but ankle sways were not different between group. Conclusion: We suggest pain-related TMD is positively related to reduced PPTs of masticatory muscles and to static balance ability. These results should be considered together with global body posture when evaluating or treating pain-related TMD.

• Journal of Advanced Navigation Technology
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• v.23 no.3
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• pp.245-250
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• 2019

Inertial navigation system has navigation errors because of the error of inertial measurement unit (IMU) and misalignment over time. In order to solve this problem, aided navigation system is performed using global navigation satellite system (GNSS), speedometer, etc. The inertial navigation system equipped with underwater vehicle mainly uses speedometer and performed aided navigation because satellite signals do not pass through underwater. There are DVL, EM-Log, and RPM in the speedometer, and the sensors are applied according to the system environment. This paper describes velocity aided navigation using RPM of inertial navigation system operating in high speed and deep water environment. In addition, we proposes an algorithm to compensate the limit of RPM with straight direction and the current velocity error. There are results of monte-calo simulation to prove performance of the proposed algorithm.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.2
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• pp.38-46
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• 2011

3D motion analysis system which is currently widely used for walking analysis has limitations due to both necessity of wide space for many cameras for measurement, high cost, and complicated preparation procedure, which results in low accessability in use and application for clinical diagnosis. To resolve this problem, we developed 3-dimensional wireless ambulatory measurement system based on inertial sensor which can be easily applicable for clinical diagnosis for lower extremity deformity and developed system was evaluated by applying for 10 elderly people with diabetes mellitus. Developed system was composed of wireless ambulatory measurement module that consists of inertial measurement unit (IMU) which measures the gait characteristics, microcontroller which collects and precesses the inertial data, bluetooth device which transfers the measured data to PC and Window's application for storing and processing and analyzing received data. This system will utilize not only to measure lower extremity (foot) problem conveniently in clinical medicine but also to analyze 3D motion of human in other areas as sports science, rehabilitation.

• The Journal of Korea Robotics Society
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• v.9 no.1
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• pp.28-38
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• 2014

This paper verifies the performance of Extended Kalman Filter(EKF) and MCL(Monte Carlo Localization) approach to localization of an underwater vehicle through experiments. Especially, the experiments use acoustic range sensor whose measurement accuracy and uncertainty is not yet proved. Along with localization, the experiment also discloses the uncertainty features of the range measurement such as bias and variance. The proposed localization method rejects outlier range data and the experiment shows that outlier rejection improves localization performance. It is as expected that the proposed method doesn't yield as precise location as those methods which use high priced DVL(Doppler Velocity Log), IMU(Inertial Measurement Unit), and high accuracy range sensors. However, it is noticeable that the proposed method can achieve the accuracy which is affordable for correction of accumulated dead reckoning error, even though it uses only range data of low reliability and accuracy.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.5
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• pp.584-591
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• 2014

This paper presents a novel aided navigation method for AUV (Autonomous Underwater Vehicles). The navigation system for AUV includes several sensors such as IMU (Inertial Measurement Unit), DVL (Doppler Velocity Log) and depth sensor. In general, the $13^{th}$ order INS error model, which includes depth error, velocity error, attitude error, and the accelerometer and gyroscope biases as state variables is used with measurements from DVL and depth sensors. However, the model may degrade the estimation performance of the heading state. Therefore, the $11^{th}$ INS error model is proposed. Its validity is verified by using a degree of observability and analyzing steady state error. The performance of the proposed model is shown by the computer simulation. The results show that the performance of the reduced $11^{th}$ order error model is better than that of the conventional $13^{th}$ order error model.

• Journal of Ocean Engineering and Technology
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• v.17 no.4
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• pp.73-80
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• 2003

This paper presents considerations on the results of the rotating arm test, which was carried out for assessment of an hybrid navigation system for a semi-autonomous underwater vehicle. The navigation system consists of an inertial measurement unit(IMU), an ultra-short baseline(USBL) acoustic navigation sensor and a doppler velocity log(DVL) accompanying a magnetic compass. A navigational systemmodel is derived to include the scale effect and bias errors of the DVL, of which the state equation composed of the navigation states and sensor parameters are 25 in the order. The extended Kalman filter was used to propagate the error covariance, The rotating arm tests were carried out in the Ocean Engineering Basin of KRISO, to generate circular motion. The hybrid underwater navigation system shows good tracking performance against the circular planar motion. Additionally this paper checked the effects of the sampling ratio of the navigation system and the possibility of the dead reckoning with the DVL and the magnetic compass to estimate the position of the vehicle.

• Journal of Positioning, Navigation, and Timing
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• v.7 no.3
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• pp.165-173
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• 2018

Underwater vehicles use Inertial Navigation System (INS) with high-performance Inertial Measurement Unit (IMU) for high precision navigation. However, when underwater navigation is performed for a long time, the INS error gradually diverges, therefore, an integrated navigation method using auxiliary sensors is used to solve this problem. In terms of underwater vehicles, the vertical axis error is primarily compensated through Vertical Channel Damping (VCD) using a depth gauge, and an integrated navigation filter can be designed to perform horizontal axis error and sensor error correction using a speedometer such as Electromagnetic-Log (EM-Log). However, since EM-Log outputs the forward direction relative speed of the vehicle with respect to the sea and sea current, INS correction filter using this may cause a rather large error. Although it is possible to design proper filters if the exact model of the sea current is known, it is impossible to know the accurate model in reality. Therefore, this study proposes an INS/EM-Log integrated navigation filter with the function to estimate sea current using an Interacting Multiple Model (IMM) filters, and the performance of this filter is analyzed through a simulation performed in various environments.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.2
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• pp.302-313
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• 2018

As the demand for indoor location recognition system has been rapidly increased in accordance with the increasing use of smart devices and the increasing use of augmented reality, indoor positioning systems(IPS) using BLE (Bluetooth Lower Energy) beacons and UWB (Ultra Wide Band) have been developed. In this paper, a positioning plate is generated by using trilateration technique based on BLE Beacon and using RSSI (Received Signal Strength Indicator). The resultant value is used to calculate the PDR-based coordinates using the positioning element of the Inertial Measurement Unit sensor, We propose a precise indoor positioning algorithm that combines RSSI and PDR technique. Based on the plate algorithm proposed in this paper, the experiment have done at large scale indoor sports arena and airport, and the results were successfully verified by 65% accuracy improvement with average 2.2m error.