• Title/Summary/Keyword: MPU9250

Search Result 3, Processing Time 0.017 seconds

A Study on MTL Device Design and Motion Tracking in Virtual Reality Environments

  • Oh, Am-Suk
    • Journal of information and communication convergence engineering
    • /
    • v.17 no.3
    • /
    • pp.205-212
    • /
    • 2019
  • Motion tracking and localization devices are an important building block of motion tracking systems in a virtual reality (VR) environment. This study is about improving the accuracy of motion and location for enhancing user immersion in experience type VR environment to position tracking technique. In this study, we propose and test a design of such a device. The module data test of the attitude and heading reference system shows that the implementation with the MPU-9250 sensor is successful and adequate to be used with short operation time. We consider various sensor hardware dependencies of VR, and compare various correction methods and filtering methods to lower the motion to photon (MTP) time that user movement is fully reflected on the display using sensor devices. The Kalman filter is used to combine the accelerometer with the gyroscope in the sensing unit.

Collision Detection Algorithm using a 9-axis Sensor in Road Facility (9축센서 기반의 도로시설물 충돌감지 알고리즘)

  • Hong, Ki Hyeon;Lee, Byung Mun
    • Journal of Korea Multimedia Society
    • /
    • v.25 no.2
    • /
    • pp.297-310
    • /
    • 2022
  • Road facilities such as CCTV poles have potential risk of collision accidents with a car. A collision detection algorithm installed in the facility allows the collision accident to be known remotely. Most collision detection algorithms are operated by simply focusing on whether a collision have occurred, because these methods are used to measure only acceleration data from a 3-axis sensor to detect collision. However, it is difficult to detect other detailed information such as malfunction of the sensor, collision direction and collision strength, because it is not known without witness the accident. Therefore, we proposed enhanced detection algorithm to get the collision direction, and the collision strength from the tilt of the facility after accident using a 9-axis sensor in this paper. In order to confirm the performance of the algorithm, an accuracy evaluation experiment was conducted according to the data measurement cycle and the invocation cycle to an detection algorithm. As a result, the proposed enhanced algorithm confirmed 100% accuracy for 50 weak collisions and 50 strong collisions at the 9-axis data measurement cycle of 10ms and the invocation cycle of 1,000ms. In conclusion, the algorithm proposed is expected to provide more reliable and detailed information than existing algorithm.

Development of an Eye Patch-Type Biosignal Measuring Device to Measure Sleep Quality (수면의 질을 측정하기 위한 안대형 생체신호 측정기기 개발)

  • Changsun Ahn;Jaekwan Lim;Bongsu Jung;Youngjoo Kim
    • KIPS Transactions on Computer and Communication Systems
    • /
    • v.12 no.5
    • /
    • pp.171-180
    • /
    • 2023
  • The three major sleep disorders in Korea are snoring, sleep apnea, and insomnia. Lack of sleep is the root of all diseases. Some of the most serious potential problems associated with sleep deprivation are cardiovascular problems, cognitive impairment, obesity, diabetes, colitis, prostate cancer, etc. To solve these problems, the Korean government provided low-cost national health insurance benefits for polysomnography tests in July 2018. However, insomnia patients still have problems getting treated in terms of time, space, and economic perspectives. Therefore, it would be better for insomnia patients to be allowed to test at home. The measuring device can measure six biosignals (eye movement, tossing and turning, body temperature, oxygen saturation, heart rate, and audio). A gyroscope sensor (MPU9250, InvenSense, USA) was used for eye movement, tossing, and turning. The input range of the sensor was in 258°/sec to 460°/sec, and the data range was in the input range. Body temperature, oxygen saturation range, and heart rate were measured by a sensor (MAX30102, Analog Devices, USA). The body temperature was measured in 30 ℃ to 45 ℃, and the oxygen saturation range was 0% for the unused state and 20 % to 90 % for the used state. The heart rate measurement range was in 40 bpm to 180 bpm. The measurement of audio signal was performed by an audio sensor (AMM2742-T-R, PUIaudio, USA). The was -42 dB ±1 dB frequency range was 20 Hz to 20 kHz. The measured data was successfully received in wireless network conditions. The system configuration was consisted of a PC and a mobile app for bio-signal measurement and data collection. The measured data was collected by mobile phones and desktops. The data collected can be used as preliminary data to determine the stage of sleep and perform the screening function for sleep induction and sleep disturbances. In the future, this convenient sleep measurement device could be beneficial for treating insomnia.