• Title/Summary/Keyword: Self-selective angular velocity

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Torque, Work, Power, and Muscle Activity Analysis According to Self-Selected Slow, Moderate, and Fast Angular Velocity for Knee Extension

  • Jonggeun Woo;Jiheon Hong;Jeongwoo Jeon
    • The Journal of Korean Physical Therapy
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    • v.36 no.3
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    • pp.103-109
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    • 2024
  • Purpose: The performance of a task is influenced by the perception of its demands and the development of a response according to the movement pattern. This study aims to compare the change in kinetic variables and quadriceps muscle activity according to demands on angular velocity. Methods: Thirty-eight participants performed knee extensions at self-selective angular velocities of slow, moderate, and fast. Angular velocity, kinetic variables, and muscle activity (vastus medialis, vastus lateralis, and rectus femoris) were measured using a dynamometer and surface electromyography. kinetic variables and muscle activity of the knee extensors at three self-selected angular velocities were compared and correlations between the variables were analyzed. Results: There were significant differences in muscle activity and kinetic variables among angular velocities (p<0.001). Self-selective angular velocity was positively correlated with muscle activities and kinetic variables (p<0.001). The power in fast was 40 times higher than that in slow velocity. Conclusion: The simultaneous increase in angular velocity and force output was based on increased effort. The highest power was indicated for the fastest movement. We discovered that muscle activity and torque increased at a similar rate for increasing demands on angular velocity. The individual's most appropriate pattern would have been applied at the movement of self-selective angular velocity, and fast movement is considered to have the highest efficiency.

Development of the hybrid algorithm for the car navigation system (자동차 항법용 혼합항법 알고리즘 개발)

  • 김상겸;양승규;김정하
    • 제어로봇시스템학회:학술대회논문집
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    • 1997.10a
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    • pp.1403-1406
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    • 1997
  • Generally, G.P.S(Global Positioning System) is using for the car navigation system but it has some restrictions such as the discontinuity of earth satellites and SA (Selective Availability). Recently, the hybrid navigation system combining with G.P.S and Dead-reckoning are much attractuve for improving the accuracy of a vehicle positioning. G.P.S called satellite navigation system, can measure its position by using satellites. Dead-Reckoning is the self-contained navigatioin system using a wheel sensor for the vehicle velocity and a gyro sensor for the vehicle angular velocity. Some algorithm could be generated for finding the vehicle position and orientation. In this paper, we developed a hybrid algotithm wiht G.P.S DR and Map-Matching.

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