Document Type: Blackboard

Authors

Departement of Electrical Engineering, Fasa University, Fasa, Iran

Abstract

Inertial navigation systems are of the most important and practical systems in determining the velocity, position and attitude of the vehicles and different equipment. In these systems, three accelerometers and three gyroscopes are used to measure linear accelerations and angular velocities of vehicles, respectively. By using the output of these sensors and special inertial algorithms in different frames, parameters of vehicle such as position, velocity and attitude can be calculated. These systems are used in medical equipment including, but not limited to MRI devices, intelligent patient beds, surgical robots and angiography equipment. In this paper, inertial navigation systems, inertial sensors such as accelerometers,  gyroscopes and inertial navigation algorithm are introduced. Afterwards, different  applicable samples of inertial navigation system in medical equipment are described. According to the study carried out in this paper, it is presented and proved that applying inertial navigation in medical equipment is granted with precise and fast positioning as well as attitude determination. Moreover, as this technique of utilizing inertial navigation is applied to  medical devices, a high efficiency system in terms of specifying the position and attitude will be achieved.

Keywords

  1. Titterton D, Weston JL. Strapdown inertial navigation technology: IET; 2004.
  2. Ekütekin V. Navigation and control studies on cruise missiles: Middle East Technical University; 2007.
  3. Ahmad N, Ghazilla RAR, Khairi NM, Kasi V. Reviews on various inertial measurement unit (IMU) sensor applications. International Journal of Signal Processing Systems. 2013;1:256-62. doi.org/10.12720/ijsps.1.2.256-262.
  4. Borenstein J, Everett HR, Feng L, Wehe D. Mobile robot positioning-sensors and techniques. DTIC Document. 1997.
  5. Niu X, Wang Q, Li Y, Li Q, Liu J. Using inertial sensors in smartphones for curriculum experiments of inertial navigation technology. Education Sciences. 2015;5:26-46. doi.org/10.3390/educsci5010026.
  6. Panahandeh G, Händel P, editors. Planar-based visual inertial navigation. Localization and GNSS (ICL-GNSS), 2015 International Conference on; 2015: IEEE.
  7. Pajkanović A, Dokić B. Wheelchair control by head motion. Serbian Journal of electrical engineering. 2013;10:135-51. doi.org/10.2298/SJEE1301135P.
  8. Tao W, Liu T, Zheng R, Feng H. Gait analysis using wearable sensors. Sensors (Basel). 2012;12:2255-83. doi.org/10.3390/s120202255. PubMed PMID: 22438763. PubMed PMCID: 3304165.
  9. Alonge F, Cucco E, D’Ippolito F, Pulizzotto A. The use of accelerometers and gyroscopes to estimate hip and knee angles on gait analysis. Sensors (Basel). 2014;14:8430-46. doi.org/10.3390/s140508430. PubMed PMID: 24828578. PubMed PMCID: 4063036.
  10. Höller K, Penne J, Schneider A, Jahn J, Guttiérrez Boronat J, Wittenberg T, et al. Endoscopic orientation correction. Medical Image Computing and Computer-Assisted Intervention–MICCAI 2009;2009:459-66.
  11. Titterton D, Weston JL. Strapdown inertial navigation technology. 2nd edition. IET: United Kigdom; 2004.
  12. Kanesalingam T. Motion Tracking Glove for Human-Machine Interaction: Inertial Guidance. 2010.