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Sharif-Human movement instrumentation system (SHARIF-HMIS): Development and validation

Mokhlespour Esfahani, M. I ; Sharif University of Technology | 2018

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  1. Type of Document: Article
  2. DOI: 10.1016/j.medengphy.2018.07.008
  3. Publisher: Elsevier Ltd , 2018
  4. Abstract:
  5. The interest in wearable systems among the biomedical engineering and clinical community continues to escalate as technical refinements enhance their potential use for both indoor and outdoor applications. For example, an important wearable technology known as a microelectromechanical system (MEMS) is demonstrating promising applications in the area of biomedical engineering. Accordingly, this study was designed to investigate the Sharif-Human Movement Instrumentation System (SHARIF-HMIS), consisting of inertial measurement units (IMUs), stretchable clothing, and a data logger—all of which can be used outside the controlled environment of a laboratory, thus enhancing its overall utility. This system is lightweight, portable, able to be deliver data for almost 10 h, and features a new data-fusion algorithm using the Kalman filter with an adaptive approach. In specific terms, the data from the system's gyroscope, accelerometer, and magnetometer sensors can be combined to estimate total-body orientation; additionally, the noise level of these sensors can be changed to accommodate faster motions as well as magnetic disturbances. These variations can be incorporated within the extended Kalman filter by changing the parameters of the filter adaptively. In specific terms, the system's interface was developed to acquire data from eighteen IMUs located on the body to collect kinematic data associated with human motion. Meanwhile, a validation test involving one subject performing different shoulder motions was designed to compare data captured by SHARIF-HMIS and the VICON motion-capture system. This validation test demonstrated correlation values of >0.9. Results also confirmed that the output accuracy of the new system's sensor was <0.55, 1.5 and 3.5° for roll, pitch, and yaw directions, respectively. In summary, SHARIF-HMIS successfully collected kinematic data for specific human movements, which has promising implications for a range of sporting, biomedical, and healthcare-related applications. © 2018 IPEM
  6. Keywords:
  7. Kalman filter ; Wearable system ; Adaptive filtering ; Biomedical engineering ; Biomedical signal processing ; Data fusion ; Electromechanical devices ; Kalman filters ; Kinematics ; MEMS ; Controlled environment ; Data fusion algorithm ; Human movement analysis ; Inertial measurement unit ; Instrumentation systems ; Micro electromechanical system (MEMS) ; Motion capture system ; Wearable systems ; Wearable sensors
  8. Source: Medical Engineering and Physics ; Volume 61 , 2018 , Pages 87-94 ; 13504533 (ISSN)
  9. URL: https://www.sciencedirect.com/science/article/pii/S1350453318301176