Browse > Article
http://dx.doi.org/10.9718/JBER.2020.41.3.121

Validation on the Application of Bluetooth-based Inertial Measurement Unit for Wireless Gait Analysis  

Hwang, Soree (Center for Bionics, Korea Institute of Science and Technology (KIST))
Sung, Joohwan (Center for Bionics, Korea Institute of Science and Technology (KIST))
Park, Heesu (Center for Bionics, Korea Institute of Science and Technology (KIST))
Han, Sungmin (Center for Bionics, Korea Institute of Science and Technology (KIST))
Yoon, Inchan (Center for Bionics, Korea Institute of Science and Technology (KIST))
Publication Information
Journal of Biomedical Engineering Research / v.41, no.3, 2020 , pp. 121-127 More about this Journal
Abstract
The purpose of this paper is to review the validation on the application of low frequency IMU(Inertial Measurement Unit) sensors by replacing high frequency motion analysis systems. Using an infrared-based 3D motion analysis system and IMU sensors (22 Hz) simultaneously, the gait cycle and knee flexion angle were measured. And the accuracy of each gait parameter was compared according to the statistical analysis method. The Bland-Altman plot analysis method was used to verify whether proper accuracy can be obtained when extracting gait parameters with low frequency sensors. As a result of the study, the use of the new gait assessment system was able to identify adequate accuracy in the measurement of cadence and stance phase. In addition, if the number of gait cycles is increased and the results of body anthropometric measurements are reflected in the gait analysis algorithm, is expected to improve accuracy in step length, walking speed, and range of motion measurements. The suggested gait assessment system is expected to make gait analysis more convenient. Furthermore, it will provide patients more accurate assessment and customized rehabilitation program through the quantitative data driven results.
Keywords
Gait cycle; Gait parameters; Inertial measurement unit; 3D motion analysis system;
Citations & Related Records
연도 인용수 순위
  • Reference
1 Drewett RF, Minns RJ, Sibly TF. Measuring outcome of total knee replacement using quality of life indices. Annals of the royal college of surgeons of england. 1992;74(4):286.
2 Kirwan J, Currey H, Freeman M, Snow S, Young P. Overall long-term impact of total hip and knee joint replacement surgery on patients with osteoarthritis and rheumatoid arthritis. Rheumatology. 1994;33(4):357-60.   DOI
3 Rorabeck CH, Murray P. The cost benefit of total knee arthroplasty. Orthopedics. 1996;19(9):777-9.   DOI
4 Labraca NS, Castro-Sanchez AM, Mataran-Penarrocha GA, Arroyo-Morales M, Sanchez-Joya MdM, Moreno-Lorenzo C. Benefits of starting rehabilitation within 24 hours of primary total knee arthroplasty: randomized clinical trial. Clinical rehabilitation. 2011;25(6):557-66.   DOI
5 Moffet H, Collet JP, Shapiro SH, Paradis G, Marquis F, Roy L. Effectiveness of intensive rehabilitation on functional ability and quality of life after first total knee arthroplasty: a singleblind randomized controlled trial. Archives of physical medicine and rehabilitation. 2004;85(4):546-64.   DOI
6 Anouchi YS, McShane M, Kelly F, Elting J, Stiehl J. Range of motion in total knee replacement. Clinical Orthopaedics and Related Research. 1996;331:87-92.   DOI
7 Chester VL, Biden EN, Tingley M, Gait analysis. Biomedical instrumentation & technology. 2005;39(1):64-74.
8 Bamberg SJM, Benbasat AY, Scarborough DM, Krebs DE, Paradiso JA. Gait analysis using a shoe-integrated wireless sensor system. IEEE Transactions on Information Technology in Biomedicine. 2008;12(4):413-23.   DOI
9 LeMoyne R, Mastroianni T. Wearable and wireless gait analysis platforms: smartphones and portable media devices. In Wireless MEMS Networks and Applications: Elsevier. 2017:129-52.
10 Seel T, Raisch J, Schauer T. IMU-based joint angle measurement for gait analysis. Sensors. 2014;14(4):6891-909.   DOI
11 Morris J. Accelerometry-A technique for the measurement of human body movements. Journal of biomechanics. 1973;6(6):729-36.   DOI
12 Weber DJ, Stein RB, Chan KM, Loeb G, Richmond F, Rolf R, James K, Chong SL. BIONic WalkAide for correcting foot drop. IEEE Transactions on neural systems and rehabilitation engineering. 2005;13(2):242-6.   DOI
13 Currie G, Rafferty D, Duncan G, Bell F, Evans A. Measurement of gait by accelerometer and walkway: a comparison study. Medical & biological engineering & computing. 1992;30(6):669-70.   DOI
14 Auvinet B, Berrut G, Touzard C, Moutel L, Collet N, Chaleil D, Barrey E. Reference data for normal subjects obtained with an accelerometric device. Gait & posture. 2002;16(2):124-34.   DOI
15 Tong K, Granat MH. A practical gait analysis system using gyroscopes. Medical engineering & physics. 1999;21(2):87-94.   DOI
16 Park SW, Sohn RH, Ryu KH, Kim YH. Comparison of motion sensor systems for gait phase detection. Korean society for precision engineering. 2010;27(2):145-52.
17 Thomas S, Jorg R, Thomas S. IMU-Based Joint Angle Measurement for Gait Analysis. Sensors. 2014;14:6891-909.   DOI
18 Allseits EK, Agrawal V, Prasad A, Bennett C, Kim KJ. Characterizing the impact of sampling rate and filter design on the morphology of lower limb angular velocities. IEEE Sensors Journal, 2019;19(11):4115-22.   DOI