Joint movements are the key factor for the mobility of the people during daily activities. The evaluation of the joint movements is determined by the range of motion (ROM) parameters. The ROM might change due to age, gender, and some diseases. Therefore, it is essential to measure ROM accurately and compare it with the normal values of the healthy people. In this study, a low-cost, wireless, and wearable electrogoniometer was designed for highly precise and accurate measurements. The stability of the measurements is guaranteed with the quaternion based Kalman filter. The measurements of the developed system are compared with the traditional goniometer. The concordance correlation coefficient is calculated as a similarity metric, and the result is obtained as . In addition, a GUI was prepared to present 3D visualization of the movements in real-time with the ROM measurements and give visual feedback to the physiotherapists during physical examinations and to the patient during the home therapy sessions. The measurements also can be recorded using the GUI for retrospective analysis.
TerweeCBde WinterAFScholtenRJ, et al. Interobserver reproducibility of the visual estimation of range of motion of the shoulder. Arch Phys Med Rehabil2005; 86: 1356–1361.
2.
CharltonPCMentiplayBFPuaY-H, et al. Reliability and concurrent validity of a smartphone, bubble inclinometer and motion analysis system for measurement of hip joint range of motion. J Sci Med Sport2015; 18: 262–267.
3.
Dos SantosRADerhonVBrandalizeM, et al. Evaluation of knee range of motion: correlation between measurements using a universal goniometer and a smartphone goniometric application. J Bodyw Mov Ther2017; 21: 699–703.
4.
JohnsonLBSumnerSDuongT, et al. Validity and reliability of smartphone magnetometer-based goniometer evaluation of shoulder abduction–a pilot study. Man Ther2015; 20: 777–782.
5.
KolberMJFullerCMarshallJ, et al. The reliability and concurrent validity of scapular plane shoulder elevation measurements using a digital inclinometer and goniometer. Physiother Theory Pract2012; 28: 161–168.
6.
MilaneseSGordonSBuettnerP, et al. Reliability and concurrent validity of knee angle measurement: smart phone app versus universal goniometer used by experienced and novice clinicians. Man Ther2014; 19: 569–574.
7.
OckendonMGilbertRE.Validation of a novel smartphone accelerometer-based knee goniometer. J Knee Surg2012; 25: 341–346.
8.
PourahmadiMRBagheriRTaghipourM, et al. A new iPhone application for measuring active craniocervical range of motion in patients with non-specific neck pain: a reliability and validity study. Spine J2018; 18: 447–457.
9.
ShinSHLeeO-SOhJH, et al. Within-day reliability of shoulder range of motion measurement with a smartphone. Man Ther2012; 17: 298–304.
10.
StennebergMSBusstraHEskesM, et al. Concurrent validity and interrater reliability of a new smartphone application to assess 3D active cervical range of motion in patients with neck pain. Musculoskelet Sci Pract2018; 34: 59–65.
11.
WernerBCHolzgrefeREGriffinJW, et al. Validation of an innovative method of shoulder range-of-motion measurement using a smartphone clinometer application. J Shoulder Elbow Surg2014; 23: e275–e282.
12.
DomínguezGCardielEAriasS, et al. A digital goniometer based on encoders for measuring knee-joint position in an orthosis. In: 2013 world congress on nature and biologically inspired computing (NaBIC), Fargo, ND, 12–14 August 2013, pp.1–4. New York: IEEE.
13.
El-GoharyMMcNamesJ.Shoulder and elbow joint angle tracking with inertial sensors. IEEE Trans Biomed Eng2012; 59: 2635–2641.
14.
MullaneyMJMcHughMPJohnsonCP, et al. Reliability of shoulder range of motion comparing a goniometer to a digital level. Physiother Theory Pract2010; 26: 327–333.
15.
YaikwawongsNLimpaphayomNWilairatanaV.Reliability of digital compass goniometer in knee joint range of motion measurement. J Med Assoc Thai2009; 92: 517.
16.
NguyenVTHuynhLGCaiV, et al. Kinematic measurement of the ankle joint using a six d.o.f. electro-goniometer. In: 2017 international conference on system science and engineering (ICSSE), Ho Chi Minh City, Vietnam, 21–23 July 2017, pp.24–28. New York: IEEE.
17.
MuñozDPruettAWilliamsG.Knee: an everyday wearable goniometer for monitoring physical therapy adherence. In: CHI’14 extended abstracts on human factors in computing systems, Toronto, ON, Canada, April 2014, pp.209–214. New York: ACM.
18.
MehtaSPBarkerKBowmanB, et al. Reliability, concurrent validity, and minimal detectable change for iPhone goniometer app in assessing knee range of motion. J Knee Surg2017; 30: 577–584.
19.
AgostiniVKnaflitzMAntenucciL, et al. Wearable sensors for gait analysis. In: 2015 IEEE international symposium on medical measurements and applications (MeMeA), Turin, Italy, 7–9 May 2015, pp.146–150. New York: IEEE.
20.
YoonT-L.Validity and reliability of an inertial measurement unit-based 3D angular measurement of shoulder joint motion. J Korean Phys Ther2017; 29: 145–151.
21.
Ruiz-OlayaAFCallejas-CuervoMLara-HerreraCN.Wearable low-cost inertial sensor-based electrogoniometer for measuring joint range of motion. Dyna2017; 84: 180–185.
GopuraRKiguchiK.Mechanical designs of active upper-limb exoskeleton robots: state-of-the-art and design difficulties. In: 2009 IEEE international conference on rehabilitation robotics (ICORR), Kyoto, Japan, 23–26 June 2009, pp.178–187. New York: IEEE.
25.
DoorenboschCAHarlaarJVeegerDH.The globe system: an unambiguous description of shoulder positions in daily life movements. J Rehabil Res Dev2003; 40(2): 147–155.
26.
WangLZhangZSunP.Quaternion-based Kalman filter for AHRS using an adaptive-step gradient descent algorithm. Int J Adv Robot Syst2015; 12: 131.
27.
EberlyD.Quaternion algebra and calculus. Or Yehuda, Israel: Magic Software Inc, 2002.
28.
PerumalL.Quaternion and its application in rotation using sets of regions. Int J Eng Technol Innov2011; 1: 35.
29.
SabatiniAM.Quaternion-based extended Kalman filter for determining orientation by inertial and magnetic sensing. IEEE Trans Biomed Eng2006; 53: 1346–1356.
30.
LinLI.A concordance correlation coefficient to evaluate reproducibility. Biometrics1989; 45(1): 255–268.
31.
McBrideG.A proposal for strength-of-agreement criteria for Lin’s concordance correlation coefficient. NIWA Client Report. HAM2005-062, May2005. Hamilton: NIWA.
