Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2022 Aug 10;5(5):e772.
doi: 10.1002/hsr2.772. eCollection 2022 Sep.

Assessing the validity of inertial measurement units for shoulder kinematics using a commercial sensor-software system: A validation study

Jakob Henschke  1 , Hannes Kaplick  1 , Monique Wochatz  1 , Tilman Engel  1
Affiliations

Assessing the validity of inertial measurement units for shoulder kinematics using a commercial sensor-software system: A validation study

Jakob Henschke et al. Health Sci Rep. .

Erratum in

  • Erratum.
    [No authors listed] [No authors listed] Health Sci Rep. 2022 Dec 12;6(1):e992. doi: 10.1002/hsr2.992. eCollection 2023 Jan. Health Sci Rep. 2022. PMID: 36519076 Free PMC article.

Abstract

Background and  aims: Wearable inertial sensors may offer additional kinematic parameters of the shoulder compared to traditional instruments such as goniometers when elaborate and time-consuming data processing procedures are undertaken. However, in clinical practice simple-real time motion analysis is required to improve clinical reasoning. Therefore, the aim was to assess the criterion validity between a portable "off-the-shelf" sensor-software system (IMU) and optical motion (Mocap) for measuring kinematic parameters during active shoulder movements.

Methods: 24 healthy participants (9 female, 15 male, age 29 ± 4 years, height 177 ± 11 cm, weight 73 ± 14 kg) were included. Range of motion (ROM), total range of motion (TROM), peak and mean angular velocity of both systems were assessed during simple (abduction/adduction, horizontal flexion/horizontal extension, vertical flexion/extension, and external/internal rotation) and complex shoulder movements. Criterion validity was determined using intraclass-correlation coefficients (ICC), root mean square error (RMSE) and Bland and Altmann analysis (bias; upper and lower limits of agreement).

Results: ROM and TROM analysis revealed inconsistent validity during simple (ICC: 0.040-0.733, RMSE: 9.7°-20.3°, bias: 1.2°-50.7°) and insufficient agreement during complex shoulder movements (ICC: 0.104-0.453, RMSE: 10.1°-23.3°, bias: 1.0°-55.9°). Peak angular velocity (ICC: 0.202-0.865, RMSE: 14.6°/s-26.7°/s, bias: 10.2°/s-29.9°/s) and mean angular velocity (ICC: 0.019-0.786, RMSE:6.1°/s-34.2°/s, bias: 1.6°/s-27.8°/s) were inconsistent.

Conclusions: The "off-the-shelf" sensor-software system showed overall insufficient agreement with the gold standard. Further development of commercial IMU-software-solutions may increase measurement accuracy and permit their integration into everyday clinical practice.

Keywords: diagnostic techniques and procedures; kinematics; shoulder joint; validation study; wearable devices.

PubMed Disclaimer

Conflict of interest statement

The authors declare no conflict interest.

Figures

Figure 1
Figure 1
Calibration (“T‐pose”) position of the participant. (A) dorsal view, (B) frontal view. Reflective markers and two portable IMU sensors were attached on the torso. IMU sensor calibration pose. IMU, inertial measurement units.
Figure 2
Figure 2
Left: Participant performing Vertical flexion (A) and vertical extension (B). Right: angle‐time plots for Mocap (top: the red arrow indicates the calculation of a maximum) and IMU (bottom: the red arrow indicates the calculation of minimum) movement fragmentation (blue arrows indicate beginning/end of movement) before angle offset removal. Vertical flexion and vertical extension with corresponding time‐angle plots. IMU, inertial measurement units.
See this image and copyright information in PMC

References

    1. Allet L, Knols RH, Shirato K, de Bruin ED. Wearable systems for monitoring mobility‐related activities in chronic disease: a systematic review. Sensors. 2010;10(10):9026‐9052. - PMC - PubMed
    1. Hellem A, Shirley M, Schilaty N, Dahm D. Review of shoulder range of motion in the throwing athlete: distinguishing normal adaptations from pathologic deficits. Curr Rev Musculoskelet Med. 2019;12:346‐355. https://link.springer.com/article/10.1007/s12178-019-09563-5 - DOI - PMC - PubMed
    1. Wilk KE, Macrina LC, Fleisig GS, et al. Deficits in glenohumeral passive range of motion increase risk of elbow injury in professional baseball pitchers: a prospective study. Am J Sports Med. 2014;42(9):2075‐2081. - PubMed
    1. Camp CL, Zajac JM, Pearson DB, et al. Decreased shoulder external rotation and flexion are greater predictors of injury than internal rotation deficits: analysis of 132 Pitcher‐Seasons in professional baseball. Arthroscopy. 2017;33(9):1629‐1636. - PubMed
    1. Shanley E, Rauh MJ, Michener LA, Ellenbecker TS, Garrison JC, Thigpen CA. Shoulder range of motion measures as risk factors for shoulder and elbow injuries in high school softball and baseball players. Am J Sports Med. 2011;39(9):1997‐2006. - PubMed

LinkOut - more resources