Background: The human tracking algorithm called OpenPose can detect joint points and calculate joint angles. However, the reliability and validity of OpenPose have not been clarified yet.Research question: Are there the enough reliability and validity of OpenPose based motion analysis? Methods: 20 healthy young subjects participated in this study. The motion task was a bilateral squat. The joint angles of the trunk, hip, knee, and ankle were calculated using OpenPose and VICON. Kinematic measurements by three-dimensional motion analysis devices were recorded using VICON. Simultaneously, the images were taken with a digital camera from the right side. After the images were processed with OpenPose, joint angles were calculated from estimated joint points. To confirm the test-retest reliability within device, intraclass correlation coefficients [ICC (1, 3)] were calculated. To confirm the validity, linear regression analysis and ICC (2, 1) between the data obtained by OpenPose and VICON were calculated. Furthermore, the agreement between the data obtained by OpenPose and VICON was assessed by Bland-Altman analysis.Results: ICCs (1, 3) of the data obtained by OpenPose and VICON were almost perfect. There were significant associations between the data obtained by OpenPose and VICON. ICCs (2, 1) between the data obtained by OpenPose and VICON were almost perfect or substantial for trunk, knee and ankle joints, and fair on the hip joint. There were fixed biases on knee and ankle joints, and proportional biases on trunk and hip joint.Significance: OpenPose based motion analysis is reliable and has the advantage of being low cost and easier to operate than conventional methods. In future, to consider the clinical utility of OpenPose, it is necessary to identify the error between the true values indicating actual joint movement and data obtained by OpenPose with its correction for fixed and proportional biases.

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Verification of criterion-related validity of the evaluation method of postural stability using the frame subtraction method Author names and affiliationsMegumi Ota a) , Hiroshige Tateuchi a) , Takaya Hashiguchi b) , Yasuhiro Ogino b) , Noriaki Ichihashi c) a.

BackgroundMovement of target subjects can be calculated using the frame subtraction method. However, the validity of this evaluation method of dynamic postural stability has not been clarified yet. This study aimed to verify the validity of the evaluation method for jump landing using the frame subtraction score based on the ground reaction force (GRF). MethodsTwenty subjects performed single leg jump landing, and their dynamic postural stability index (DPSI), medial-lateral stability index (MLSI), anterior-posterior stability index (APSI), and vertical stability index (VSI) were calculated from the GRF. Simultaneously, motion images were taken using digital video cameras in the sagittal and frontal planes. After the motion images were analyzed using the frame subtraction method, the frame subtraction scores on the frontal, sagittal, and combined planes were calculated. To confirm its validity, the relationship between the frame subtraction scores with GRF parameters was investigated using Pearson's correlation analysis. ResultsThe frame subtraction scores on the frontal and combined planes were significantly correlated with DPSI, MLSI and VSI (r = 0.46–0.75, P < 0.05). ConclusionsTherefore, the frame subtraction method could be applied to the evaluation of dynamic postural stability. Markerless or sensorless systems are deemed to be useful in clinical practice.

Background The movement of targeted subjects can be calculated using the frame subtraction method. However, the validity of this evaluation method of dynamic postural stability has not been clarified yet. This study aimed to verify the validity of the evaluation method for jump landing using the frame subtraction score based on the ground reaction force (GRF). Methods Twenty subjects performed single-leg jump landing, and their dynamic postural stability index (DPSI), medial‒lateral stability index (MLSI), anterior‒posterior stability index, and vertical stability index (VSI) were calculated from the GRF. Simultaneously, motion images were captured using digital video cameras in the sagittal and frontal planes. After the motion images were analyzed using the frame subtraction method, the frame subtraction scores in the frontal, sagittal, and combined planes were calculated. To confirm its validity, the relationship between the frame subtraction scores and GRF parameters was investigated using Pearson's correlation analysis. Results The frame subtraction scores in the frontal and combined planes were significantly correlated with the DPSI, MLSI, and VSI (r = 0.46–0.75, P < 0.05). Conclusions Therefore, the frame subtraction method could be applied to the evaluation of dynamic postural stability. Markerless systems are deemed useful in clinical practice.