Limits...
Use of the Microsoft Kinect system to characterize balance ability during balance training.

Lim D, Kim C, Jung H, Jung D, Chun KJ - Clin Interv Aging (2015)

Bottom Line: The two systems yielded similar results for changes in the center of body mass (P>0.05) with a large Pearson's correlation coefficient of γ>0.60.The results for the two systems showed similarity in the mean lower-limb joint angle with flexion-extension movements, and these values were highly correlated (hip joint: within approximately 4.6°; knee joint: within approximately 8.4°) (0.40<γ<0.74) (P>0.05).These findings show that clinical and dynamic accuracy can be achieved using the Kinect system in balance training by measuring changes in the center of body mass and flexion-extension movements of the lower limbs, but not abduction-adduction and internal-external rotation.

View Article: PubMed Central - PubMed

Affiliation: Department of Mechanical Engineering, Sejong University, Seoul, Republic of Korea.

ABSTRACT
The risk of falling increases significantly in the elderly because of deterioration of the neural musculature regulatory mechanisms. Several studies have investigated methods of preventing falling using real-time systems to evaluate balance; however, it is difficult to monitor the results of such characterizations in real time. Herein, we describe the use of Microsoft's Kinect depth sensor system to evaluate balance in real time. Six healthy male adults (25.5±1.8 years, 173.9±6.4 cm, 71.4±6.5 kg, and 23.6±2.4 kg/m(2)), with normal balance abilities and with no musculoskeletal disorders, were selected to participate in the experiment. Movements of the participants were induced by controlling the base plane of the balance training equipment in various directions. The dynamic motion of the subjects was measured using two Kinect depth sensor systems and a three-dimensional motion capture system with eight infrared cameras. The two systems yielded similar results for changes in the center of body mass (P>0.05) with a large Pearson's correlation coefficient of γ>0.60. The results for the two systems showed similarity in the mean lower-limb joint angle with flexion-extension movements, and these values were highly correlated (hip joint: within approximately 4.6°; knee joint: within approximately 8.4°) (0.40<γ<0.74) (P>0.05). Large differences with a low correlation were, however, observed for the lower-limb joint angle in relation to abduction-adduction and internal-external rotation motion (γ<0.40) (P<0.05). These findings show that clinical and dynamic accuracy can be achieved using the Kinect system in balance training by measuring changes in the center of body mass and flexion-extension movements of the lower limbs, but not abduction-adduction and internal-external rotation.

No MeSH data available.


Related in: MedlinePlus

Changes in the joint angle of the knee.Notes: (A) During flexion–extension in the medial–lateral direction (x-axis). (B) During abduction–adduction in the anterior–posterior direction (y-axis). (C) Internal–external rotation in the cranial–caudal direction (z-axis).
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f4-cia-10-1077: Changes in the joint angle of the knee.Notes: (A) During flexion–extension in the medial–lateral direction (x-axis). (B) During abduction–adduction in the anterior–posterior direction (y-axis). (C) Internal–external rotation in the cranial–caudal direction (z-axis).

Mentions: Figure 3 shows changes in the hip joint angles during movements of the subjects, and Figure 4 shows changes in the knee joint angles measured using both the Kinect system and the 3D infrared camera system. Table 1 lists a summary of these data. For the hip joints, the changes in the joint angles measured using the Kinect system were 15.67°–25.19° in the x-axis (flexion–extension), 6.61°–21.67° in the y-axis (abduction-adduction), and 6.81°–68.15° in the z-axis (internal–external rotation), whereas the changes measured using the infrared camera system were 13.25°–21.03° in the x-axis, 11.21°–15.83° in the y-axis, and 10.72°–25.78° in the z-axis. For knee joints, the changes in the joint angles measured using the Kinect system were 15.27°–24.37° in the x-axis, 7.93°–25.69° in the y-axis, and 8°–61.22° in the z-axis, whereas those measured using the infrared camera system were 20.36°–31.28° in the x-axis, 4.81°–19.87° in the y-axis, and 6.5°–18.76° in the z-axis. The differences in the measured lower-limb joint angles in the x- and y-axes were small (within 4.6° at the hip joint, and within 8.4° at the knee joint); however, the differences in the lower-limb joint angles in the z-axis were larger (within 19.1° for the hip joint, and within 16.3° for the knee joint). No significant changes were found between the mean lower-limb joint angles measured using the two systems (for the hip joint we found Px=0.22, Py=0.85, and Pz=0.17, and for the knee joint we found Px=0.58, Py=0.37, and Pz=0.08); however, the results of the correlation analysis for changes in the mean lower-limb joint angles measured using the two systems revealed high degrees of correlation in the x-axis (γ=0.73 for the hip joint and γ=0.42 for the knee), but low degrees of correlation in the y- and z-axes (γ<0.40 for both the hip and knee joints). Therefore, changes in the lower-limb joint angles as measured using the Kinect system were in agreement with those from the 3D infrared camera system only for flexion–extension in the x-axis.


Use of the Microsoft Kinect system to characterize balance ability during balance training.

Lim D, Kim C, Jung H, Jung D, Chun KJ - Clin Interv Aging (2015)

Changes in the joint angle of the knee.Notes: (A) During flexion–extension in the medial–lateral direction (x-axis). (B) During abduction–adduction in the anterior–posterior direction (y-axis). (C) Internal–external rotation in the cranial–caudal direction (z-axis).
© Copyright Policy
Related In: Results  -  Collection

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Show All Figures
getmorefigures.php?uid=PMC4493972&req=5

f4-cia-10-1077: Changes in the joint angle of the knee.Notes: (A) During flexion–extension in the medial–lateral direction (x-axis). (B) During abduction–adduction in the anterior–posterior direction (y-axis). (C) Internal–external rotation in the cranial–caudal direction (z-axis).
Mentions: Figure 3 shows changes in the hip joint angles during movements of the subjects, and Figure 4 shows changes in the knee joint angles measured using both the Kinect system and the 3D infrared camera system. Table 1 lists a summary of these data. For the hip joints, the changes in the joint angles measured using the Kinect system were 15.67°–25.19° in the x-axis (flexion–extension), 6.61°–21.67° in the y-axis (abduction-adduction), and 6.81°–68.15° in the z-axis (internal–external rotation), whereas the changes measured using the infrared camera system were 13.25°–21.03° in the x-axis, 11.21°–15.83° in the y-axis, and 10.72°–25.78° in the z-axis. For knee joints, the changes in the joint angles measured using the Kinect system were 15.27°–24.37° in the x-axis, 7.93°–25.69° in the y-axis, and 8°–61.22° in the z-axis, whereas those measured using the infrared camera system were 20.36°–31.28° in the x-axis, 4.81°–19.87° in the y-axis, and 6.5°–18.76° in the z-axis. The differences in the measured lower-limb joint angles in the x- and y-axes were small (within 4.6° at the hip joint, and within 8.4° at the knee joint); however, the differences in the lower-limb joint angles in the z-axis were larger (within 19.1° for the hip joint, and within 16.3° for the knee joint). No significant changes were found between the mean lower-limb joint angles measured using the two systems (for the hip joint we found Px=0.22, Py=0.85, and Pz=0.17, and for the knee joint we found Px=0.58, Py=0.37, and Pz=0.08); however, the results of the correlation analysis for changes in the mean lower-limb joint angles measured using the two systems revealed high degrees of correlation in the x-axis (γ=0.73 for the hip joint and γ=0.42 for the knee), but low degrees of correlation in the y- and z-axes (γ<0.40 for both the hip and knee joints). Therefore, changes in the lower-limb joint angles as measured using the Kinect system were in agreement with those from the 3D infrared camera system only for flexion–extension in the x-axis.

Bottom Line: The two systems yielded similar results for changes in the center of body mass (P>0.05) with a large Pearson's correlation coefficient of γ>0.60.The results for the two systems showed similarity in the mean lower-limb joint angle with flexion-extension movements, and these values were highly correlated (hip joint: within approximately 4.6°; knee joint: within approximately 8.4°) (0.40<γ<0.74) (P>0.05).These findings show that clinical and dynamic accuracy can be achieved using the Kinect system in balance training by measuring changes in the center of body mass and flexion-extension movements of the lower limbs, but not abduction-adduction and internal-external rotation.

View Article: PubMed Central - PubMed

Affiliation: Department of Mechanical Engineering, Sejong University, Seoul, Republic of Korea.

ABSTRACT
The risk of falling increases significantly in the elderly because of deterioration of the neural musculature regulatory mechanisms. Several studies have investigated methods of preventing falling using real-time systems to evaluate balance; however, it is difficult to monitor the results of such characterizations in real time. Herein, we describe the use of Microsoft's Kinect depth sensor system to evaluate balance in real time. Six healthy male adults (25.5±1.8 years, 173.9±6.4 cm, 71.4±6.5 kg, and 23.6±2.4 kg/m(2)), with normal balance abilities and with no musculoskeletal disorders, were selected to participate in the experiment. Movements of the participants were induced by controlling the base plane of the balance training equipment in various directions. The dynamic motion of the subjects was measured using two Kinect depth sensor systems and a three-dimensional motion capture system with eight infrared cameras. The two systems yielded similar results for changes in the center of body mass (P>0.05) with a large Pearson's correlation coefficient of γ>0.60. The results for the two systems showed similarity in the mean lower-limb joint angle with flexion-extension movements, and these values were highly correlated (hip joint: within approximately 4.6°; knee joint: within approximately 8.4°) (0.40<γ<0.74) (P>0.05). Large differences with a low correlation were, however, observed for the lower-limb joint angle in relation to abduction-adduction and internal-external rotation motion (γ<0.40) (P<0.05). These findings show that clinical and dynamic accuracy can be achieved using the Kinect system in balance training by measuring changes in the center of body mass and flexion-extension movements of the lower limbs, but not abduction-adduction and internal-external rotation.

No MeSH data available.


Related in: MedlinePlus