Human Standing-Up Trajectory Model and Experimental Study on Center-Of -Mass Velocity

Shi, Yaochen; Meng, Lingyang; Daimin, Chen

doi:10.1088/1757-899x/612/2/022088

Cited by 2 publications

(4 citation statements)

References 3 publications

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“…The authors believe that STS transitions are equal to soft switching between different postural states, which is a sequence of emergent behaviors. The overwhelming majority of the published research in analyzing the STS movement area has addressed the muscle coordination dynamics and has modeled either the kinematic behavior of STS using simple multi-link models or the motion trajectories [9][10][11][12][13][14][15][16][17][18][19]. Nevertheless, the pattern of the kinematic interaction and synergetic coordination among the joints involved during STS has not been deeply scrutinized.…”

Section: Discussionmentioning

confidence: 99%

“…In another study, the temporal features of muscle synergies during STS were compared between healthy participants and post-stroke patients [11]. The focus of another class of studies has been on modeling the optimized kinematic behavior of STS movement [12][13][14][15][16][17][18][19]. In [13], it has been examined whether the minimum jerk and minimum-torque change models are suitable for predicting optimal joint trajectories during STS or not.…”

Section: Introductionmentioning

confidence: 99%

“…In these studies, the hip position relative to the ankle location and inclination angle of the head arm torso (HAT) was represented by three composite Bezier curves [16,18]. In another study, a human standing-up trajectory model was established by adopting a three-link model identified using captured human data [19].…”

Section: Introductionmentioning

confidence: 99%

“…The emphasis of the aforementioned categorized studies was mainly on identifying muscle coordination dynamics and joint trajectories during STS were not addressed [9][10][11]. An overwhelming majority of the studies focused on modeling joint trajectories using simplified multi-link models without considering the muscle part [12][13][14][15][17][18][19]. During STS movement, the range of transition is so large that it requires a significant change in the length of the muscle-tendon [20]; therefore, the effect of the nonlinear behavior of the muscle on the movement pattern is negligible.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Is the Hénon map able to predict the interaction dynamics between the knee and hip joints emerged during sit-to-stand movement?

Torbati¹,

Jami²,

Kobravi³

2022

Biomed. Phys. Eng. Express

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In this study, the performance of a two-dimensional Hénon map in predicting the interactive dynamics of the knee and hip joints emerging during a normative sit-to-stand movement was evaluated. The instantaneous values of the knee and hip joints were the model inputs, and the next values of the knee and hip joints were predicted by the Hénon map. The map predicted the desired relative behavior of the joints, showing synergetic coordination between the joints. The experimental data were recorded from four healthy participants and used to identify the Hénon map via a genetic algorithm. Model performance was quantitatively assessed by computing the calculated prediction error and analyzing the behavioral dynamics of the state spaces reconstructed via the captured kinematic data. According to the results, there was an obvious similarity between the dynamics of the state space trajectories of the identified model and those of the recorded data, not only in terms of stretching and folding dynamics, but also concerning generalized synchrony. The acceptable performance of the proposed modeling solution can also be demonstrated through these results.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Is the Hénon map able to predict the interaction dynamics between the knee and hip joints emerged during sit-to-stand movement?

Torbati¹,

Jami²,

Kobravi³

2022

Biomed. Phys. Eng. Express

View full text Add to dashboard Cite

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IOAM: A Novel Sensor Fusion-Based Wearable for Localization and Mapping

Lee

Pike

et al. 2022

Remote Sensing

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With the development of indoor location-based services (ILBS), the dual foot-mounted inertial navigation system (DF-INS) has been extensively used in many fields involving monitoring and direction-finding. It is a widespread ILBS implementation with considerable application potential in various areas such as firefighting and home care. However, the existing DF-INS is limited by a high inaccuracy rate due to the highly dynamic and non-stable stride length thresholds. The system also provides less clear and significant information visualization of a person’s position and the surrounding map. This study proposes a novel wearable-foot IOAM-inertial odometry and mapping to address the aforementioned issues. First, the person’s gait analysis is computed using the zero-velocity update (ZUPT) method with data fusion from ultrasound sensors placed on the inner side of the shoes. This study introduces a dynamic minimum centroid distance (MCD) algorithm to improve the existing extended Kalman filter (EKF) by limiting the stride length to a minimum range, significantly reducing the bias in data fusion. Then, a dual trajectory fusion (DTF) method is proposed to combine the left- and right-foot trajectories into a single center body of mass (CBoM) trajectory using ZUPT clustering and fusion weight computation. Next, ultrasound-type mapping is introduced to reconstruct the surrounding occupancy grid map (S-OGM) using the sphere projection method. The CBoM trajectory and S-OGM results were simultaneously visualized to provide comprehensive localization and mapping information. The results indicate a significant improvement with a lower root mean square error (RMSE = 1.2 m) than the existing methods.

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Human Standing-Up Trajectory Model and Experimental Study on Center-Of -Mass Velocity

Cited by 2 publications

References 3 publications

Is the Hénon map able to predict the interaction dynamics between the knee and hip joints emerged during sit-to-stand movement?

Is the Hénon map able to predict the interaction dynamics between the knee and hip joints emerged during sit-to-stand movement?

IOAM: A Novel Sensor Fusion-Based Wearable for Localization and Mapping

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