Multi-Objective Optimization for Upper Body Posture Prediction

2004 ◽  
Author(s):  
Jingzhou Yang ◽  
R. Timothy Marler ◽  
HyungJoo Kim ◽  
Jasbir Arora ◽  
Karim Abdel-Malek
Keyword(s):  
Body Posture ◽  
Upper Body ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Upper Body Posture ◽  
Posture Prediction

Recognition and prediction of driver’s whole body posture model

2022 ◽  
pp. 095440702110686
Author(s):  
Jun Wu ◽  
Jian Liu ◽  
Xiuyuan Li ◽  
Lingbo Yan ◽  
Libo Cao ◽  
...  
Keyword(s):  
Regression Model ◽  
Body Posture ◽  
Upper Body ◽  
Whole Body ◽  
Lower Body ◽  
Key Factor ◽  
Upper Body Posture ◽  
Spatial Coordinates ◽  
Posture Prediction ◽  
Connection Length

The driver’s whole-body posture at the time of a collision is a key factor in determining the magnitude of injury to the driver. However, current researchs on driver posture models only consider the upper body posture of the driver, and the lower body area which is not perceived by sensors is not studied. This paper investigates the driver’s posture and establishes a 3D posture model of the driver’s whole body through the application of machine vision algorithms and regression model statistics. This study proposes an improved Kinect-OpenPose algorithm for identifying the 3D spatial coordinates of nine keypoints of the driver’s upper body. The posture prediction regression model of four keypoints of the lower body is established by conducting volunteer posture acquisition experiments on the developed simulated driving seat and analyzing the volunteer posture data through using the principal components of the upper body keypoints and the seat parameters. The experiments proved that the error of the regression model in this paper is minor than that of current studies, and the accuracy of the keypoint location and the keypoint connection length of the established driver whole body posture model is high, which provides implications for future studies.

Multi-objective optimization-based method for kinematic posture prediction: development and validation

Robotica ◽  
2010 ◽  
Vol 29 (2) ◽  
pp. 245-253 ◽  
Author(s):  
Jingzhou (James) Yang ◽  
Tim Marler ◽  
Salam Rahmatalla
Keyword(s):  
Performance Measures ◽  
Human Performance ◽  
Design Tool ◽  
Upper Body ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Validation Criteria ◽  
Posture Prediction ◽  
Development And Validation ◽  
Digital Human

SUMMARYPosture prediction plays an important role in product design and manufacturing. There is a need to develop a more efficient method for predicting realistic human posture. This paper presents a method based on multi-objective optimization (MOO) for kinematic posture prediction and experimental validation. The predicted posture is formulated as a multi-objective optimization problem. The hypothesis is that human performance measures (cost functions) govern how humans move. Twelve subjects, divided into four groups according to different percentiles, participated in the experiment. Four realistic in-vehicle tasks requiring both simple and complex functionality of the human simulations were chosen. The subjects were asked to reach the four target points, and the joint centers for the wrist, elbow, and shoulder and the joint angle of the elbow were recorded using a motion capture system. We used these data to validate our model. The validation criteria comprise R-square and confidence intervals. Various physics factors were included in human performance measures. The weighted sum of different human performance measures was used as the objective function for posture prediction. A two-domain approach was also investigated to validate the simulated postures. The coefficients of determinant for both within-percentiles and cross-percentiles are larger than 0.70. The MOO-based approach can predict realistic upper body postures in real time and can easily incorporate different scenarios in the formulation. This validated method can be deployed in the digital human package as a design tool.

scholarly journals Standard reference values of the upper body posture in healthy middle-aged female adults in Germany

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Daniela Ohlendorf ◽  
Polyna Sosnov ◽  
Julia Keller ◽  
Eileen M. Wanke ◽  
Gerhard Oremek ◽  
...  
Keyword(s):  
Sagittal Plane ◽  
Standing Position ◽  
Repeated Measurements ◽  
Clinical Diagnostics ◽  
Body Posture ◽  
Upper Body ◽  
Back Surface ◽  
Left Shoulder ◽  
Upper Body Posture ◽  
Standard Values

AbstractIn order to classify and analyze the parameters of upper body posture, a baseline in form of standard values is demanded. To this date, standard values have only been published for healthy young women. Data for female adults between 51 and 60 years are lacking. 101 symptom-free female volunteers aged 51–60 (55.16 ± 2.89) years. The mean height of the volunteers was 1.66 ± 0.62 m, with a mean body weight of 69.3 ± 11.88 kg and an average BMI of 25.02 ± 4.55 kg/m2. By means of video raster stereography, a 3D-scan of the upper back surface was measured in a habitual standing position. The confidence interval, tolerance range and ICCs were calculated for all parameters. The habitual standing position is almost symmetrical in the frontal plane the most prominent deviation being a slightly more ventral position of the left shoulder blade in comparison to the right. The upper body (spine position) is inclined ventrally with a minor tilt to the left. In the sagittal plane, the kyphosis angle of the thoracic spine is greater than the lordosis angle of the lumbar spine. The pelvis is virtually evenly balanced with deviations from an ideal position falling under the measurement error margin of 1 mm/1°. There were also BMI influenced postural variations in the sagittal plane and shoulder distance. The ICCs are calculated from three repeated measurements and all parameters can be classified as "almost perfect". Deflections from an ideally symmetric spinal alignment in women aged 51–60 years are small-scaled, with a minimal frontal-left inclination and accentuated sigmoidal shape of the spine. Postural parameters presented in this survey allow for comparisons with other studies as well as the evaluation of clinical diagnostics and applications.

Multi-Objective Optimization of Human Gait With a Discomfort Function

2016 ◽  
Author(s):  
Hyun-Jung Kwon ◽  
Hyun-Joon Chung ◽  
Yujiang Xiang
Keyword(s):  
Joint Torque ◽  
Upper Body ◽  
Whole Body ◽  
Human Gait ◽  
Multi Objective Optimization ◽  
Joint Angles ◽  
Backward Walking ◽  
Multi Objective ◽  
Body Model ◽  
Neutral Angle

The objective of this study was to develop a discomfort function for including a high DOF upper body model during walking. A multi-objective optimization (MOO) method was formulated by minimizing dynamic effort and the discomfort function simultaneously. The discomfort function is defined as the sum of the squares of deviation of joint angles from their neutral angle positions. The dynamic effort is the sum of the joint torque squared. To investigate the efficacy of the proposed MOO method, backward walking simulation was conducted. By minimizing both dynamic effort and the discomfort function, a 3D whole body model with a high DOF upper body for walking was demonstrated successfully.

Effect of upper body posture on forced inspiration and expiration

1982 ◽  
Vol 52 (4) ◽  
pp. 879-886 ◽  
Author(s):  
F. Haas ◽  
M. Simnowitz ◽  
K. Axen ◽  
D. Gaudino ◽  
A. Haas
Keyword(s):  
Muscle Tension ◽  
Spinal Column ◽  
Peak Inspiratory Pressure ◽  
Body Posture ◽  
Upper Body ◽  
Distance Runners ◽  
Long Distance ◽  
Upper Body Posture ◽  
Residual Capacity ◽  
Expiratory Flow

The upper body posture naturally adopted by long distance runners was quantified, and its effects on ventilation were assessed in 14 subjects. Maximum voluntary ventilation (MVV) and flow-volume loop maneuvers were performed in three seated positions: 1) natural running posture (RUN), with back angled forward 11 degrees, neck flexed, and head extended 35 degrees forward of the spinal column; 2) back vertical with head and neck as above (NEF); and 3) head and back vertical (VERT). MVV was significantly higher in RUN compared with both NEF and VERT, as were peak inspiratory pressure (PImax) from functional residual capacity, peak expiratory flow (PEF), and peak inspiratory flow (PIF). Expiratory flow at 50% of vital capacity was significantly higher in RUN and NEF than in VERT, consistent with reported increases in flow due to tracheal stiffening. The increased PIF and PImax in RUN indicate increased inspiratory muscle tension and/or improved transduction of tension into a more negative pleural pressure. Magnetometer tracings of rib cage dimensions demonstrated greater anteroposterior stability during maximal inspiratory efforts in RUN compared with VERT. The improved inspiratory function seen in RUN may be due to more effective diaphragmatic and/or accessory muscle function. These findings demonstrate that the position naturally adopted by long distance runners favors ventilation.

scholarly journals Photogrammetric Assessment of Upper Body Posture Using Postural Angles: A Literature Review

2017 ◽  
Vol 16 (2) ◽  
pp. 131-138 ◽  
Author(s):  
Deepika Singla ◽  
Zubia Veqar ◽  
Mohammed Ejaz Hussain
Keyword(s):  
Literature Review ◽  
Body Posture ◽  
Upper Body ◽  
Upper Body Posture

scholarly journals Influence of typical handball characteristics on upper body posture and postural control in male handball players

2020 ◽  
Vol 12 (1) ◽  
Author(s):  
D. Ohlendorf ◽  
S. Salzer ◽  
R. Haensel ◽  
J. Rey ◽  
L. Maltry ◽  
...  
Keyword(s):  
Postural Control ◽  
Body Posture ◽  
Upper Body ◽  
Upper Body Posture
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