scholarly journals 3D-Posture Recognition Using Joint Angle Representation

2014 ◽  
pp. 106-115 ◽  
Author(s):  
Adnan Al Alwani ◽  
Youssef Chahir ◽  
Djamal E. Goumidi ◽  
Michèle Molina ◽  
François Jouen
Keyword(s):  
Joint Angle ◽  
Posture Recognition

Joint-angle-based yoga posture recognition for prevention of falls among older people

2019 ◽  
Vol 53 (4) ◽  
pp. 528-545
Author(s):  
Ponmozhi Chezhiyan ◽  
Deepalakshmi P.
Keyword(s):  
Older People ◽  
Joint Angle ◽  
The Elderly ◽  
Learning System ◽  
Computer Assisted ◽  
World Population ◽  
Joint Angles ◽  
Content Type ◽  
Posture Recognition ◽  
Do So

Purpose United Nations’ World Population Ageing Report states that falls are one of the most common problems in the elderly around the world. Falls are a leading cause of morbidity and mortality among mature adults, and the second leading cause of accidental or unintentional injury/death after road traffic injuries. The rates are higher in hospitalized patients and nursing home residents. Major contributing reasons for falling are loss of footing or traction, balance problem in carpets and rugs, reduced muscle strength, poor vision, mobility/gait, cognitive impairment: in other words lack of balance. Balance can be improved by the practice of yoga which helps to balance both body and mind through a series of physical postures called asanas, breathing control and meditation. Elders, especially women, are often unable to practice yoga regularly, largely brought on by a feeling of discomfort at having to do so in full public view, preferring instead to have private sessions at home, and at leisure. A computer-assisted self-learning system can be developed to help such elders, though improper training and the postures associated with it may harm the body’s muscles and ligaments. To have a flawless system it is essential to classify asanas, and identify the one the practitioner is currently practicing, following which the system can offer the guidance necessary. The purpose of this paper is to propose a posture recognition system, especially of sitting and standing postures. Asanas are chiefly classified into two: sitting and standing postures. This study helps to decide the values of the parameters for classification, which involve the hip and joint angles. Design/methodology/approach To model human bodies, skeleton parts such as head, neck (which are responsible for head movements), arms, hands (to decide on hand postures), and legs and feet (for standing posture identification) have been modeled and stored as a vector. Each feature is defined as a set of movable joints. Every interaction among the skeleton joints defines an action. Human skeletal information may be represented as a hierarchy of joints, in a parent–child relationship. So that whenever there is a change in joint its corresponding parent joint may also be altered. Findings The findings have to do with analyzing the reasons for falls in the elderly and their need for yoga as a precautionary measure. As yoga is ideally suited to self-assisted learning, it is feasible to design a system that assists people who do not wish to practice yoga in public. However, asanas are to be classified prior to doing so. In this paper, the authors have designed a posture identification framework comprising the sitting and standing postures that are fundamental to all yoga asanas, using joint angle measurements. Having fixed joint angle values is not possible, given the variations in angle values among the participants. Consequently, such parameters as the hip joint and knee angles are to be specified in range for a classification of asanas. Research limitations/implications This work identifies the angle limits of standing and sitting postures so as to design a self-assisting system for yoga. Yoga asanas are classified and tested to enable their accurate identification. Extensive testing with older people is needed to assess the system. Practical implications The increase in the population of the elderly, coupled with their need for medical care, is a major concern worldwide. As older people are reluctant to practice yoga in public, it is anticipated that the proposed system will motivate them to do so at their convenience, and in the seclusion of their homes. Social implications As older people are reluctant to adapt as well as practice yoga in public view, the proposal motivates and helps them to carry out yoga practices at their convenience. Originality/value This paper fulfills the initial study on the need and feasibility of creating a self-assisted yoga learning system. To identify postures and classify them joint angles are used; their range of motion has been calculated in order to set them as parameters of classification.

Joint Angle, Velocity, and Range Estimation Using 2D MUSIC and Successive Interference Cancellation in FMCW MIMO Radar System

2020 ◽  
Vol E103.B (3) ◽  
pp. 283-290
Author(s):  
Jonghyeok LEE ◽  
Sunghyun HWANG ◽  
Sungjin YOU ◽  
Woo-Jin BYUN ◽  
Jaehyun PARK
Keyword(s):  
Interference Cancellation ◽  
Joint Angle ◽  
Mimo Radar ◽  
Radar System ◽  
Successive Interference Cancellation ◽  
Range Estimation

Hand posture Recognition for shape variant hands

2011 ◽  
Vol 6 (4) ◽  
pp. 1-6
Author(s):  
Ayesha Butalia ◽  
◽  
A.K. Ramani ◽  
Parag Kulkarni ◽  
Swapnil Patil ◽  
...  
Keyword(s):  
Hand Posture ◽  
Hand Posture Recognition ◽  
Posture Recognition

scholarly journals Genome-Wide Association Studies Based on Equine Joint Angle Measurements Reveal New QTL Affecting the Conformation of Horses

Genes ◽  
2019 ◽  
Vol 10 (5) ◽  
pp. 370 ◽  
Author(s):  
Annik Imogen Gmel ◽  
Thomas Druml ◽  
Rudolf von Niederhäusern ◽  
Tosso Leeb ◽  
Markus Neuditschko
Keyword(s):  
Joint Angle ◽  
Association Studies ◽  
Genome Wide Association ◽  
Cranial Morphology ◽  
Genome Wide Association Studies ◽  
Joint Angles ◽  
Mineral Density ◽  
Mixed Effect ◽  
Stifle Joint ◽  
Genome Wide

The evaluation of conformation traits is an important part of selection for breeding stallions and mares. Some of these judged conformation traits involve joint angles that are associated with performance, health, and longevity. To improve our understanding of the genetic background of joint angles in horses, we have objectively measured the angles of the poll, elbow, carpal, fetlock (front and hind), hip, stifle, and hock joints based on one photograph of each of the 300 Franches-Montagnes (FM) and 224 Lipizzan (LIP) horses. After quality control, genome-wide association studies (GWASs) for these traits were performed on 495 horses, using 374,070 genome-wide single nucleotide polymorphisms (SNPs) in a mixed-effect model. We identified two significant quantitative trait loci (QTL) for the poll angle on ECA28 (p = 1.36 × 10−7), 50 kb downstream of the ALX1 gene, involved in cranial morphology, and for the elbow joint on ECA29 (p = 1.69 × 10−7), 49 kb downstream of the RSU1 gene, and 75 kb upstream of the PTER gene. Both genes are associated with bone mineral density in humans. Furthermore, we identified other suggestive QTL associated with the stifle joint on ECA8 (p = 3.10 × 10−7); the poll on ECA1 (p = 6.83 × 10−7); the fetlock joint of the hind limb on ECA27 (p = 5.42 × 10−7); and the carpal joint angle on ECA3 (p = 6.24 × 10−7), ECA4 (p = 6.07 × 10−7), and ECA7 (p = 8.83 × 10−7). The application of angular measurements in genetic studies may increase our understanding of the underlying genetic effects of important traits in equine breeding.

scholarly journals 602 THE EFFECT OF BILATERAL ISOKINETIC KNEE EXTENSION/FLEXION ON JOINT ANGLE AT PEAK TORQUE

1993 ◽  
Vol 25 (Supplement) ◽  
pp. S108 ◽  
Author(s):  
J. R. Bryant ◽  
L. E. Brown ◽  
M. Whitehurst
Keyword(s):  
Joint Angle ◽  
Peak Torque ◽  
Knee Extension

scholarly journals Force Generation on the Hallux Is More Affected by the Ankle Joint Angle than the Lesser Toes: An In Vivo Human Study

Biology ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 48
Author(s):  
Junya Saeki ◽  
Soichiro Iwanuma ◽  
Suguru Torii
Keyword(s):  
Repeated Measures ◽  
Joint Angle ◽  
Plantar Flexion ◽  
Human Study ◽  
Force Generation ◽  
Functional Difference ◽  
Multiple Comparison Test ◽  
The Difference ◽  
Metatarsophalangeal Joints

The structure of the first toe is independent of that of the other toes, while the functional difference remains unclear. The purpose of this study was to investigate the difference in the force generation characteristics between the plantar-flexion of the first and second–fifth metatarsophalangeal joints (MTPJs) by comparing the maximal voluntary plantar-flexion torques (MVC torque) at different MTPJs and ankle positions. The MVC torques of the first and second–fifth MTPJs were measured at 0°, 15°, 30°, and 45° dorsiflexed positions of the MTPJs, and at 20° plantar-flexed, neutral, and 20° dorsiflexed positions of the ankle. Two-way repeated measures analyses of variance with Holm’s multiple comparison test (MTPJ position × ankle position) were performed. When the MTPJ was dorsiflexed at 0°, 15°, and 30°, the MVC torque of the first MTPJ when the ankle was dorsiflexed at 20° was higher than that when the ankle was plantar-flexed at 20°. However, the ankle position had no significant effect on the MVC torque of the second–fifth MTPJ. Thus, the MVC torque of the first MTPJ was more affected by the ankle position than the second–fifth MTPJs.

scholarly journals Approach to hand posture recognition based on hand shape features for human–robot interaction

2021 ◽  
Author(s):  
Jing Qi ◽  
Kun Xu ◽  
Xilun Ding
Keyword(s):  
Gaussian Mixture ◽  
Human Robot Interaction ◽  
Polar Coordinates ◽  
Support Vector ◽  
Hand Posture ◽  
Data Set ◽  
Hand Shape ◽  
Hand Posture Recognition ◽  
Hand Segmentation ◽  
Posture Recognition

AbstractHand segmentation is the initial step for hand posture recognition. To reduce the effect of variable illumination in hand segmentation step, a new CbCr-I component Gaussian mixture model (GMM) is proposed to detect the skin region. The hand region is selected as a region of interest from the image using the skin detection technique based on the presented CbCr-I component GMM and a new adaptive threshold. A new hand shape distribution feature described in polar coordinates is proposed to extract hand contour features to solve the false recognition problem in some shape-based methods and effectively recognize the hand posture in cases when different hand postures have the same number of outstretched fingers. A multiclass support vector machine classifier is utilized to recognize the hand posture. Experiments were carried out on our data set to verify the feasibility of the proposed method. The results showed the effectiveness of the proposed approach compared with other methods.

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