Flexible software for the elimination of the markers used in the analysis of human posture through kinect®sensor (original) (raw)
Related papers
Journal of Datta Meghe Institute of Medical Sciences University
BACKGROUND: Recognition of human pose is very signi cant in studies involving human computer interactions. Microsoft's Kinect II or Microsoft's Kinect azure sensor in 3D motion capturing systems shows a growing interest in vision-based Human computer interaction as they are low-cost. In this research we introduced and ruled out the e cacy of Microsoft Kinect Azure in evaluation of static coronal Posture in normal healthy population. METHOD: The research has been structured as an observational study. The total of 132 participants will be taken from AVBRH, sawangi Meghe for study as per inclusion and exclusion criteria. With intervention the period of the study will be 6 months. It holds single period, concurrent validity evaluation comparing normal Posture derived from the Kinect system. DISCUSSION: This study protocol aims to evaluate the Validity of evaluation of Normal human posture using Microsoft Kinect Azure. The study's expected outcome will concert on the evaluation of coronal Posture using Microsoft Kinect Azure in normal healthy population.
BMC musculoskeletal disorders, 2018
Clinical examinations are subjective and often show a low validity and reliability. Objective and highly reliable quantitative assessments are available in laboratory settings using 3D motion analysis, but these systems are too expensive to use for simple clinical examinations. Qinematic™ is an interactive movement analyses system based on the Kinect camera and is an easy-to-use clinical measurement system for assessing posture, balance and side-bending. The aim of the study was to test the test-retest the reliability and construct validity of Qinematic™ in a healthy population, and to calculate the minimal clinical differences for the variables of interest. A further aim was to identify the discriminative validity of Qinematic™ in people with low-back pain (LBP). We performed a test-retest reliability study (n = 37) with around 1 week between the occasions, a construct validity study (n = 30) in which Qinematic™ was tested against a 3D motion capture system, and a discriminative va...
The lack of low cost devices apt to collaborate both researches and clinical intervention s quality for health promotion is quite significant, peculiarly in developing countries. The objective of this study consisted in calculating the accuracy of the hardware Kinect™ by Microsoft™. Methods: anthropometric data were collected from a subject in orthostatic position, at four different distances from the optical axes of the hardware, on X, Y and Z. The normality and the variances homogeinity of the data were stated through Kolmogorov-Smirnov and Barlett’s tests, in this order. It has been adopted a significance P < 0.05 for all the statistical tests, and the size effect for all of the spatial coordinates (in the four different placements) exceeded 0.80. Results: the relative error presented no significant differences in all of those distances in the three spatial axels and the accuracy averaged 0.047m; such result allows to conclude that the hardware presents satisfactory both scientific and clinical applicability, embracing potentially human movement investigations and interventions, as well as orthopedics, physiotherapy, physical education, and sports among others.
Assessment of Joint Parameters in a Kinect Sensor Based Rehabilitation Game
2019
A Kinect sensor based basketball game is developed for delivering post-stroke exercises in association with a newly developed elbow exoskeleton. Few interesting features such as audiovisual feedback and scoring have been added to the game platform to enhance patient's engagement during exercises. After playing the game, the performance score has been calculated based on their reachable points and reaching time to measure their current health conditions. During exercises, joint parameters are measured using the motion capture technique of Kinect sensor. The measurement accuracy of Kinect sensor is validated by two comparative studies where two healthy subjects were asked to move elbow joint in front of Kinect sensor wearing the developed elbow exoskeleton. In the first study, the joint information collected from Kinect sensor was compared with the exoskeleton based sensor. In the next study, the length of upperarm and forearm measured by Kinect were compared with the standard anthropometric data. The measurement errors between Kinect and exoskeleton are turned out to be in the acceptable range; 1% for subject 1 and 0.44% for subject 2 in case of joint angle; 5.55% and 3.58% for subject 1 and subject 2 respectively in case of joint torque. The average errors of Kinect measurement as compared to the anthropometric data of the two subjects are 16.52% for upperarm length and 9.87% for forearm length. It shows that Kinect sensor can measure the activity of joint movement with a minimum margin of error.
Kinect-Based Physiotherapy and Assessment: A Comprehensive Review
Indonesian Journal of Electrical Engineering and Computer Science, 2018
Kinect-based physical rehabilitation grows significantly as a mechanism for clinical assessment and rehabilitation due to its flexibility, low-cost and markerless system for human action capture. It is also an approach to provide convenience for for patients’ exercises continuation at home. In this paper, we discuss a review of the present Kinect-based physiotherapy and assessment for rehabilitation patients to provide an outline of the state of art, limitation and issues of concern as well as suggestion for future work in this approach. The paper is constructed into three main parts. The introduction was discussed on physiotherapy exercises and the limitation of current Kinect-based applications. Next, we also discuss on Kinect Skeleton Joint and Kinect Depth Map features that being used widely nowadays. A concise summary with significant findings of each paper had been tabulate for each feature; Skeleton Joints and Depth Map. Afterwards, we assemble a quite number of classificati...
PLOS ONE, 2020
Posturography provides quantitative, objective measurements of human balance and postural control for research and clinical use. However, it usually requires access to specialist equipment to measure ground reaction forces, which are not widely available in practice, due to their size or cost. In this study, we propose an alternative approach to posturography. It uses the skeletal output of an inexpensive Kinect depth camera to localise the Centre of Mass (CoM) of an upright individual. We demonstrate a pipeline which is able to measure postural sway directly from CoM trajectories, obtained from tracking the relative position of three key joints. In addition, we present the results of a pilot study that compares this method of measuring postural sway to the output of a NeuroCom SMART Balance Master. 15 healthy individuals (age: 42.3 ± 20.4 yrs, height: 172 ± 11 cm, weight: 75.1 ± 14.2 kg, male = 11), completed 25 Sensory Organisation Test (SOT) on a NeuroCom SMART Balance Master. Simultaneously, the sessions were recorded using custom software developed for this study (CoM path recorder). Postural sway was calculated from the output of both methods and the level of agreement determined, using Bland-Altman plots. Good agreement was found for eyes open tasks with a firm support, the agreement decreased as the SOT tasks became more challenging. The reasons for this discrepancy may lie in the different approaches that each method takes to calculate CoM. This discrepancy warrants further study with a larger cohort, including fall-prone individuals, cross-referenced with a marker-based system. However, this pilot study lays the foundation for the development of a portable device, which could be used to assess postural control, more cost-effectively than existing equipment.
Accuracy evaluation of the Kinect v2 sensor during dynamic movements in a rehabilitation scenario
— In this paper, the accuracy evaluation of the Kinect v2 sensor is investigated in a rehabilitation scenario. The accuracy analysis is provided in terms of joint positions and angles during dynamic postures used in low-back pain rehabilitation. Although other studies have focused on the validation of the accuracy in terms of joint angles and positions, they present results only considering static postures whereas the rehabilitation exercise monitoring involves to consider dynamic movements with a wide range of motion and issues related to the joints tracking. In this work, joint positions and angles represent clinical features, chosen by medical staff, used to evaluate the subject's movements. The spatial and temporal accuracy is investigated with respect to the gold standard, represented by a stereophotogrammetric system, characterized by 6 infrared cameras. The results provide salient information for evaluating the reliability of Kinect v2 sensor for dynamic postures.
Reliability of Kinect measurements for assessing the movement of operators in ergonomic studies
Analyzing human poses at workstations is a key issue in ergonomics in order to evaluate potentials risks of musculoskeletal disorders. Kinect looks promising in measuring 3D joint kinematics on site but few studies have estimated the accuracy of the kinematic data delivered by this sensor in real situations. Thus, this study aims at evaluating the accuracy of the Kinect sensor for work-related motions. To this end we compared ISB Euler joint angles estimated with a Kinect to those obtained with a wellestablished marker-based device. Several repetitions of four of the main manual tasks described in MTM-2 classification were performed. Results showed that the RMSE between the data obtained with the two systems were 11(±3)° and 25(±4)° for the shoulder and the elbow joints respectively. Moreover, the measurement error was not randomly distributed but strongly depended on the joint configuration. Better knowledge on the Kinect measurement errors should help scientists and engineers to design appropriate protocols to measure joint kinematics in ergonomic assessments with this promising device.
Statistical Validation for Clinical Measures: Repeatability and Agreement of Kinect™-Based Software
BioMed research international, 2018
The rehabilitation process is a fundamental stage for recovery of people's capabilities. However, the evaluation of the process is performed by physiatrists and medical doctors, mostly based on their observations, that is, a subjective appreciation of the patient's evolution. This paper proposes a tracking platform of the movement made by an individual's upper limb using Kinect sensor(s) to be applied for the patient during the rehabilitation process. The main contribution is the development of quantifying software and the statistical validation of its performance, repeatability, and clinical use in the rehabilitation process. The software determines joint angles and upper limb trajectories for the construction of a specific rehabilitation protocol and quantifies the treatment evolution. In turn, the information is presented via a graphical interface that allows the recording, storage, and report of the patient's data. For clinical purposes, the software information ...