Kinect v2 tracked Body Joint Smoothing for Kinematic Analysis in Musculoskeletal Disorders
01 Jul 2020-Vol. 2020, pp 5769-5772
TL;DR: This work proposes a filter combined with the concept of body kinematics to remove noise and enhances the quality of 3D coordinates in body frame data and compares Range of Motion (RoM) values obtained from the proposed filter with the gold standard goniometry.
Abstract: Body joint monitoring is essential for disorder diagnosis and assessment of treatment effectiveness. Microsoft Kinect v2 is a low-cost and markerless human motion-tracking RGB-D sensor that provides spatial locations of tracked skeletal joints in the form of 3D coordinates. Sometimes, body tracking of kinect v2 produces erratic 3D coordinates, which affects the real-time tracking performance of the sensor. A careful study of the literature suggests that skeletal tracking of kinect v2 needs further exploration. This work proposes a filter combined with the concept of body kinematics to remove noise and enhances the quality of 3D coordinates in body frame data. Also, it generates "Motion Signature" of the tracked joint, which shows movement pattern for kinematic analysis, and helpful in joint monitoring of Musculoskeletal Disorders (MSD). The clinically relevant anatomical movement was executed, to evaluate the performance of the proposed filter. We compared Range of Motion (RoM) values obtained from the proposed filter with the gold standard goniometry. Results indicate that RoM values from the proposed filter are in high correlation with the goniometry with an Intraclass Correlation Coefficient values ranging between 0.95 to 0.98 authenticating that it improves the skeletal joint tracking of kinect v2.
Citations
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TL;DR: The results indicated that the HumanTrak system is an objective, valid and reliable way to assess and track shoulder ROM.
Abstract: Background: Objective assessment of shoulder joint active range of motion (AROM) is critical to monitor patient progress after conservative or surgical intervention. Advancements in miniature devices have led researchers to validate inertial sensors to capture human movement. This study investigated the construct validity as well as intra- and inter-rater reliability of active shoulder mobility measurements using a coupled system of inertial sensors and the Microsoft Kinect (HumanTrak). Methods: 50 healthy participants with no history of shoulder pathology were tested bilaterally for fixed and free ROM: (1) shoulder flexion, and (2) abduction using HumanTrak and goniometry. The repeat testing of the standardised protocol was completed after seven days by two physiotherapists. Results: All HumanTrak shoulder movements demonstrated adequate reliability (intra-class correlation (ICC) ≥ 0.70). HumanTrak demonstrated higher intra-rater reliability (ICCs: 0.93 and 0.85) than goniometry (ICCs: 0.75 and 0.53) for measuring free shoulder flexion and abduction AROM, respectively. Similarly, HumanTrak demonstrated higher intra-rater reliability (ICCs: 0.81 and 0.94) than goniometry (ICCs: 0.70 and 0.93) for fixed flexion and abduction AROM, respectively. Construct validity between HumanTrak and goniometry was adequate except for free abduction. The differences between raters were predominately acceptable and below ±10°. Conclusions: These results indicated that the HumanTrak system is an objective, valid and reliable way to assess and track shoulder ROM.
12 citations
Cites methods from "Kinect v2 tracked Body Joint Smooth..."
...[46] compared the Kinect (v2) and goniometry and reported a high correlation for ROM measurements with ICC values ranging between 0....
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TL;DR: Wang et al. as mentioned in this paper proposed an indoor landscape reconstruction method based on VR (virtual reality) and drew indoor landscape information and images by using VR technology to generate an indoor landscapes reconstruction panorama.
Abstract: Indoor three-dimensional layout has a strong application background, such as virtual office three-dimensional layout planning, museum three-dimensional layout planning, and cave scene three-dimensional layout planning, which have been widely used in telecommuting, education, tourism, and other industries. In view of this, this paper proposes an indoor landscape reconstruction method based on VR (virtual reality) and draws indoor landscape information and images by using VR technology to generate an indoor landscape reconstruction panorama. A model is established to correct the distance error and reflectivity error of depth image, improve the accuracy of the depth image, and finally improve the accuracy of three-dimensional indoor scene TDR (three-dimensional reconstruction). In the process of optimizing layout, the Monte Carlo sampling method is used based on the Markov chain, and constraints are used as density functions to guide layout sampling and generate a number of reasonable scene layout suggestions in the iterative process of the sampler. Experiments show that this method can provide scientific and reasonable guidance to users' scene layout and help them complete the furniture layout quickly.
3 citations
1 citations
17 Oct 2022
TL;DR: In this article , the authors define possible approaches for processing raw signals, paying attention to the type of noise that can afflict the signal, in order to better analyze a patient's performance during motor activity, obtained through biomedical instrumentation and/or digital technologies.
Abstract: In the field of tele-rehabilitation, to better analyze a patient’s performance during motor activity, obtained through biomedical instrumentation and/or digital technologies, it is necessary to process and evaluate the signals extracted from the various sensors employed. In the literature there is often a lack of in-depth studies regarding such approaches and methodologies of signal processing. The purpose of the present paper is to define possible approaches for processing raw signals, paying attention to the type of noise that can afflict the signal. In the application of the ReMoVES IoT system, a procedure is here proposed and applied to analyze the signals coming from the Microsoft Kinect sensor, which is used to detect upper limb movements while performing the exercise, in order to study the behavior of a group of healthy subjects, and compare it with the performance of a patient who first performed a training phase in an inpatient setting and then for about a month, a treatment plan at home.
References
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TL;DR: Wearable systems are a promising solution to provide quantitative and meaningful clinical information about progress in a rehabilitation pathway and to extrapolate meaningful parameters in the diagnosis of shoulder pathologies.
Abstract: Wearable sensors are acquiring more and more influence in diagnostic and rehabilitation field to assess motor abilities of people with neurological or musculoskeletal impairments. The aim of this systematic literature review is to analyze the wearable systems for monitoring shoulder kinematics and their applicability in clinical settings and rehabilitation. A comprehensive search of PubMed, Medline, Google Scholar and IEEE Xplore was performed and results were included up to July 2019. All studies concerning wearable sensors to assess shoulder kinematics were retrieved. Seventy-three studies were included because they have fulfilled the inclusion criteria. The results showed that magneto and/or inertial sensors are the most used. Wearable sensors measuring upper limb and/or shoulder kinematics have been proposed to be applied in patients with different pathological conditions such as stroke, multiple sclerosis, osteoarthritis, rotator cuff tear. Sensors placement and method of attachment were broadly heterogeneous among the examined studies. Wearable systems are a promising solution to provide quantitative and meaningful clinical information about progress in a rehabilitation pathway and to extrapolate meaningful parameters in the diagnosis of shoulder pathologies. There is a strong need for development of this novel technologies which undeniably serves in shoulder evaluation and therapy.
54 citations
TL;DR: The results suggest that the Kinect is a viable tool for general biomechanical research, with specific limits on what levels of performance can be expected under various conditions.
45 citations
"Kinect v2 tracked Body Joint Smooth..." refers background in this paper
...[9], but reported lower skeletal joint angle accuracy with respect to Qualisys, which is a multiple cameras based motion tracking system....
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TL;DR: Low-cost, automated motion analysis may be acceptable to screen for moderate to severe motion impairments in active shoulder motion and Automatic detection of motion limitation may allow quick screening to be performed in an oncologist's office and trigger timely referrals for rehabilitation.
Abstract: Objective
To determine if a low-cost, automated motion analysis system using Microsoft Kinect could accurately measure shoulder motion and detect motion impairments in women following breast cancer surgery.
Design
Descriptive study of motion measured via 2 methods.
Setting
Academic cancer center oncology clinic.
Participants
20 women (mean age = 60 yrs) were assessed for active and passive shoulder motions during a routine post-operative clinic visit (mean = 18 days after surgery) following mastectomy (n = 4) or lumpectomy (n = 16) for breast cancer.
Interventions
Participants performed 3 repetitions of active and passive shoulder motions on the side of the breast surgery. Arm motion was recorded using motion capture by Kinect for Windows sensor and on video. Goniometric values were determined from video recordings, while motion capture data were transformed to joint angles using 2 methods (body angle and projection angle).
Main Outcome Measure
Correlation of motion capture with goniometry and detection of motion limitation.
Results
Active shoulder motion measured with low-cost motion capture agreed well with goniometry (r = 0.70–0.80), while passive shoulder motion measurements did not correlate well. Using motion capture, it was possible to reliably identify participants whose range of shoulder motion was reduced by 40% or more.
Conclusions
Low-cost, automated motion analysis may be acceptable to screen for moderate to severe motion impairments in active shoulder motion. Automatic detection of motion limitation may allow quick screening to be performed in an oncologist's office and trigger timely referrals for rehabilitation.
17 citations
Additional excerpts
...98, which show excellent reliability of proposed filter’s result as compared with [14] and [15]....
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28 May 2017
TL;DR: This work proposes a novel approach to constrain a standard Kalman filter, based on the dynamics of individual joints, in order to keep the distance between any two physically connected joints constant over time.
Abstract: Microsoft Kinect has the huge potential to be used in home-based rehabilitation and clinical assessments for patients suffering from stroke or other neurological disorder, due to its affordability and unobtrusiveness in analysing joint kinematics. However, skeleton data obtained from Kinect Xbox 360 (Kinect 1) or Kinect Xbox One (Kinect 2) are usually noisy which affects accuracy of estimation of three dimensional joint locations. The noise profile varies for both stationary and dynamic postures and it affects anthropometric measurements of the body segments connecting any two joints. We propose a novel approach to constrain a standard Kalman filter, based on the dynamics of individual joints, in order to keep the distance between any two physically connected joints (namely bone length) constant over time. Our constrained Kalman filter method not only tracks the joints accurately but also reduces the variation in bone lengths by 92% and 94% for Kinect 2 and 1 respectively.
15 citations
"Kinect v2 tracked Body Joint Smooth..." refers background in this paper
...The body tracking of kinect v2 provides noisy skeletal data that affect sensor’s precision and tracking performance [11]....
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01 Aug 2015
TL;DR: The idea behind this work is to attempt to tackle the problem of gesture movement of the human body using Microsoft Kinect sensor by using Holt exponential smoothing filter.
Abstract: One of the most imperative research areas in the field of Human Computer Interaction (HCI) is gesture recognition as it provides a natural and spontaneous way to communicate between people and machines. Gesture based applications range from computer games to virtual augmented reality and is recently being explored in other fields. The idea behind this work is to attempt to tackle the problem of gesture movement of the human body using Microsoft Kinect sensor. The skeletal tracking (ST) system of the Natural User Interface (NUI) provides joint positions of tracked persons skeletons. These joint positions are the data consumed as position and pose, and they are used for many purposes, such as gesture detection, navigating user interfaces, and so on. The filter method used is Holt exponential smoothing filter. This filter smooth out the jitter, adds the capability to continue tracking for a short period of time when the subject moves out of range of the sensor, and improves the accuracy of the tracking by incorporating the information.
7 citations
"Kinect v2 tracked Body Joint Smooth..." refers background in this paper
...[7] have proposed holt exponential smoothing filter [8] to smooth jitters present in tracked skeletal joints for gesture recognition in NUI based applications....
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