Human Arm Motion Tracking by Orientation-Based Fusion of Inertial Sensors and Kinect Using Unscented Kalman Filter

Atrsaei, Arash; Salarieh, Hassan; Alasty, Aria

doi:10.1115/1.4034170

Cited by 38 publications

(23 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In order to gain accurate result, muscle length should be performed when the patient is not in acute pain in order to avoid pain inhibition and muscle guarding [15]. Goniometer or a tape can be used to do the measurements and there are four steps in performing muscle length analysis [16].…”

Section: Muscle Length Analysismentioning

confidence: 99%

A Novel Musculoskeletal Imbalance Identification Mechanism for Lower Body Analyzing Gait Cycle by Motion Tracking

Tennakoon¹,

Paranamana²,

Weerasinghe³

et al. 2018

IJITCS

View full text Add to dashboard Cite

Abstract-Muscles in a human body consists of a pair. Musculoskeletal imbalances caused by repetitive usage of one part of the muscle in this pair and incorrect posture a human body takes on regular basis lead to severe injuries in terms of neuro musculoskeletal problems, hamstring strains, lower back tightness, repetitive stress injuries, altered movement patterns, postural dysfunctions, trapped nerves and etc. and both neurological and physical performances are severely affected when time progresses. In clinical domain, muscle imbalances are determined by gait and posture analysis, Movement analysis, Joint range of motion analysis and muscle length analysis which require expertise knowledge and experience. X-Rays and CT scans in the medical domain also require domain experts to interpret the results of a checkup. Kinect is a motion capturing device which is able to track human skeleton, its joints and body movements within its sensory range. The purpose of this research is to provide a mechanism to identify muscle imbalances based on gait analysis tracked via Kinect motion capture device by differentiate the deviation of healthy person's gait patterns. Primarily, the outcome of this study will be a self-identification method of human skeletal imbalance.

show abstract

Section: Muscle Length Analysismentioning

confidence: 99%

A Novel Musculoskeletal Imbalance Identification Mechanism for Lower Body Analyzing Gait Cycle by Motion Tracking

Tennakoon¹,

Paranamana²,

Weerasinghe³

et al. 2018

IJITCS

View full text Add to dashboard Cite

show abstract

“…In total 19 local coordinate systems (LCS), following ISB recommendations [27] for axis orientation, were located in the origins indicated by numbers (1)(2)(3)(4)(5)(6)(7)(8)(9)(10)(11)(12)(13)(14)(15)(16)(17)(18)(19) in Figure 1. Then 33 LCSs origin motions relative to parent LCSs (Table 1) Each of 33 trajectory plots was processed to assess different properties of the shape created by hodograph.…”

Section: Methodsmentioning

confidence: 99%

“…Some solutions have been proposed to increase the quality of the results such a fusing the data from the Kinect and accelerometers [18], modifying the placement of the sensor according to the type of measurements [19,20], fuse the data form multiple Kinect [21] or develop new algorithms of skeleton detection based on raw data [22].…”

Section: Introductionmentioning

confidence: 99%

3D Analysis of Upper Limbs Motion During Rehabilitation Exercises Using the Kinect<sup>TM</sup> Sensor: Development, Laboratory Validation and Clinical Application

Bonnechère

Sholukha

Omelina

et al. 2018

Preprint

View full text Add to dashboard Cite

Optoelectronic devices are gold standard for 3D evaluation in clinics but due to the complexity of such kind of hardware and the lack of access for patients affordable, transportable and easy to use systems must be developed to be largely used in daily clinics. The Kinect TM sensor presents various advantages compared to optoelectronic devices: price, transportability but also some limitations: (in)accuracy of the skeleton detection and tracking as well as the limited amount of available points that make 3D evaluation impossible. To overcome these limitations a novel method has been developed to perform 3D evaluation of the upper limbs. This system is coupled to rehabilitation exercises allowing functional evaluation while performing physical rehabilitation. To validate this new approach a double step method was used. The first step is a laboratory validation where the results obtained with the Kinect TM have been compared with results obtained with an optoelectronic device, 40 healthy young adults participated in this first part. The second step was to determine the clinical relevance of such kind of measurement. Results of the healthy subjects were compared with a group of 22 elderly adults and a group of 10 chronic stroke patients to determine if different patterns can be observed. The new methodology and the different steps of the validations are presented in this paper.

show abstract

“…We simulate the process noise w and measurement noise v with random functions. Then, the simulated parameters go through the parallel plant model based on the state-space model described in Equations (12) and (13). The true output of the model is y, the measurement with measurement noise is y n , and the estimation using the Kalman filter is y e .…”

Section: Simulation With An Artificial Signalmentioning

confidence: 99%

“…The true output of the model is y, the measurement with measurement noise is y n , and the estimation using the Kalman filter is y e . Equations (12) and (13). The true output of the model is y , the measurement with measurement noise is n y , and the estimation using the Kalman filter is e y .…”

Section: Simulation With An Artificial Signalmentioning

confidence: 99%

A Fruit Fly-Optimized Kalman Filter Algorithm for Pushing Distance Estimation of a Hydraulic Powered Roof Support through Tuning Covariance

et al. 2016

View full text Add to dashboard Cite

Abstract:To measure the pushing distance of a hydraulic-powered roof support, and reduce the cost from a non-reusable displacement sensor embedded in pushing a hydraulic cylinder, an inertial sensor is used to measure the pushing distance, and a Kalman filter is applied to process the inertial data. To obtain better estimation performance, an improved fruit fly optimization algorithm (IFOA) is proposed to tune the parameters of the Kalman filter, processing noise covariance Q and observation noise covariance R. The key procedures of the proposed method, including state-space model, fitness function, and Kalman filter implementation, are presented. Finally, an artificial signal is utilized to verify the feasibility of the proposed method, and the tuning results of other algorithms, particle swarm optimization (PSO), genetic algorithm (GA), basic FOA, and 3D-FOA are compared. The proposed method is also applied in the pushing distance estimation scenario. The simulation and application results prove the effectiveness and superiority of the proposed method.

show abstract

Human Arm Motion Tracking by Orientation-Based Fusion of Inertial Sensors and Kinect Using Unscented Kalman Filter

Cited by 38 publications

References 20 publications

A Novel Musculoskeletal Imbalance Identification Mechanism for Lower Body Analyzing Gait Cycle by Motion Tracking

A Novel Musculoskeletal Imbalance Identification Mechanism for Lower Body Analyzing Gait Cycle by Motion Tracking

3D Analysis of Upper Limbs Motion During Rehabilitation Exercises Using the Kinect<sup>TM</sup> Sensor: Development, Laboratory Validation and Clinical Application

A Fruit Fly-Optimized Kalman Filter Algorithm for Pushing Distance Estimation of a Hydraulic Powered Roof Support through Tuning Covariance

Contact Info

Product

Resources

About