Filtering motion signals from Microsoft Kinect® in the context of stroke rehabilitation

Moreira, Gabrielly Marques; Giovanini, Luiz H. F.; Castro, Marcos P. R. de; Nogueira, G. N.; Boumer, Tatiane Caroline; Manffra, Elisängela Ferretti

doi:10.1007/s42600-019-00029-8

Cited by 3 publications

(2 citation statements)

References 6 publications

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“…Several studies have demonstrated that Kalman filter has achieved the best denoising performance when compared to other filter-based approaches [14]. Other types of filters such as double exponential smoothing filter [65], median filtering [67], fourth-order low-pass Butterworth filter [40]. also have been used.…”

Section: Related Workmentioning

confidence: 99%

Multiple Kinect based system to monitor and analyze key performance indicators of physical training

Ryselis

Petkus²,

Blažauskas

et al. 2020

Hum. Cent. Comput. Inf. Sci.

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Using a single Kinect device for human skeleton tracking and motion tracking lacks of reliability required in sports medicine and rehabilitation domains. Human joints reconstructed from non-standard poses such as squatting, sitting and lying are asymmetric and have unnatural lengths while their recognition error exceeds the error of recognizing standard poses. In order to achieve higher accuracy and usability for practical smart health applications we propose a practical solution for human skeleton tracking and analysis that performs the fusion of skeletal data from three Kinect devices to provide a complete 3D spatial coverage of a subject. The paper describes a novel data fusion algorithm using algebraic operations in vector space, the deployment of the system using three Kinect units, provides analysis of dynamic characteristics (position of joints, speed of movement, functional working envelope, body asymmetry and the rate of fatigue) of human motion during physical exercising, and evaluates intra-session reliability of the system using test–retest reliability metrics (intra-class correlation, coefficient of variation and coefficient of determination). Comparison of multi-Kinect system vs single-Kinect system shows an improvement in accuracy of 15.7%, while intra-session reliability is rated as excellent.

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Section: Related Workmentioning

confidence: 99%

Multiple Kinect based system to monitor and analyze key performance indicators of physical training

Ryselis

Petkus²,

Blažauskas

et al. 2020

Hum. Cent. Comput. Inf. Sci.

View full text Add to dashboard Cite

show abstract

“…Various studies have showed good accuracy in human upper limb motion tracking based on inertial measurement unit [10,17]. In addition, some gaming sensors have been used in the human motion analysis and rehabilitation assessment including Microsoft Kinect [18][19][20][21], and Nintendo Wii and Sony Move [22,23].…”

Section: Introductionmentioning

confidence: 99%

A Sensor Based Assessment Monitoring System for Patients with Neurological Disabilities

Bai

2021

jrc

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The neurological conditions can cause the disability of upper limb and the rehabilitation therapy can help the patients to restore their upper limb motion. However, the current method for upper limb rehabilitation assessment is very basic. The aim of this work is to develop a system and visualize the information to support the doctors and clinicians in the assessment of upper limb motion of patients who are undertaken neurological rehabilitation. Movement tracking including position and orientation have been tracked and data analysis have been done in both time domain and frequency domain. Furthermore, movement smoothness analysis has been done to obtain more information from patients' movement recovery. The created information visualization can provide objective measurements of patients' motion recovery and insightful information and for doctors and clinicians including the frequency analysis and movement smoothness analysis. The findings showed the system is able to provide accurate position within 0.1 cm and orientation tracking within 1 degree and meaningful insights for the assessment of upper limb motion functions in daily rehabilitation assessment by providing doctors and clinicians with visualizations of the objective measurements.

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Strategies Adopted by Stroke Patients to Maintain Balance in Dynamic Tasks in a Video Game

Moreira

Scrok

Loureiro

et al. 2023

Journal of Motor Behavior

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Filtering motion signals from Microsoft Kinect® in the context of stroke rehabilitation

Cited by 3 publications

References 6 publications

Multiple Kinect based system to monitor and analyze key performance indicators of physical training

Multiple Kinect based system to monitor and analyze key performance indicators of physical training

A Sensor Based Assessment Monitoring System for Patients with Neurological Disabilities

Strategies Adopted by Stroke Patients to Maintain Balance in Dynamic Tasks in a Video Game

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