Kinect-enabled home-based rehabilitation system using Dynamic Time Warping and fuzzy logic

Su, Chuan‐Jun; Chiang, Chang-Yu; Jingyan, Huang

doi:10.1016/j.asoc.2014.04.020

Cited by 124 publications

(90 citation statements)

References 16 publications

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“…The Kinect is also being used for the assess ment of postural control [30], gait [31], balance [3], static foot posture [32], body sway [33], and common motor movements [34], all with promising comparisons to three-dimensional gold standard systems. The use of the Kinect as a rehabilitation tool outside of the clinic and in the home [35][36][37] suggests the sensor's portability and supports the recommendation of previous research to incorporate assessment throughout the continuum of care [38].…”

Section: Microsoft Kinectmentioning

confidence: 53%

Reliability and validity of the Microsoft Kinect for assessment of manual wheelchair propulsion

Milgrom¹,

OTD²,

Foreman³

et al. 2016

J Rehabil Res Dev

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Abstract-Concurrent validity and test-retest reliability of the Microsoft Kinect in quantification of manual wheelchair pro pulsion were examined. Data were collected from five manual wheelchair users on a roller system. Three Kinect sensors were used to assess test-retest reliability with a still pose. Three sys tems were used to assess concurrent validity of the Kinect to measure propulsion kinematics (joint angles, push loop charac teristics): Kinect, Motion Analysis, and Dartfish ProSuite (Dart fish joint angles were limited to shoulder and elbow flexion). Intraclass correlation coefficients (ICCs) revealed good reliabil ity (0.87-0.99) between five of the six joint angles (neck flexion, shoulder flexion, shoulder abduction, elbow flexion, wrist flexion). ICCs suggested good concurrent validity for elbow flexion between the Kinect and Dartfish and between the Kinect and Motion Analysis. Good concurrent validity was revealed for maximum height, hand-axle relationship, and maximum area (0.92-0.95) between the Kinect and Dartfish and maxi mum height and hand-axle relationship (0.89-0.96) between the Kinect and Motion Analysis. Analysis of variance revealed sig nificant differences (p < 0.05) in maximum length between Dartfish (mean 58.76 cm) and the Kinect (40.16 cm). Results pose promising research and clinical implications for propul sion assessment and overuse injury prevention with the applica tion of current findings to future technology.

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Section: Microsoft Kinectmentioning

confidence: 53%

Reliability and validity of the Microsoft Kinect for assessment of manual wheelchair propulsion

Milgrom¹,

OTD²,

Foreman³

et al. 2016

J Rehabil Res Dev

View full text Add to dashboard Cite

show abstract

“…The image database used for the experiment consists of various images captured by cameras in different types of indoor and outdoor circumstances without any specific constraint conditions. The cameras used in this study are the Bumblebee 2 of Pointgrey [29] as a stereo camera, Kinect 2 of Microsoft as a TOF camera [15], and WMK-H302 of Wonwoo Engineering as an infrared camera [30]. In the different circumstances of illumination, edge, and distance, the proposed imageswitching algorithm was applied to the experiment of this study.…”

Section: Resultsmentioning

confidence: 99%

“…In the case of the time delay method using a laser, such a sensor is a one-dimensional sensor type to obtain distance information at one point of the real world through one measurement. In this case, multiple measurements are required to expand two-dimensionally or three-dimensionally [15].…”

Section: Related Workmentioning

confidence: 99%

A Multiple Feature-Based Image-Switching Strategy in Visual Sensor Networks

Jang

Kim

2015

International Journal of Distributed Sensor Networks

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Generally, one fixed camera is used to take still or dynamic images and extract proper information from the captured images. However, the process of analyzing images through the use of one camera is very sensitive to neighboring environmental factors, such as illumination, background, and noise; thus, it is hard to guarantee precision. To extract proper information from images more precisely in visual sensor networks, this paper proposes an image-switching strategy where, among different types of installed cameras, the one camera best suited to neighboring circumstances is chosen. The proposed strategy is to first receive initial images as input data and then extract multiple features representing neighboring circumstances from the input images. Subsequently, it is to define the neighboring circumstances metric, which is the weighted sum of the extracted features, and to dynamically switch cameras to obtain images in accordance with the neighboring circumstances. The results of the experiment show that the proposed dynamic switching strategy reliably chooses, from among different cameras, the one camera that is best suited to the neighboring circumstances.

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“…The choice of pattern recognition algorithm is often determined by the choice of features set and vice-versa. In case of motion representation with the constant length, in which each action has same number of representation features, no matter how many samples original recording has, authors reports using popular classifiers like for example support vector machines [44], neural networks [32] or even nearest-neighbor [63,70]. When the continues data stream of MoCap signal classified (like it is in our case) the HMM [26,45] and DTW [3,63] are most common approaches.…”

Section: Application For Human Actions Recognitionmentioning

confidence: 99%

Averaging of motion capture recordings for movements’ templates generation

Hachaj

Koptyra

Ogiela

2018

Multimed Tools Appl

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In this paper we propose, describe and evaluate the novel motion capture (MoCap) data averaging framework. It incorporates hierarchical kinematic model, angle coordinates' preprocessing methods, that recalculate the original MoCap recording making it applicable for further averaging algorithms, and finally signals averaging processing. We have tested two signal averaging methods namely Kalman Filter (KF) and Dynamic Time Warping barycenter averaging (DBA). The propose methods have been tested on MoCap recordings of elite Karate athlete, multiple champion of Oyama karate knockdown kumite who performed 28 different karate techniques repeated 10 times each. The proposed methods proved to have not only high effectiveness measured with root-mean-square deviation (4.04 ± 5.03 degrees for KF and 5.57 ± 6.27 for DBA) and normalized Dynamic Time Warping distance (0.90 ± 1.58 degrees for KF and 0.93 ± 1.23 for DBA), but also the reconstruction and visualization of those recordings persists all crucial aspects of those complicated actions. The proposed methodology has many important applications in classification, clustering, kinematic analysis and coaching. Our approach generates an averaged full body motion template that can be practically used for example for human actions Multimed Tools Appl (2018) 77:30353-30380 recognition. In order to prove it we have evaluated templates generated by our method in human action classification tasks using DTW classifier. We have made two experiments. In first leave -one -out cross -validation we have obtained 100% correct recognitions. In second experiment when we classified recordings of one person using templates of another recognition rate 94.2% was obtained.

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Kinect-enabled home-based rehabilitation system using Dynamic Time Warping and fuzzy logic

Cited by 124 publications

References 16 publications

Reliability and validity of the Microsoft Kinect for assessment of manual wheelchair propulsion

Reliability and validity of the Microsoft Kinect for assessment of manual wheelchair propulsion

A Multiple Feature-Based Image-Switching Strategy in Visual Sensor Networks

Averaging of motion capture recordings for movements’ templates generation

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