Skeleton-Based Abnormal Gait Detection

Nguyen, Trong-Nguyen; Huynh, Huu-Hung; Meunier, Jean

doi:10.3390/s16111792

Cited by 63 publications

(93 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The notation N indicates normal gaits, L and R respectively represent left and right legs, and v i is the i th volunteer. Method [14] was employed to deal with the former data type. That study separated an input sequence of skeletons into consecutive gait cycles detected using the distance between two foot joints.…”

Section: Comparison With Other Related Methodsmentioning

confidence: 99%

“…Similarly to related studies on gait analysis (e.g. [4,14,2,10]), the assessment of gait symmetry in our system also considers the temporal factor. Concretely, the value measuring the gait symmetry is estimated on a sequence of consecutive histograms.…”

Section: Gait Symmetry Assessmentmentioning

confidence: 99%

“…There are several reasons leading to our choice: (1) gait cycle determination would be difficult to perform when working on pathological gaits, (2) the symmetry can be measured well by dealing with the mentioned shifting on an arbitrary (long enough) sequence of histograms, and (3) sub-sequences do not need to have common properties (e.g. similar beginning and ending postures as in [14] or [2]) because we do not focus on training a model representing the gait. Each sub-sequence is then separated into two sequences of left and right sub-histograms.…”

Section: Gait Symmetry Assessmentmentioning

confidence: 99%

“…Beside its low price, this camera provides a builtin functionality of human skeleton localization, estimated in each single depth frame [18,19]. Such skeletal information is useful for gait-related problems such as abnormal gait detection [14], gaitbased recognition [8], and pathological gait analysis [5]. A limitation of skeleton-based approaches is that the skeleton may be deformed due to self-occlusions in the depth map.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Human gait symmetry assessment using a depth camera and mirrors

Nguyen

Huynh

Meunier

2018

Computers in Biology and Medicine

Self Cite

View full text Add to dashboard Cite

It is proposed in this paper a reliable approach for human gait symmetry assessment using a Time-of-Flight (ToF) depth camera and two mirrors. The setup formed from these devices provides a sequence of 3D point clouds that is the input of our system. A cylindrical histogram is estimated for describing the posture in each point cloud. The sequence of such histograms is then separated into two sequences of sub-histograms representing two half-bodies. A cross-correlation technique is finally applied to provide values describing gait symmetry indices. The evaluation was performed on 9 different gait types to demonstrate the ability of our approach in assessing gait symmetry. A comparison between our system and related methods, that employ different input data types, is also provided.

show abstract

Section: Comparison With Other Related Methodsmentioning

confidence: 99%

Section: Gait Symmetry Assessmentmentioning

confidence: 99%

Section: Gait Symmetry Assessmentmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Human gait symmetry assessment using a depth camera and mirrors

Nguyen

Huynh

Meunier

2018

Computers in Biology and Medicine

Self Cite

View full text Add to dashboard Cite

show abstract

“…This technique is selected to perform a comparison because it was employed to solve many problems related to temporal information (e.g. gait assessment [27], [28]). …”

Section: The Set Of Observationsmentioning

confidence: 99%

Dynamic Gesture Classification for Vietnamese Sign Language Recognition

Vo¹,

Huynh²,

Doan³

et al. 2017

ijacsa

Self Cite

View full text Add to dashboard Cite

Abstract-This paper presents an approach of feature extraction and classification for recognizing continuous dynamic gestures corresponding to Vietnamese Sign Language (VSL). Input data are captured by the depth sensor of a Microsoft Kinect, which is almost not affected by the light of environment. In detail, each gesture is represented by a volume corresponding to a sequence of depth images. The feature extraction stage is performed by dividing such volume into a 3D grid of same-size blocks in which each one is then converted into a scalar value. This step is followed by the process of classification. The wellknown method Support Vector Machine (SVM) is employed in this work, and the Hidden Markov Model (HMM) technique is also applied in order to provide a comparison on recognition accuracy. Besides, a dataset of 3000 samples corresponding to 30 dynamic gestures in VSL was created by 5 volunteers. The experiments on this dataset to validate the approach and that shows the promising results with average accuracy up to 95%.

show abstract

Abnormal gait recognition using exemplar based algorithm in healthcare applications

Sivarathinabala

Abirami

Baskaran

2020

Int J Communication

View full text Add to dashboard Cite

SummaryIn healthcare applications, gait plays a major role in identification of the normal or abnormal person in different situations. Human gait refers to the walking style of the person, and it may also refer as locomotion using human limbs. The abnormal gait has irregular patterns of stance and swing phases. Without any clinical impairment, this paper proposes a novel approach to classify the person as normal or the person as suffering from neurological disorders from the videos using their gait videos. In addition, neurological gait disorders such as Parkinson gait, hemiplegic gait, and neuropathic gait has been identified using the gait features. Many systems are designed to detect and identify gait disorders using head, hip, heel, and toe behavior analysis from the bidirectional gait videos. As motivated by previous mechanisms, this paper proposes a novel vision based algorithm to recognize the gait abnormalities using model free approaches and significant feature vector generation from complete silhouette images of one gait cycle of a person. Here, a lean angle and ramp angle are considered as distinguishing and prominent features, and the results of these features are properly classified into normal or abnormal gait through the design of an unsupervised classifier.

show abstract

Skeleton-Based Abnormal Gait Detection

Cited by 63 publications

References 19 publications

Human gait symmetry assessment using a depth camera and mirrors

Human gait symmetry assessment using a depth camera and mirrors

Dynamic Gesture Classification for Vietnamese Sign Language Recognition

Abnormal gait recognition using exemplar based algorithm in healthcare applications

Contact Info

Product

Resources

About