2D Markerless Gait Analysis

Goffredo, Michela; Carter, John N.; Nixon, Mark S.

doi:10.1007/978-3-540-89208-3_18

Cited by 12 publications

(8 citation statements)

References 19 publications

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“…To our knowledge, amongst the 2D ML methods for clinical gait analysis proposed in the literature, just a few use anatomically relevant points to define the CS A [22, 32, 33]. Goffredo and colleagues [22] used an approach based on skeletonisation and obtained the proportions of the human body segments from anatomical studies [34].…”

Section: Discussionmentioning

confidence: 99%

“…Goffredo and colleagues [22] used an approach based on skeletonisation and obtained the proportions of the human body segments from anatomical studies [34]. This approach, although completely automatic, neglects the subject-specific characteristics, possibly leading to joint angles estimation inaccuracies.…”

Section: Discussionmentioning

confidence: 99%

“…However, neither reference to the specific clinical gait analysis protocol used nor a quantitative assessment of the method performance is reported. Similarly, Goffredo and colleagues [22] only performed a qualitative validation of their method by comparing the estimated joint kinematics to standard patterns taken from the literature. Moreover, none of the abovementioned works described the procedure used to track the pelvis, which is critical for the correct estimation of the hip joint angle.…”

Section: Discussionmentioning

confidence: 99%

“…First, the joint kinematics is only available for the limb in the foreground, while other authors managed to obtain a bilateral joint kinematics description using a single camera [22]. Therefore, to obtain kinematics from both sides, the subject has to walk in both directions of progression.…”

Section: Discussionmentioning

confidence: 99%

“…To the best of our knowledge, only a paucity of studies have proposed ML methods for the estimation of the lower limb joint kinematics for clinical evaluations [20–24]. However, in the abovementioned studies, the analyses were either limited to a single joint [20, 21], or they lacked a validation against a clinically accepted gold standard [22, 23]. These limitations hampered the wide spread use of such techniques in clinical settings [4, 7, 9].…”

Section: Introductionmentioning

confidence: 99%

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A 2D Markerless Gait Analysis Methodology: Validation on Healthy Subjects

Castelli

Paolini²,

Cereatti

et al. 2015

Computational and Mathematical Methods in Medicine

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A 2D markerless technique is proposed to perform lower limb sagittal plane kinematic analysis using a single video camera. A subject-specific, multisegmental model of the lower limb was calibrated with the subject in an upright standing position. Ankle socks and underwear garments were used to track the feet and pelvis segments, whereas shank and thigh segments were tracked by means of reference points identified on the model. The method was validated against a marker based clinical gait model. The accuracy of the spatiotemporal parameters estimation was found suitable for clinical use (errors between 1% and 3% of the corresponding true values). Comparison analysis of the kinematics patterns obtained with the two systems revealed high correlation for all the joints (0.82 < R 2 < 0.99). Differences between the joint kinematics estimates ranged from 3.9 deg to 6.1 deg for the hip, from 2.7 deg to 4.4 deg for the knee, and from 3.0 deg to 4.7 deg for the ankle. The proposed technique allows a quantitative assessment of the lower limb motion in the sagittal plane, simplifying the experimental setup and reducing the cost with respect to traditional marker based gait analysis protocols.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

A 2D Markerless Gait Analysis Methodology: Validation on Healthy Subjects

Castelli

Paolini²,

Cereatti

et al. 2015

Computational and Mathematical Methods in Medicine

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Vision-Based Marker-Less Spatiotemporal Gait Analysis by Using a Mobile Platform: Preliminary Validation

Filtjens

Amsters

Junaid

et al. 2019

Communications in Computer and Information Science

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Gait analysis is one of the most useful tools for assessing age-related conditions. This study describes the preliminary validation of a novel visionbased method for unobtrusive, ambulatory monitoring of spatiotemporal gait parameters. The method uses a mobile platform that is equipped with a Microsoft Kinect. A proprietary, generative tracker is used for measuring the 3D segmental movement of the subject. A novel method was developed for extracting gait parameters from the raw joint measurements by using the relative distance between the two ankle joints. The results are assessed in terms of mean absolute error and mean absolute percentage error with respect to a motion capture system. The mean absolute error ± precision was 5.5 ± 3.5 cm for stride length, 1.7 ± 1.3 cm for step width, 0.93 ± 0.44 steps/min for cadence, and 2.5 ± 2.0 % for single limb support. While these results are promising, additional experiments are required to assess the repeatability of this approach.

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