Statistical parametric mapping of biomechanical one-dimensional data with Bayesian inference

Serrien, Ben; Goossens, Maggie; Baeyens, Jean Pierre

doi:10.1080/23335432.2019.1597643

Cited by 31 publications

(21 citation statements)

References 36 publications

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“…It must also be acknowledged that the present study relies on investigation of joint kinematics at discrete time points (i.e., key instants). Future studies may therefore extend the current work using methodologies to investigate the continuous time series of kinematic data, such as statistical parametric mapping [40], vector coding [41] or principal component analysis [42], as well as considering other biomechanical principles not explored within this study. Additionally, differences in anthropometric data were not accounted for, where the same angular velocities and joint angles may lead to different linear velocities.…”

Section: Discussionmentioning

confidence: 99%

A Correlational Analysis of Shuttlecock Speed Kinematic Determinants in the Badminton Jump Smash

et al. 2020

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The forehand jump smash is an essential attacking stroke within a badminton player’s repertoire. A key determinate of the stroke’s effectiveness is post-impact shuttlecock speed, and therefore awareness of critical technique factors that impact upon speed is important to players/coaches. Three-dimensional kinematic data of player, racket and shuttlecock were recorded for 18 experienced players performing maximal effort forehand jump smashes. Joint angles and X-factor (transverse plane pelvis-thorax separation) were calculated at key instants: preparation, end of retraction, racket lowest point, turning point and shuttlecock contact. Peak shoulder, elbow, and wrist joint centre linear velocities, phase durations and jump height were also calculated. Correlational analyses were performed with post-impact shuttlecock speed, revealing significant correlations to peak wrist joint centre linear velocity (r = 0.767), acceleration phase duration (r = −0.543), shoulder internal/external rotation angle at shuttlecock contact (r = 0.508) and X-factor at the end of retraction (r = −0.484). Multiple linear regression analysis revealed 43.7% of the variance in shuttlecock speed could be explained by acceleration phase duration and X-factor at the end of retraction, where shorter acceleration phase durations and more negative X-factor at end of retraction caused greater shuttlecock speeds. These results suggest that motions of the proximal segments (shoulder and pelvis–thorax separation) are critical to developing greater distal linear velocities, which subsequently lead to greater post-impact shuttlecock speed.

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Section: Discussionmentioning

confidence: 99%

A Correlational Analysis of Shuttlecock Speed Kinematic Determinants in the Badminton Jump Smash

et al. 2020

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“…peak values or ROM) or from a selected phase in the waveform (e.g. swing, stance), thereby losing information about the kinematic waveform [17]. In addition, abovementioned studies only included healthy participants, for whom these demanding tasks impose no difficulties.…”

Section: Introductionmentioning

confidence: 99%

Functional movement assessment by means of inertial sensor technology to discriminate between movement behaviour of healthy controls and persons with knee osteoarthritis

Straaten

Wesseling

Jonkers

et al. 2020

J NeuroEngineering Rehabil

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Background: Apart from biomechanical alterations in movement patterns, it is known that movement limitations in persons with knee osteoarthritis (PwKOA) are related to an individual's perception and belief regarding pain and disability. To gain more insights into the functional movement behaviour of PwKOA in a clinical setting, inertial sensor technology can be applied. This study first aims to evaluate the ability of inertial sensors to discriminate between healthy controls (HC) and PwKOA. Secondly, this study aims to determine the relationship between movement behaviour, pain-related factors and disability scores. Methods: Twelve HC and 19 PwKOA were included. Five repetitions of six functional movement tasks (walking, forward lunge, sideward lunge, ascent and descent stairs, single leg squat and sit-to-stand) were simultaneously recorded by the inertial sensor system and a camera-based motion analysis system. Statistically significant differences in angular waveforms of the trunk, pelvis and lower limb joints between HC and PwKOA were determined using one-dimensional statistical parametric mapping (SPM1D). The Knee injury and Osteoarthritis Outcome Score and TAMPA scale for Kinesiophobia were used to evaluate the relationship between discriminating joint motion, pain-related factors and disability using spearman's correlation coefficients. Results: PwKOA had significantly less trunk rotation, internal pelvis rotation and knee flexion ROM during walking. Additionally, the reduced knee flexion (i.e. at the end of the stance phase and swing phase) was related to increased level of perceived pain. During the sideward lunge, PwKOA had significantly less knee flexion, ankle plantarflexion and hip abduction. This decreased hip abduction (i.e. during stance) was related to higher fear of movement. Finally, PwKOA had significantly less knee flexion during the forward lunge, single leg squat and during ascent and descent stairs. No significant correlations were observed with disability.

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“…In comparison with a frequentist approach, with a sample size of n = 50 subjects, an effect size of Cohen's δ = 0.4 can be acquired with an 85% statistical power and a 5% Type I error rate. Finally, Bayesian statistical parametric testing (SPM [33][34][35] ) was used to identify the kinematic differences between threat conditions. For this analysis, we solely used the kinematic trajectories in which a heel landing was observed.…”

Section: Sampling Plan and Statistical Analysis A Bayesian Approach mentioning

confidence: 99%

“…Non-parametric alternatives were used, if the assumptions of a statistical test were violated, hence a Bayesian signed-rank test 38 was applied for the tests that compared fear, anxiety, and walking speed across threat conditions. The Bayesian parametric hypothesis testing was performed in JASP 36 , and the SPM analysis (code adapted from https://osf.io/ q5b72/ 35 ) and the non-parametric tests (code adapted from https://osf.io/gny35/ 38 ) were performed in R 39 .…”

Section: Sampling Plan and Statistical Analysis A Bayesian Approach mentioning

confidence: 99%

The influence of postural threat on strategy selection in a stepping-down paradigm

Kluft

Bruijn

Luu

et al. 2020

Sci Rep

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To walk safely in their environment, people need to select adequate movement strategies during gait. In situations that are perceived as more threatening, older adults adopt more cautious strategies. For individuals with excessive fear, selecting adequate strategies might be troubling. We investigated how a postural threat affects the selection of strategies within and between older adults by using a steppingdown paradigm. In twenty-four older adults we determined the height at which they switched in stepping-down strategies from a less demanding but more balance threatening heel landing to a more demanding yet safer toe landing. We expected that this switching height would be lower in the high (0.78 m elevation) compared to low threat (floor level) condition. Furthermore, we investigated if older adults, for which the postural threat evoked an increase in the perceived fear, presented a different stepping down strategy due to the postural threat. Our results indicated that the postural threat changed older adults' strategies selection towards a more conservative toe landing. Hence, despite the additional effort, older adults prefer more cautious strategies during a postural threat. No effects of perceived fear on strategy selection between individuals were observed, potentially due to relatively small differences in fear among participants.

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Statistical parametric mapping of biomechanical one-dimensional data with Bayesian inference

Cited by 31 publications

References 36 publications

A Correlational Analysis of Shuttlecock Speed Kinematic Determinants in the Badminton Jump Smash

A Correlational Analysis of Shuttlecock Speed Kinematic Determinants in the Badminton Jump Smash

Functional movement assessment by means of inertial sensor technology to discriminate between movement behaviour of healthy controls and persons with knee osteoarthritis

The influence of postural threat on strategy selection in a stepping-down paradigm

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