Joint damage and motor learning during unipedal stance in haemophilia arthropathy: report of two cases

Cruz‐Montecinos, Carlos; Rivera-Lillo, Gonzalo; Burgos, Pablo; Torres-Elgueta, Julio; Pérez‐Alenda, Sofía; Querol, Felipe

doi:10.1111/hae.13060

Cited by 4 publications

(13 citation statements)

References 9 publications

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“…The sensorial strategies employed by haemophilia patients when in a quiet stance are poorly understood, but the present research provides integral insight into this subject. The applied methodology could be used to determine the progress of balance rehabilitation, to establish which sensorial strategies are better suited for physical therapy programmes (eg visual‐somatosensory feedback or only improve the somatic planter), to ascertain the effects of automaticity in postural control, and to improve postural control interventions so as to prevent intra‐articular reinjuries in patients with haemophilia.…”

Section: Discussionmentioning

confidence: 99%

“…Despite existing tools and a relevant need, only some aspects of static postural control are known for adult and paediatric haemophilia patients, as compared with healthy people . Currently, only one case report proposes that haemophilic arthropathy may affect performance during sensorimotor stability tasks and subsequent learning; however, more studies are needed to corroborate this assumption. To deeply understand postural control in individuals with haemophilia, and thus contribute towards improved balance‐training programmes, research must be conducted on the sensorial postural control strategies needed in bipedal tasks and on the irregularity of postural balance.…”

Section: Introductionmentioning

confidence: 99%

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Sensory strategies of postural sway during quiet stance in patients with haemophilic arthropathy

et al. 2017

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Sensory strategies of postural sway during quiet stance in patients with haemophilic arthropathy

et al. 2017

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“…There is little knowledge about the motor learning curve during postural control training between days [22,53,59]. In this study, based on a power law fit model, both groups showed a decrement of error across the trial; however, the rate of the decrement was higher for the biofeedback group.…”

Section: Discussionmentioning

confidence: 66%

“…In assessing trunk sway smoothness, global trunk smoothness (along the three dimensions x, y, z) was taken into account as opposed to measuring only along a given axis [52,53]. For this, jerk was obtained instantaneously as the Euclidean distance from three orthogonal discrete accelerometry signals acquired from the smartphone (G j ), where j represents the inertial axis of the accelerometer, i.e., anteroposterior, mediolateral and superiorinferior axes relative to the COM of the accelerometer; nT represents periodic sampling; i represents the number of samples; and := means jerk update while acquisition is running.…”

Section: Discussionmentioning

confidence: 99%

“…It is worth mentioning that a previous study found COM oscillations ranging between 2.5 and 4.5 Hz during one-leg balance training [22]. For each participant, the training threshold was defined as 30% of the maximum jerk generated during three unipedal tests lasting 30 s. This threshold was selected based on a previous report with a similar methodology [53]. Error was defined as time outside the training threshold during 30 s of unipedal stance (Figure 1B).…”

Section: Discussionmentioning

confidence: 99%

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Impact of Visual Biofeedback of Trunk Sway Smoothness on Motor Learning during Unipedal Stance

Cruz‐Montecinos

Cuesta‐Vargas

Muñoz

et al. 2020

Sensors

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The assessment of trunk sway smoothness using an accelerometer sensor embedded in a smartphone could be a biomarker for tracking motor learning. This study aimed to determine the reliability of trunk sway smoothness and the effect of visual biofeedback of sway smoothness on motor learning in healthy people during unipedal stance training using an iPhone 5 measurement system. In the first experiment, trunk sway smoothness in the reliability group (n = 11) was assessed on two days, separated by one week. In the second, the biofeedback group (n = 12) and no-biofeedback group (n = 12) were compared during 7 days of unipedal stance test training and one more day of retention (without biofeedback). The intraclass correlation coefficient score 0.98 (0.93–0.99) showed that this method has excellent test–retest reliability. Based on the power law of practice, the biofeedback group showed greater improvement during training days (p = 0.003). Two-way mixed analysis of variance indicates a significant difference between groups (p < 0.001) and between days (p < 0.001), as well as significant interaction (p < 0.001). Post hoc analysis shows better performance in the biofeedback group from training days 2 and 7, as well as on the retention day (p < 0.001). Motor learning objectification through visual biofeedback of trunk sway smoothness enhances postural control learning and is useful and reliable for assessing motor learning.

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30‐sit‐to‐stand power is a better tool than isometric knee extensor strength to detect motor impairment in people with haemophilic arthropathy

Cruz‐Montecinos,

Moena‐León,

Durán‐Ovalle

et al. 2024

Haemophilia

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IntroductionRegular assessment of motor impairments is crucial in people with haemophilic arthropathy (PwHA). This study aimed to determine if there are differences in 30‐seconds sit‐to‐stand (30‐STS) power and maximal voluntary isometric contraction (MVIC) of the knee extensors between PwHA and healthy control group (CG). The secondary aims were to investigate the correlation between 30‐STS power and MVIC of knee extensors with clinical characteristics and to assess their effectiveness in identifying motor impairment in PwHA.MethodsA cross‐sectional study was conducted by collecting data from PwHA (n = 17) and a sedentary CG (n = 15). MVIC (torque) and 30‐STS power were normalised to body mass. Correlation analysis and simple linear regression adjusted for age were used to assess the association between tests and clinical variables. Using z‐scores derived from the mean and standard deviation of the CG, we compared the MVIC and the 30‐STS power in PwHA.ResultsPwHA showed lower MVIC and 30‐STS power compared to CG (p < .001; large effect size d > .8). Lower 30‐STS power was associated with greater joint impairment and greater fear of movement, whereas MVIC showed no association with clinical variables. 30‐STS power showed a lower z‐score compared to MVIC (p < .001). In addition, 30‐STS power detected 47% of PwHA with motor impairment compared to 0% for MVIC (p = .002).ConclusionsOur results suggest that 30‐STS power may be more effective than knee extensors MVIC in detecting motor impairment in PwHA. Consequently, lower limb skeletal muscle power, rather than maximum knee extensor strength, appears to be more affected in PwHA.

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Joint damage and motor learning during unipedal stance in haemophilia arthropathy: report of two cases

Cited by 4 publications

References 9 publications

Sensory strategies of postural sway during quiet stance in patients with haemophilic arthropathy

Sensory strategies of postural sway during quiet stance in patients with haemophilic arthropathy

Impact of Visual Biofeedback of Trunk Sway Smoothness on Motor Learning during Unipedal Stance

30‐sit‐to‐stand power is a better tool than isometric knee extensor strength to detect motor impairment in people with haemophilic arthropathy

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