Measuring movement fluency during the sit-to-walk task

Kerr, Andrew; Pomeroy, Valerie M.; Rowe, Peter; Dall, Philippa M.; Rafferty, Daniel

doi:10.1016/j.gaitpost.2012.09.026

Cited by 23 publications

(52 citation statements)

References 33 publications

(43 reference statements)

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“…Humans often transition between postures as part of daily life. For example working adults are reported to rise from a seated position more than 60 times per day [ 1 ] and healthy individuals have been found to initiate walking from sedentary positions including siting over 90% of the time (rising-to-walk) [ 2 ]. Whilst ubiquitous, rising-to-walk is also a flexible transitional task.…”

Section: Introductionmentioning

confidence: 99%

Parameters that remain consistent independent of pausing before gait-initiation during normal rise-to-walk behaviour delineated by sit-to-walk and sit-to-stand-and-walk

et al. 2018

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BackgroundRising-to-walk is an everyday transitional movement task rarely employed in gait rehabilitation. Sit-to-walk (STW) and sit-to-stand-and-walk (STSW), where a pause separates sit-to-stand and gait-initiation (GI) represent extremes of rising-to-walk behaviour. Delayed GI can indicate pathological impairment but is also observed in healthy individuals. We hypothesise that healthy subjects express consistent biomechanical parameters, among others that differ, during successful rising-to-walk task performance regardless of behaviour. This study therefore sought to identify if any parameters are consistent between STW and STSW in health because they represent normal rise-to-walk performance independent of pause, and also because they represent candidate parameters sensitive enough to monitor change in pathology.MethodsTen healthy volunteers performed 5 trials of STW and STSW. Event timing, ground-reaction-forces (GRFs), whole-body-centre-of-mass (BCoM) displacement, and centre-of-pressure (CoP) to extrapolated BCoM (xCoM) distance (indicator of positional stability) up to the 3rd step were compared between-tasks with paired t-tests. For consistent parameters; agreement between-tasks was assessed using Bland-Altman analyses and minimal-detectable-change (MDC) calculations.ResultsMean vertical GRFs, peak forward momentum and fluidity during rising; CoP-xCoM separation at seat-off, upright, GI-onset, and steps1-2; and forward BCoM velocity were all significantly greater in STW. In contrast, peak BCoM vertical momentum, flexion-momentum time, and 3rd step stability were consistent between tasks and yielded acceptable reliability.ConclusionSTW is a more challenging task due to the merging of rising with GI reflected by greater CoP-xCoM separation compared to STSW indicative of more positional instability. However, BCoM vertical momentum, flexion-momentum time, and step3 stability remained consistent in healthy individuals and are therefore candidates with which to monitor change in gait rehabilitation following pathology. Future studies should impose typical pause-durations observed in pathology upon healthy subjects to determine if the parameters we have identified remain consistent.

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Section: Introductionmentioning

confidence: 99%

Parameters that remain consistent independent of pausing before gait-initiation during normal rise-to-walk behaviour delineated by sit-to-walk and sit-to-stand-and-walk

et al. 2018

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“…The MATLAB function that implements the above calculations is displayed in the Listing 2. The MATLAB function displayed in the Listing 2 inputs an array R of size 3×3×N and a sampling period DT and returns the numerical estimate of the Cartesian kinematic jerk index (9). At Line 9, note that the operator real was introduced to get rid of the imaginary part of the matrix logarithm, that, in principle, should be equal to zero, while, in practice, it arises from finite-precision machine calculations.…”

Section: Computational Estimation Of the Kinematic Jerk Index Asmentioning

confidence: 99%

A Mobile Acquisition System and a Method for Hips Sway Fluency Assessment

2018

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The present contribution is motivated by recent studies on the assessment of the fluency of body movements during complex motor tasks. In particular, we focus on the estimation of the Cartesian kinematic jerk (namely, the derivative of the acceleration) of the hips' orientation during a full threedimensional movement. The kinematic jerk index is estimated on the basis of gyroscopic signals acquired through a smartphone. A specific free mobile application available for the ANDROID TM mobile operating system, Hyper IMU, is used to acquire the gyroscopic signals and to transmit them to a personal computer via a User Datagram Protocol (UDP) through a wireless network. The personal computer elaborates the acquired data through a MATLAB script, either in real time or offline, and returns the kinematic jerk index associated to a motor task.

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“…However, advances in body-worn sensors [35] and video processing technology [36] promise low-cost motion analysis that could include measurement of movement quality [18]. The use of these systems is beginning to be Page 14 of 25 A c c e p t e d M a n u s c r i p t 11 accepted in rehabilitation research [36].…”

Section: Of 25mentioning

confidence: 99%