Detecting clinical practice guideline-recommended wheelchair propulsion patterns with wearable devices following a wheelchair propulsion intervention

Chen, Pin-Wei; Klaesner, Joseph W.; Zwir, Igor; Morgan, Kerri

doi:10.1080/10400435.2021.2010146

Cited by 1 publication

(2 citation statements)

References 28 publications

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“…Therefore, the disadvantage of IMUs is that propulsion variables are not measured directly on the wheel but must be deduced from the (raw) IMU signals. To use IMUs for tracking physical activity and wheelchair propulsion, methodologies have been developed for use in both daily life [ 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 ] and sports settings [ 37 , 38 , 39 , 40 , 41 , 42 ]. Regarding wheelchair propulsion in daily life, most of the literature is published on methods for quantifying a manual wheelchair user’s energy expenditure or activity levels during physical activity [ 27 , 30 , 31 , 34 ].…”

Section: Introductionmentioning

confidence: 99%

“…However, methods for quantifying wheelchair propulsion itself, and thus quantifying the wheelchair user’s exposure to one of the risk factors for shoulder problems, are scarce. Nevertheless, in general, one or two variables of propulsion quantification are addressed in previous publications, (such as speed [ 26 , 29 , 36 ], distance covered [ 26 , 29 , 33 , 35 , 36 ], number of pushes [ 20 , 24 , 25 , 28 , 32 ], duration of movement [ 23 , 36 ], direction of movement [ 23 ] or propulsion style [ 21 , 22 ]); a methodology combining several of the relevant variables is still missing.…”

Section: Introductionmentioning

confidence: 99%

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Real-Life Wheelchair Mobility Metrics from IMUs

de Vries,

van der Slikke,

van Dijk

et al. 2023

Sensors

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Daily wheelchair ambulation is seen as a risk factor for shoulder problems, which are prevalent in manual wheelchair users. To examine the long-term effect of shoulder load from daily wheelchair ambulation on shoulder problems, quantification is required in real-life settings. In this study, we describe and validate a comprehensive and unobtrusive methodology to derive clinically relevant wheelchair mobility metrics (WCMMs) from inertial measurement systems (IMUs) placed on the wheelchair frame and wheel in real-life settings. The set of WCMMs includes distance covered by the wheelchair, linear velocity of the wheelchair, number and duration of pushes, number and magnitude of turns and inclination of the wheelchair when on a slope. Data are collected from ten able-bodied participants, trained in wheelchair-related activities, who followed a 40 min course over the campus. The IMU-derived WCMMs are validated against accepted reference methods such as Smartwheel and video analysis. Intraclass correlation (ICC) is applied to test the reliability of the IMU method. IMU-derived push duration appeared to be less comparable with Smartwheel estimates, as it measures the effect of all energy applied to the wheelchair (including thorax and upper extremity movements), whereas the Smartwheel only measures forces and torques applied by the hand at the rim. All other WCMMs can be reliably estimated from real-life IMU data, with small errors and high ICCs, which opens the way to further examine real-life behavior in wheelchair ambulation with respect to shoulder loading. Moreover, WCMMs can be applied to other applications, including health tracking for individual interest or in therapy settings.

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