Abstract
A healthy lifestyle reduces the risk of cardio-vascular disease. As wheelchair-bound individuals with spinal cord injury (SCI) are challenged in their activities, promoting and coaching an active lifestyle is especially relevant. Although there are many commercial activity trackers available for the able-bodied population, including those providing feedback about energy expenditure (EE), activity trackers for the SCI population are largely lacking, or are limited to a small set of activities performed in controlled settings. The aims of the present study were to develop and validate an algorithm based on inertial measurement unit (IMU) data to continuously monitor EE in wheelchair-bound individuals with a SCI, and to establish reference activity values for a healthy lifestyle in this population. For this purpose, EE was measured in 30 subjects each wearing four IMUs during 12 different physical activities, randomly selected from a list of 24 activities of daily living. The proposed algorithm consists of three parts: resting EE estimation based on multi-linear regression, an activity classification using a k-nearest-neighbors algorithm, and EE estimation based on artificial neural networks (ANNs). The mean absolute estimation error for the ANN-based algorithm was 14.4% compared to indirect calorimeter measurements. Based on reference values from the literature and the data collected within this study, we recommend wheeling 3 km per day for a healthy lifestyle in wheelchair-bound SCI individuals. Combining the proposed algorithm with a recommendation for physical activity provides a powerful tool for the promotion of an active lifestyle in the SCI population, thereby reducing the risk for secondary diseases.
Highlights
The life expectancy of individuals with a spinal cord injury (SCI) has increased significantly over the last decades [1]
The estimates are compared in terms of mean absolute error (MAE), mean signed error (MSE) and maximal error
3500 3000 2500 2000 1500 1000 500 0 low intensity rest watching TV reading crossword puzzles playing cards riding an elevator playing with iPad writing computer work passive wheeling high intensity washing dishes hanging out laundry handbike ergometer table tennis weight lifting wheeling skill parcour wheelchair ergometer wheeling @ self−chosen wheeling @ 2km/h wheeling @ 3.5km/h wheeling @ 5km/h wheeling @ 6.5km/h wheeling uphill wheeling downhill
Summary
The life expectancy of individuals with a spinal cord injury (SCI) has increased significantly over the last decades [1]. Hypertension, hyperlipidemia, and diabetes have all been identified as risk factors for cardio-vascular disease, with a higher prevalence in the SCI population [4]. Regular physical activity has been associated with a reduction of these risk factors in the able-bodied population, as well as in the SCI population [5,6,7]. The SCI population is challenged due to their limited choice of activities [8, 9], and there is a great need to promote and coach physical activity [10]. One possible approach to promote a more active lifestyle is to provide feedback on daily physical activity and energy expenditure (EE)
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