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  4. Wearable Sensors in Ambulatory Individuals With a Spinal Cord Injury: From Energy Expenditure Estimation to Activity Recommendations

Wearable Sensors in Ambulatory Individuals With a Spinal Cord Injury: From Energy Expenditure Estimation to Activity Recommendations

Frontiers in Neurology, 2019 · DOI: 10.3389/fneur.2019.01092 · Published: November 1, 2019

NeurologyRehabilitationTelehealth & Digital Health

Simple Explanation

This study addresses the challenge of promoting physical activity in individuals with incomplete spinal cord injury (iSCI) who are able to walk. Commercial activity trackers are not designed for reliable assessments in individuals with an incomplete spinal cord injury (iSCI). The study aimed to develop an energy expenditure (EE) estimation model based on wearable sensor data for iSCI individuals. Additionally, common activity recommendations for the non-disabled population were translated to easily understandable activity goals. The study suggests a minimum of 2,000–3,000 steps per day for ambulatory individuals with an iSCI. If iSCI individuals targeted the 10,000 steps a day recommendation, their equivalent would be around 8,000 steps a day.

Study Duration
Not specified
Participants
30 ambulatory individuals with an incomplete spinal cord injury (iSCI)
Evidence Level
Not specified

Key Findings

  • 1
    The best EE estimation model comprised the estimation of resting EE using the updated Harris-Benedict equation, classifying activities using a k-nearest neighbor algorithm, and applying a multiple linear regression-based EE estimation model for each activity class.
  • 2
    The mean absolute estimation error of this model was 15.2 ± 6.3% and the corresponding mean signed error was −3.4 ± 8.9%.
  • 3
    Translating activity recommendations of global health institutions, we suggest a minimum of 2,000–3,000 steps per day for ambulatory individuals with an iSCI.

Research Summary

This study developed an energy expenditure (EE) estimation model for ambulatory individuals with incomplete spinal cord injury (iSCI) using wearable sensor data. The developed model uses the updated Harris-Benedict equation for resting EE, a k-nearest neighbor algorithm for activity classification, and multiple linear regression for EE estimation in each activity class, achieving a mean absolute estimation error of 15.2%. The study translates activity recommendations for the non-disabled population into step goals for iSCI individuals, suggesting a minimum of 2,000-3,000 steps per day and equating 10,000 steps for non-disabled individuals to approximately 8,000 steps for iSCI individuals.

Practical Implications

Personalized Activity Recommendations

The translated activity recommendations can be used to develop personalized activity plans for ambulatory individuals with iSCI.

Rehabilitation Tool

The dedicated EE estimation model can be used to monitor progress during rehabilitation and to adjust activity levels accordingly.

Potential Activity Tracker

The findings contribute to the development of an activity tracker specifically designed for individuals with iSCI, promoting a healthier lifestyle.

Study Limitations

  • 1
    Relatively low number of participants using walking aids.
  • 2
    The proposed algorithm does not take fitness or lifestyle of an individual into account.
  • 3
    Both, the classification algorithm and EE estimation algorithm, have first to be validated under real-world settings.

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