ArticleFrontiers in neurology2019
Wearable Sensors in Ambulatory Individuals With a Spinal Cord Injury: From Energy Expenditure Estimation to Activity Recommendations.
Article in Frontiers in neurology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 2 of them syntheses that pooled it.
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Who cites it
13 citing papers in PubMed, 2 syntheses or guidelines pooled it, 34 citations in OpenAlex.
- Wearable Health Devices in Health Care: Narrative Systematic Review.JMIR mHealth and uHealth · 2020Pooled it
- Systematic review on the application of wearable inertial sensors to quantify everyday life motor activity in people with mobility impairments.Journal of neuroengineering and rehabilitation · 2020Pooled it
- Feasibility and Sensitivity of Wearable Sensors for Daily Activity Monitoring in Spinal Cord Injury Trials.Neurorehabilitation and neural repair · 2025Trial
- Validating the ADFSCI hypotension symptom domain as a scalable patient reported outcome measure in spinal cord injury.NPJ digital medicine · 2026Article
- Nutritional alterations, adverse consequences, and comprehensive assessment in spinal cord injury: a review.Frontiers in nutrition · 2025Review
- Article
- Quantifying Treatments as Usual and with Technologies in Neurorehabilitation of Individuals with Spinal Cord Injury.Healthcare (Basel, Switzerland) · 2024Article
- Reliability of patient-specific gait profiles with inertial measurement units during the 2-min walk test in incomplete spinal cord injury.Scientific reports · 2024Article
- Measurement properties of device-based physical activity instruments in ambulatory adults with physical disabilities and/or chronic diseases: a scoping review.BMC sports science, medicine & rehabilitation · 2023Article
- Accuracy and comparison of sensor-based gait speed estimations under standardized and daily life conditions in children undergoing rehabilitation.Journal of neuroengineering and rehabilitation · 2022Article
- Classification of Wheelchair Related Shoulder Loading Activities from Wearable Sensor Data: A Machine Learning Approach.Sensors (Basel, Switzerland) · 2022Article
- Acceptability of wearable inertial sensors, completeness of data, and day-to-day variability of everyday life motor activities in children and adolescents with neuromotor impairments.Frontiers in rehabilitation sciences · 2022Article
- Towards a Mobile Gait Analysis for Patients with a Spinal Cord Injury: A Robust Algorithm Validated for Slow Walking Speeds.Sensors (Basel, Switzerland) · 2021Article
Corrections and comments
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Authors and funding
7 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Inappropriate physical inactivity is a global health problem increasing the risk of cardiometabolic diseases. Wearable sensors show great potential to promote physical activity and thus a healthier lifestyle. While commercial activity trackers are available to estimate energy expenditure (EE) in non-disabled individuals, they are not designed for reliable assessments in individuals with an incomplete spinal cord injury (iSCI). Furthermore, activity recommendations for this population are currently rather vague and not tailored to their individual needs, and activity guidelines provided for the non-disabled population may not be easily translated for this population. However, especially in iSCI individuals with impaired abilities to stand and walk, the assessment of physical activities and appropriate recommendations for a healthy lifestyle are challenging. Therefore, the study aimed at developing an EE estimation model for iSCI individuals able to walk based on wearable sensor data. Additionally, the data collected within this study was used to translate common activity recommendations for the non-disabled population to easily understandable activity goals for ambulatory individuals with an iSCI. In total, 30 ambulatory individuals with an iSCI were equipped with wearable sensors while performing 12 different physical activities. EE was measured continuously and demographic and anthropometric variables, clinical assessment scores as well as wearable-sensor-derived features were used to develop different EE estimation models. 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. The mean absolute estimation error of this model was 15.2 ± 6.3% and the corresponding mean signed error was -3.4 ± 8.9%. 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. If ambulatory individuals with an iSCI targeted the popular 10,000 steps a day recommendation for the non-disabled population, their equivalent would be around 8,000 steps a day. The combination of the presented dedicated EE estimation model for ambulatory individuals with an iSCI and the translated activity recommendations is an important step toward promoting an active lifestyle in this population.
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