Validation of the use of Actigraph GT3X accelerometers to estimate energy expenditure in full time manual wheelchair users with spinal cord injury

Abstract

Study design: Cross-sectional validation study. Objectives: The goals of this study were to validate the use of accelerometers by means of multiple linear models (MLMs) to estimate the O 2 consumption (VO 2 ) in paraplegic persons and to determine the best placement for accelerometers on the human body. Setting: Non-hospitalized paraplegics' community. Methods: Twenty participants (age ¼ 40.03 years, weight ¼ 75.8 kg and height ¼ 1.76 m) completed sedentary, propulsion and housework activities for 10 min each. A portable gas analyzer was used to record VO 2 . Additionally, four accelerometers (placed on the non-dominant chest, non-dominant waist and both wrists) were used to collect second-by-second acceleration signals. Minute-byminute VO 2 (ml kg À1 min À1 ) collected from minutes 4 to 7 was used as the dependent variable. Thirty-six features extracted from the acceleration signals were used as independent variables. These variables were, for each axis including the resultant vector, the percentiles 10th, 25th, 50th, 75th and 90th; the autocorrelation with lag of 1 s and three variables extracted from wavelet analysis. The independent variables that were determined to be statistically significant using the forward stepwise method were subsequently analyzed using MLMs. Results: The model obtained for the non-dominant wrist was the most accurate (VO 2 ¼ 4.0558 À0.0318Y 25 þ 0.0107Y 90 þ 0.0051 Y ND2 À0.0061Z ND2 þ 0.0357VR 50 ) with an r-value of 0.86 and a root mean square error of 2.23 ml kg À1 min À1 . Conclusions: The use of MLMs is appropriate to estimate VO 2 by accelerometer data in paraplegic persons. The model obtained to the non-dominant wrist accelerometer (best placement) data improves the previous models for this population.

Construct Validity of the Spanish Version of the CHAMPS Questionnaire for institutionalized patients over 65 years old

“…With the purpose of determining the construct validity of the questionnaire, participants were asked to carry the accelerometer with them for one week. The device remained attached to their right thigh above the iliac crest while in standing position 21 , or around their dominant wrist while in sitting position 22 . It was expressed that they were to use the device from early in the morning until they went to bed at night, putting it aside only if they wished to have a bath or a shower, or needed to perform any kind of water-based activity.…”

ActiDote – A wireless sensor-based system for self-tracking activity levels among manual wheelchair users

“…Compared to the results presented in other state-ofthe-art works [5][6][7]10], the ActiDote system has been additionally tested considering wheelchair propulsion on ramps of different slopes. The outcome is a model that yields meaningful estimations in a larger set of conditions.…”

“…The linear model using a single feature from the wheelchair frame and two features from the wrist is shown in Equation 5, where F 1 is the standard deviation of the X axis of the accelerometer attached to the wheelchair frame, F 2 is the average of the magnitude of the acceleration measured at the wrist and F 3 is the standard deviation of the magnitude of the acceleration measured at the wrist. EE = 2.964 · F 1 − 0.577 · F 2 + 0.564 · F 3 + 6.842 (5) Both solutions need to be further tested in order to evaluate their robustness and to know how they behave in different real world situations (e.g., locomotion over different ground surfaces). Results of the models created after undergoing the feature selection process.…”

“…Moreover, they concluded that the model built from the acceleration measured at the wrist explains more of the variance and results in the lowest random error when predicting physical activity energy expenditure in manual wheelchair users. Garcia-Masso et al [5] used the Actigraph GT3X and extracted thirty-six features from the acceleration signals. They built linear regression models to estimate EE and concluded that the sensor placed on the non-dominant wrist gave the best results.…”

“…We used a large treadmill 4 to set the speed and inclination of the wheelchair, and a K5 portable metabolic cart 5 to quantify the actual energy expenditure of the user. Calibration procedures were performed before each session according to the manufacturer's instructions.…”