Objective Quantification of In-Hospital Patient Mobilization after Cardiac Surgery Using Accelerometers: Selection, Use, and Analysis

Abstract

Cardiac surgery patients infrequently mobilize during their hospital stay. It is unclear for patients why mobilization is important, and exact progress of mobilization activities is not available. The aim of this study was to select and evaluate accelerometers for objective qualification of in-hospital mobilization after cardiac surgery. Six static and dynamic patient activities were defined to measure patient mobilization during the postoperative hospital stay. Device requirements were formulated, and the available devices reviewed. A triaxial accelerometer (AX3, Axivity) was selected for a clinical pilot in a heart surgery ward and placed on both the upper arm and upper leg. An artificial neural network algorithm was applied to classify lying in bed, sitting in a chair, standing, walking, cycling on an exercise bike, and walking the stairs. The primary endpoint was the daily amount of each activity performed between 7 a.m. and 11 p.m. The secondary endpoints were length of intensive care unit stay and surgical ward stay. A subgroup analysis for male and female patients was planned. In total, 29 patients were classified after cardiac surgery with an intensive care unit stay of 1 (1 to 2) night and surgical ward stay of 5 (3 to 6) nights. Patients spent 41 (20 to 62) min less time in bed for each consecutive hospital day, as determined by a mixed-model analysis (p < 0.001). Standing, walking, and walking the stairs increased during the hospital stay. No differences between men (n = 22) and women (n = 7) were observed for all endpoints in this study. The approach presented in this study is applicable for measuring all six activities and for monitoring postoperative recovery of cardiac surgery patients. A next step is to provide feedback to patients and healthcare professionals, to speed up recovery.

Keywords: LOO cross-validation; activity classification; biomedical signal processing; early ambulation; k-fold cross validation; patient monitoring; thoracic surgery; wearable technology.

Figure 1

The AX3 accelerometers were placed lateroproximal on the right upper arm and anterodistal on the right upper leg. Permission was obtained for use of this photograph for publication.

Figure 2

Relative time spent per activity per postoperative day at the cardio-thoracic surgery ward between 7 a.m. and 11 p.m. A decrease in lying in bed (orange) and an increase in sitting (sky blue) were observed during the hospital stays. The number of included patients decreased because of the varying length of stay and discharge from the hospital.

Figure 3

Patient activities at the cardio-thoracic surgery ward as labelled with the average time spent on each activity between 7 a.m. and 11 p.m. on the left panels, and the relative time as percentage on the right panels: (a,b) lying in bed; (c,d) sitting in a chair; (e,f) standing; (g,h) walking; (i,j) cycling; (k,l) walking the stairs. Lines represent the mean with 95% confidence interval and the p-values depict the effect of time (days) on each activity. Fixed axes are used for comparison with additional inlays to show details.

Figure 3

Patient activities at the cardio-thoracic surgery ward as labelled with the average time spent on each activity between 7 a.m. and 11 p.m. on the left panels, and the relative time as percentage on the right panels: (a,b) lying in bed; (c,d) sitting in a chair; (e,f) standing; (g,h) walking; (i,j) cycling; (k,l) walking the stairs. Lines represent the mean with 95% confidence interval and the p-values depict the effect of time (days) on each activity. Fixed axes are used for comparison with additional inlays to show details.