Purpose Patients after cardiac surgery infrequently mobilize during their surgical ward stay. Patients are unaware why mobilization is important, and patients’ progress of mobilization activities is not available. The aim of this study was to use accelerometers with artificial intelligence algorithms for quantification of in-hospital mobilization after cardiac surgery. Methods Six static and dynamic patient activities were defined to measure patient mobilization. An accelerometer (AX3, Axivity) was postoperatively placed on both the upper arm and upper leg. An artificial neural network algorithm classified lying in bed, sitting in a chair, standing, walking, cycling on an exercise bike, and walking the stairs. The primary endpoint was each activity duration performed between 7 a.m. and 11 p.m. Secondary endpoints were length of intensive care unit stay and surgical ward stay. A subgroup analysis was performed for male and female patients. Results In total, 29 patients were classified after cardiac surgery with an intensive care unit stay of 1 (1–2) night and surgical ward stay of 5 (3–6) nights. Patients spent 41 (20–62) min less time in bed for each following hospital day (p<0.001). Standing (p=0.004), walking (p<0.001), and walking the stairs (p=0.001) increased during hospital stay. No differences between men (n=22) and women (n=7) were observed for all endpoints. Conclusion 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 tailored feedback to patients and healthcare professionals, to speed up recovery.
|Number of pages||1|
|Publication status||Published - 21 May 2021|
|Event||Voorjaarsvergadering Nederlandse Vereniging voor Thoraxchirurgie 2021 - Virtual, Netherlands|
Duration: 21 May 2021 → 21 May 2021
|Conference||Voorjaarsvergadering Nederlandse Vereniging voor Thoraxchirurgie 2021|
|Abbreviated title||Voorjaarswebinar NVT 2021|
|Period||21/05/21 → 21/05/21|