Background/Objective

Activity is increasingly being recognized as a highly relevant parameter in all areas of healthcare for diagnosis, treatment, or outcome assessment, especially in orthopaedics where the movement apparatus is directly affected. Therefore, the aim of this study was to develop, describe, and clinically validate a generic activity-monitoring algorithm, satisfying a combination of three criteria. The algorithm must be able to identify, count, and time a large set of relevant daily activities. It must be validated for orthopaedic patients as well as healthy individuals, and the validation must be in a setting that mimics free-living conditions.

Methods

Using various technical solutions, such as a dual-axis approach, dynamic inclinometry (hip flexion), and semiautomatic calibration (gait speed), the algorithms were designed to count and time the following postures, transfers, and activities of daily living: resting/sitting, standing, walking, ascending and descending stairs, sit–stand transitions, and cycling. In addition, the number of steps per walking bout was determined. Validation was performed with healthy individuals and patients who had undergone unilateral total joint arthroplasty, representing a wide spectrum of functional capacity. Video observation was used as the gold standard to count and time activities in a validation protocol approaching free-living conditions.

Results

In total 992 and 390 events (activities or postures) were recorded in the healthy group and patient group, respectively. The mean error varied between 0% and 2.8% for the healthy group and between 0% and 7.5% for the patient group. The error expressed in percentage of time varied between 2.0% and 3.0% for both groups.

Conclusion

Activity monitoring of orthopaedic patients by counting and timing a large set of relevant daily life events is feasible in a user- and patient-friendly way and at high clinical validity using a generic three-dimensional accelerometer and algorithms based on empirical and physical methods. The algorithms performed well for healthy individuals as well as patients recovering after total joint replacement in a challenging validation set-up. With such a simple and transparent method real-life activity parameters can be collected in orthopaedic practice for diagnostics, treatments, outcome assessment, or biofeedback.