Quantitative Gait Analysis as a New Modality for Functional Evaluation of Patients with Heart Failure

Background: Six minute walk test (6MWT) is a standardized for evaluation of patients with heart failure (HF). Quantitative gait analysis (QGA) using wearable sensors is a non-invasive tool for accurately measuring gait parameters used in the diagnosis of neurologic diseases and in rehabilitation medicine. This study aimed to evaluate the relationship between QGA parameters and results of the 6MWT performed in patients with HF.

Methods: Thirty patients with HF were prospectively recruited and underwent 6MWT while wearing 6 mobility sensors (3D-accelerometers, gyroscopes & magnometers) on the feet, wrists, chest and lower back (APDM©, Portland, USA). Brain Natriuretic Peptide (BNP) and hemoglobin levels were assessed before exercising.

Results: Mean age of the cohort was 61.3, 83% males and a mean Ejection Fraction of 29.7%. Mean 6MWT distance was 413m. Focusing on the first five strides, mean stride time and mean stride length significantly correlated with total walk distance (R=-0.66 and 0.62 respectively, p<0.01 for both). Combining the two parameters using a linear regression model yielded an even more significant correlation with an R2 value of 0.77, p<0.0001. Additional gait parameters such as swing time and stride velocity displayed a significant correlation with the distance covered as well (R>|0.45|).

Conclusion: Several QGA parameters were found to correlate with the results of the 6MWT. QGA is a simple non-invasive diagnostic tool that can be used in the evaluation and prognostication of HF patients. The predictive value of only 5 strides suggests that using QGA may substitute the need to perform the full 6MWT.