Related Experiment Video
Updated: Apr 27, 2026
Home-Based Monitor for Gait and Activity Analysis
Published on: August 8, 2019
Monitoring daily function in persons with transfemoral amputations using a commercial activity monitor: a feasibility
Mark V Albert1, Sean Deeny2, Cliodhna McCarthy3
1Center for Bionic Medicine, Rehabilitation Institute of Chicago, Chicago, IL; Department of Physical Medicine and Rehabilitation, Northwestern University, Chicago, IL; Department of Computer Science, Loyola University Chicago, Chicago, IL; Sensory Motor Performance Program, Rehabilitation Institute of Chicago, Chicago, IL; Max Nader, Center for Rehabilitation Technologies and Outcomes Research, Rehabilitation Institute of Chicago, Chicago, IL.∗.
Objective:
To assess in a feasibility study the mobility of persons with transfemoral amputations using data collected from a popular, consumer-oriented activity monitor (Fitbit).
Design:
Observational cohort study.
Setting:
Research hospital outpatient evaluation.
Participants:
Nine subjects with transfemoral amputations (4 women and 5 men, ages 21-64 years) and Medicare functional assessments (K level) of K3 (n = 7), K2 (n = 1), and K4 (n = 1).
Methods:
One-week monitoring of physical activity using the Fitbit One activity monitor.
Main Outcome Measures:
Daily estimates of step counts, distance walked, floors/stairs climbed, calories burned, and proprietary Fitbit activity scores. For each day, the amount of time in each of the following levels of activity was also reported: sedentary, lightly active, fairly active, and highly active.
Results:
The percentage of movement time above the fairly active level had a predictable relationship to the designated K level. The average activity measures show decreased levels of activity for obese subjects (body mass index >30). Estimated step counts were highly predictive/redundant with estimated miles walked without setting individual stride lengths. Using linear regression prediction models, calorie estimates were found to be highly dependent on subject age, height, and weight, whereas the proprietary activity score was independent of all 3 demographic factors.
Conclusions:
This feasibility study demonstrates that the Fitbit activity monitor estimates the activity of subjects with transfemoral amputations, producing results that correlate with their K-level functional activity classifications. The Fitbit activity score is independent of individual variations in age, weight, and height compared with estimated calories for this small sample size. These tools may provide useful insights into prosthetic use in an at-home environment.
