Remote timed up and go evaluation from activities of daily living reveals changing mobility after surgery

Abstract

Background. Mobility impairment is common in older adults and negatively influences the quality of life. Mobility level may change rapidly following surgery or hospitalization in the elderly. The Timed Up and Go (TUG) is a simple, frequently used clinical test for functional mobility; however, TUG requires supervision from a trained clinician, resulting in infrequent assessments. Additionally, assessment by TUG in clinic settings may not be completely representative of the individual's mobility in their home environment. Objective. In this paper, we introduce a method to estimate TUG from activities detected in free-living, enabling continuous remote mobility monitoring without expert supervision. The method is used to monitor changes in mobility following Total Hip Arthroplasty (THA). Methods. Community-living elderly (n=239, 65-91 years) performed a standardized TUG in a laboratory and wore a wearable pendant device that recorded accelerometer and barometric sensor data for at least 3-days. Activities of daily living, including walks and sit-to-stand transitions, and their related mobility features were extracted and used to develop a regularized linear model for remote TUG test estimation. Changes in the remote TUG were evaluated in orthopaedic patients (n=15, 55-75 years), during 12-weeks following THA. Results. In leave-one-out-cross-validation, a strong correlation (ρ=0.70) was observed between the new remote TUG and standardized TUG times. Test-retest reliability of 3-day estimates was high (ICC=0.94). Compared to 2-weeks post-THA, remote TUG was significantly improved at 6-weeks (11.7±3.9 s vs 8.0±1.8 s, p<0.001), with no further change at 12-weeks (8.1±3.9 s, p=0.37). Conclusions. Remote TUG can be estimated in older adults using 3-days of ADLs data recorded using a wearable pendant. Remote TUG has discriminatory potential for identifying frail elderly and may provide a convenient way to monitor changes in mobility in unsupervised settings.

Wearable Sensor-Based Prediction Model of Timed up and Go Test in Older Adults

“…The 95% limits of agreement in the Bland-Altman plots were narrower than those of Saporito's Bland-Altman plots, which means our estimated TUG is essentially equivalent to the measured actual TUG. Saporito and colleagues developed the remote TUG prediction model with 2.1 s of MAPE [23]. Thus, the developed model demonstrated prediction errors (foot: MSPE = 1.124s, RMSPE = 1.046 s, MAPE = 0.865 s, pelvis: MSPE = 1.162 s, RMSPE = 1.065 s, MAPE = 0.921 s, foot-pelvis combination: MSPE = 1.192 s, RMSPE = 1.075 s, MAPE = 0.918 s) that are less than Saporito's prediction errors.…”

“…Several studies [20][21][22] identified the different stages of the TUG test using the actual TUG test or similar settings, but we aimed to estimate the TUG test using normal ground walking with daily-life settings. Saporito et al introduced a remote mobility monitoring method by estimating TUG from free-living activities [23]. We compared our TUG prediction results with Saporito's TUG estimation.…”

“…In many studies, various sensor locations were used for health and mobility assessment [5,[12][13][14][15][19][20][21][22][23][24]. Obviously, a wrist type of sensor is less obtrusive and more user convenient.…”

Wearable activity sensors and early pain after total joint arthroplasty

“…We observed excellent outpatient compliance with sensor wear, minimal gaps in data collection, and no device malfunctions during the study period. Wearable sensors reasonably estimate results of accepted functional tests such as the timed up-and-go test [7]. Analyzing outpatient sensor information to guide medical decisions would represent a paradigm shift from traditional strategies based on rigid follow-up schedules, untriggered patient contact, and waiting for patients to call to report a problem to more timely care, with potential clinical benefits from shorter delays to interventions.…”

Use of Wearable Sensors and Machine Learning Methods in Promoting Total Joint Replacement Treatment Outcomes: A Survey

“…In terms of limitations, small sample sizes were the most common one with all studies reporting participants between 15-25. Another common limitation is the Western centric participant pools of the studies (Saporito et al, 2019).…”