2 research outputs found
EQUIVALENCE TESTING OF WEARABLE TECHNOLOGIES DURING SIMULATED ACTIVITIES OF DAILY LIVING
BACKGROUND: Step-based metrics, including steps/day and cadence (steps/min), are well established in the physical activity literature. However, there remains a need for robust criterion validation of step-counting wearable technologies across a wide range of ambulatory movements. Validation studies have typically examined device accuracy during rhythmic treadmill or overground walking, with few studies examining step-count accuracy during simulated activities of daily living (SADL). PURPOSE: To determine the step-count criterion validity of wearable devices during SADLs. METHODS: Participants (N = 260, 52.7±18.9 years, BMI 25.6±3.7 kg/m2, 50% women) from the CADENCE-Adults study, completed a series of laboratory-based SADLs, including folding laundry, vacuuming, stair stepping, and preferred pace overground walking. Participants wore devices on their waist (Yamax Digiwalker SW200 [SW200], New Lifestyles NL1000 [NL], ActiGraph GT9X [AG] and ActiCal [AC]), thigh (activPal [AP]), and ankle (StepWatch [SW]). The criterion measure was directly observed hand-counted steps (both in real-time and verified using video recording). Equivalence testing plots were generated to assess the criterion validity of each device. Unlike traditional null hypothesis testing, which seeks to determine whether there were any statistical differences between devices, equivalence testing evaluates agreement between the criterion and test device. The equivalence zone was set at ±0.2 SD of the criterion step count for each SADL. Devices were deemed equivalent to the criterion when their mean error and the 95% CI fell within the equivalence zone. RESULTS: On average, devices tended to underestimate (-4, -31, -28, -6 steps/min) for folding laundry, vacuuming, stair stepping, and overground walking, respectively. No devices fell inside the equivalence zone for folding laundry, vacuuming, and stair stepping. For preferred pace overground walking, only the SW and AP fell within the equivalence zone. CONCLUSIONS: No device performed well across the full range of activities; however, the SW and AP were deemed equivalent during preferred pace overground walking. Device manufacturers should aim to refine step algorithms to improve step-count accuracy across a wider range of ambulatory activities. FUNDING: NIH-NIA-5R01AG04902
CHARACTERIZATION OF FREE-LIVING STEP-BASED PHYSICAL ACTIVITY METRICS AMONG PATIENTS WITH FEMOROACETABULAR IMPINGEMENT SYNDROME
BACKGROUND: Femoroacetabular impingement syndrome (FAIS) is a hip-joint disorder characterized by abnormal bony morphology (femoral-sided, “cam”; or acetabular-sided, “pincer”). FAIS is a precursor to hip arthritis and is often associated with low physical activity (PA) due to pain. Previous studies have relied on self-report questionnaires to assess PA. Device-based measurement (e.g., accelerometry), specifically step-based metrics (e.g., steps/day and cadence indices), may offer a more comprehensive assessment of PA patterns in this population. METHODS: We recruited 25 participants with FAIS (age=31.0±9.2 years, 60% women, BMI=26.1±4.7 kg/m2) and 14 healthy controls (age=28.1±9.1 years, 64% women, BMI=26.3±3.4 kg/m2). Participants were categorized as Cam only, Combined (cam and pincer), or Healthy (controls). Participants wore a waist-mounted accelerometer (ActiGraph GT3X+, ActiGraph LLC, Pensacola, FL) for 7 days during waking hours. Step-based metrics were computed, including steps/day, peak 1- and 30-min cadence (PK1 and PK30; steps/min), and time spent in various cadence bands (1-19, 20-39, 40-59,⋯100-119 steps/min). One-way ANOVAs with post hoc testing were conducted to examine group differences. Effect sizes (eta squared; η2) were calculated and interpreted as small=0.01, medium=0.06, and large=0.14. RESULTS: We found significant group effects for PK1 and PK30 (p=0.02 and 0.05, η²=0.29 and 0.25, respectively). Post hoc tests showed lower PK1 and PK30 for Cam vs. Healthy (p=0.003 and 0.005, respectively) and Combined vs. Healthy (p=0.02 and 0.05, respectively). Similarly, there were main effects for time spent in slow, medium, and brisk cadence bands (60-79, 80-99, and 100-119 steps/min (p=0.004, 0.02, and 0.02; η²=0.27, 0.26, and 0.19, respectively). Post hoc tests indicated differences in time spent in these cadence bands for Cam vs. Healthy (p=0.007, 0.03, and 0.02, respectively), while Combined differed significantly from Healthy only for the slow and medium cadence bands (p=0.01 and 0.03, respectively). There was no main effect for steps/day between groups (p=0.06, η²=0.1). CONCLUSION: Although there was no main effect of group for steps/day, several cadence-based metrics were lower among the FAIS groups, particularly for Cam vs Healthy. Future studies are encouraged to examine step-based metrics in individuals with FAIS, as they appear to capture real-world differences in walking behaviors