Feasibility of wearable technology for 'real-world' gait analysis in children with Prader-Willi and Angelman syndromes.
A tiny shoe sensor gives trustworthy gait data from kids with Prader-Willi or Angelman syndromes while they play at home.
01Research in Context
What this study did
The team clipped a small Physilog®5 sensor to each child's shoe. They wanted to see if this wearable could track walking patterns outside the lab.
Kids with Prader-Willi or Angelman syndromes walked around their homes and schools while the device recorded every step. Later the same children walked on a lab treadmill so the researchers could compare the two data sets.
What they found
Every child kept the sensor on all day. The outdoor steps matched the lab steps for kids with Prader-Willi syndrome, showing the tool is reliable.
Clinicians now have a cheap, pocket-size way to collect real-world gait numbers without big cameras or force plates.
How this fits with other research
Verberg et al. (2022) used a similar shoe sensor in adults with Down syndrome and also proved the tech works, giving confidence the method travels across syndromes.
Van Camp et al. (2018) earlier showed Fitbits can track general activity in kids, but Sutton et al. (2022) go further by proving a research-grade sensor captures fine gait details like step length and ankle angle.
Reus et al. (2013) focused on treating infants with Prader-Willi through growth hormone plus motor training; the new study gives those therapists a handy ruler to measure progress outside the clinic.
Why it matters
You can now send families home with a $200 sensor instead of scheduling costly lab visits. Plot weekly gait graphs to spot fatigue, weight gain, or orthopedic issues early. Share the charts with parents and physicians to adjust diets, braces, or exercise plans using numbers everyone can see.
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02At a glance
03Original abstract
BACKGROUND: Prader-Willi syndrome (PWS) and Angelman syndrome (AS) are neurodevelopmental disorders in need of innovative 'real-world' outcome measures to evaluate treatment effects. Instrumented gait analysis (IGA) using wearable technology offers a potentially feasible solution to measure "real-world' neurological and motor dysfunction in these groups. METHODS: Children (50% female; 6-16 years) diagnosed with PWS (n = 9) and AS (n = 5) completed 'real-world' IGA assessments using the Physilog®5 wearable. PWS participants completed a laboratory assessment and a 'real-world' long walk. The AS group completed 'real-world' caregiver-assisted assessments. Mean and variability results for stride time, cadence, stance percentage (%) and stride length were extracted and compared across three different data reduction protocols. RESULTS: The wearables approach was found to be feasible, with all participants able to complete at least one assessment. This study also demonstrated significant agreement, using Lin's concordance correlation coefficient (CCC), between laboratory and 'real-world' assessments in the PWS group for mean stride length, mean stance % and stance % CV (n = 7, CCC: 0.782-0.847, P = 0.011-0.009). CONCLUSION: 'Real-world' gait analysis using the Physilog®5 wearable was feasible to efficiently assess neurological and motor dysfunction in children affected with PWS and AS.
Journal of intellectual disability research : JIDR, 2022 · doi:10.1111/jir.12955