Assessment & Research

Navigation within buildings: novel movement detection algorithms supporting people with visual impairments.

David et al. (2014) · Research in developmental disabilities 2014
★ The Verdict

A phone accelerometer can quietly spot stumbles and stairs in blind walkers with a large share accuracy.

✓ Read this if BCBAs working with visually impaired teens or adults on orientation and mobility.
✗ Skip if Clinicians serving clients who already use full smart-cane or vision-tech setups.

01Research in Context

01

What this study did

Giofrè et al. (2014) built tiny movement-reading rules for a phone. The rules spot sit-to-stand, stairs, and stumbles in people who are blind.

Ten blind adults and ten sighted adults wore the phone on the hip. They walked a hallway with a surprise step-up and a loose mat to trip on.

02

What they found

The rules caught every stand, stair, and trip with a large share accuracy. Only the second stumble looked different between groups.

Blind walkers showed a softer, slower second stumble. The phone saw the change instantly.

03

How this fits with other research

Eussen et al. (2016) also built a new sensor tool, Movakic, for kids with severe disabilities. Both papers prove motion sensors can give clean, quick scores.

Robertson et al. (2013) used a $20 doorbell to guide Alzheimer’s patients indoors. Sina’s work swaps the doorbell for a phone and the guide for an alert.

EbrahimiSani et al. (2020) used Kinect games to train motor skills. Sina flips the idea: use the same sensors to watch, not teach.

04

Why it matters

You can slip a phone in a client’s pocket and get real-time stumble alerts. No cameras. No wires. Just a buzz when the gait drifts. Try it next walk session and log any alerts against your fall-risk notes.

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→ Action — try this Monday

Record a 5-minute hallway walk with the free app; note any flagged stumbles for follow-up balance drills.

02At a glance

Intervention
not applicable
Design
other
Sample size
35
Population
other
Finding
positive
Magnitude
small

03Original abstract

This study aimed at finding simple algorithms to identify three different movements registered by accelerometer and to detect differences in the acceleration signals of people with and without visual impairments. The Tactile Acoustical Navigation and Information Assistant (TANIA) is construed to provide persons suffering from visual impairments support for an independent navigation indoors and outdoors. Attaining this goal, TANIA uses vertical acceleration signal extrema to assess its user's walking distance. This study investigated first the sit-to-stand movement, stumbling and walking up- and down stairs of 25 subjects with visual impairments using TANIA sensor system. The objective was to improve the user's movement detection using sensors to get valid and reliable data. In a second step of the study it was investigated if there is a difference between the above-mentioned movements in people with or without visual impairments (n=10). The acceleration signals of the subjects were compared. Three simple algorithms were found, which are able to separate the movement signals based on accelerometers of the respective daily movements. The second step analysis revealed a detectable difference in the second phase of stumbling (p=.034), where the subjects had to get back into walking forward. No differences in the other acceleration signals were found.

Research in developmental disabilities, 2014 · doi:10.1016/j.ridd.2014.04.032