Evidence map›Paper›PMID 38434031›Full record

ArticleHeliyon2024

A novel wearable biofeedback system to prevent trip-related falls.

Shilpa Jacob, Geoff Fernie, Atena Roshan Fekr

Abstract read
In one paragraph

Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Shilpa JacobThe Kite Research Institute, Toronto Rehabilitation Institute-University Health Network, Toronto, ON, M5G 2A2, Canada.
Geoff FernieThe Kite Research Institute, Toronto Rehabilitation Institute-University Health Network, Toronto, ON, M5G 2A2, Canada.
Atena Roshan FekrThe Kite Research Institute, Toronto Rehabilitation Institute-University Health Network, Toronto, ON, M5G 2A2, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Real-time gait monitoring of older adults and gait-impaired individuals while providing real-time biofeedback has the potential to help reduce trip-related falls. A low or unsuccessful Minimum Toe Clearance (MTC) is considered a predictor of tripping risk. Thus, increasing the MTC can be a key component in minimizing the likelihood of tripping. This paper discusses a proof-of-concept wearable system that estimates the MTC in real-time using two Time-of-Flight (ToF) sensors and provides auditory biofeedback to alert users if they have a low MTC during everyday walking activities. Ten healthy female adults were asked to perform two experiments: 1) walk at a predetermined speed to evaluate the proposed real-time MTC detection algorithm, and 2) walk in four conditions: baseline, biofeedback with no distraction, biofeedback with distraction 1 (talking on the phone), and biofeedback with distraction 2 (playing a simple mobile game). The average MTC values were significantly greater during all feedback conditions than the baseline, indicating that the proposed system could successfully warn users to increase their MTC in real-time.

Indexed as

BiofeedbackFall preventionFoot clearanceGait analysisTime-of-flight sensorTrippingWearable

Identifiers

PMID38434031
PMCPMC10906283

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.