Evidence map›Paper›PMID 39262653›Full record

Article...IEEE...International Conference on Connected Health: Applications, Systems and Engineering Technologies. IEEE International Conference on Connected Health: Applications, Systems and Engineering Technologies2024

Gait-Guard: Turn-aware Freezing of Gait Detection for Non-intrusive Intervention Systems.

Kenneth Koltermann, John Clapham, GinaMari Blackwell, Woosub Jung, Evie N Burnet, Ye Gao, Huajie Shao, Leslie Cloud, Ingrid Pretzer-Aboff, Gang Zhou

Abstract read
In one paragraph

Article in ...IEEE...International Conference on Connected Health: Applications, Systems and Engineering Technologies. IEEE International Conference on Connected Health: Applications, Systems and Engineering Technologies, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

10 authors.

Kenneth KoltermannDepartment of Computer Science, William & Mary.
John ClaphamDepartment of Computer Science, William & Mary.
GinaMari BlackwellSchool of Nursing, Virginia Commonwealth University.
Woosub JungComputer & Information Sciences, Towson University.
Evie N BurnetDepartment of Kinesiology, William & Mary.
Ye GaoDepartment of Computer Science, William & Mary.
Huajie ShaoDepartment of Computer Science, William & Mary.
Leslie CloudDepartment of Neurology, Virginia Commonwealth University.
Ingrid Pretzer-AboffSchool of Nursing, Virginia Commonwealth University.
Gang ZhouDepartment of Computer Science, William & Mary.

Funding

SCH: Context-Aware Freezing of Gait Mitigation in Real-World SettingR01NS120560 · NINDS · VIRGINIA COMMONWEALTH UNIVERSITY · PI CLOUD, LESLIE J, PRETZER-ABOFF, INGRID A · 2021 to 2024
$1.2M
NINDS NIH HHS R01 NS120560
6 · The paper itself

Abstract

Freezing of gait significantly reduces the quality of life for Parkinson's disease patients by increasing the risk of injurious falls and reducing mobility. Real-time intervention mechanisms promise relief from these symptoms, but require accurate real-time, portable freezing of gait detection systems to be effective. Current real-time detection systems have unacceptable false positive freezing of gait identification rates to be adopted by the patients for real-world use. To rectify this, we propose Gait-Guard, a closed-loop, real-time, and portable freezing of gait detection and intervention system that treats symptoms in real-time with a low false positive rate. We collected 1591 freezing of gait events across 26 patients to evaluate Gait-Guard. Gait-Guard achieved a 112% reduction in the false positive intervention rate when compared with other validated real-time freezing of gait detection systems, and detected 96.5% of the true positives with an average intervention latency of just 378.5ms in a subject-independent study, making Gait-Guard a practical system for patients to use in their daily lives.

Indexed as

Freezing of GaitParkinson’s DiseaseTransformer Neural NetworksWearable Devices

Identifiers

PMID39262653
PMCPMC11384236

What OpenQuestion holds

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Registered trials

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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.