FoG-Finder: Real-time Freezing of Gait Detection and Treatment

Freezing of gait is a serious symptom of Parkinson's disease that increases the risk of injury through falling, and reduces quality of life. Current clinical freezing of gait treatments fail to adequately address the fall risk posed by freezing of gait symptoms, and current real-time treatment...

Celý popis

Uložené v:
Podrobná bibliografia
Vydané v:IEEE/ACM Conference on Connected Health: Applications, Systems and Engineering Technologies (Online) Ročník 2023; s. 22 - 33
Hlavní autori: Koltermann, Kenneth, Jung, Woosub, Blackwell, GinaMari, Pinney, Abbott, Chen, Matthew, Cloud, Leslie, Pretzer-Aboff, Ingrid, Zhou, Gang
Médium: Konferenčný príspevok.. Journal Article
Jazyk:English
Vydavateľské údaje: ACM 01.06.2023
Predmet:
Feature extraction
freezing of gait
Injuries
neural networks
Parkinson's disease
Real-time systems
wearable devices
ISSN:2832-2975, 2832-2967, 2832-2975
On-line prístup:Získať plný text
Tagy: Pridať tag
Žiadne tagy, Buďte prvý, kto otaguje tento záznam!
Popis
Shrnutí:Freezing of gait is a serious symptom of Parkinson's disease that increases the risk of injury through falling, and reduces quality of life. Current clinical freezing of gait treatments fail to adequately address the fall risk posed by freezing of gait symptoms, and current real-time treatment systems have high false positive rates. To address this problem, we designed a closed-loop, non-intrusive, and real-time freezing of gait detection and treatment system, FoG-Finder, that automatically detects and treats freezing of gait. To evaluate FoG-Finder, we first collected 716 freezing of gait events from 11 patients. We then compared FoG-Finder against other real-time systems with our dataset. Our system was able to achieve a 13.4% higher F1 score and a 10.7% higher overall accuracy while achieving a reduction of 85.8% in the false positive treatment rate compared with other validated real-time freezing of gait detection and treatment systems. Additionally, FoG-Finder achieved an average treatment latency of 427ms and 615ms for subject-dependent and leave-one-subject-out settings, respectively, making it a viable system to treat freezing of gait in the real-world.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:2832-2975
2832-2967
2832-2975
DOI:10.1145/3580252.3586980