跳至主要内容
临床试验/NCT07580612
NCT07580612招募中不适用

Artificial Intelligence-Driven Freezing Of Gait Detection in the Home: Investigating How Free-living Activities Affect the Algorithm

KU Leuven3 个研究点 分布在 3 个国家目标入组 126 人开始时间: 2025年9月22日最近更新:

试验速览

阶段
不适用
状态
招募中
发起方
KU Leuven
入组人数
126
试验地点
3

研究概览

简要总结

Freezing of gait (FOG) is a debilitating symptom of Parkinson's disease increases the risk of falling. Despite being a common symptom, it is still difficult to evaluate freezing of gait quickly and accurately. Currently, the gold-standard method to determine the severity of FOG is a manual analysis of video footage by an experienced assessor, collected during standardized FOG-provoking walking tests. Because this is a very time-intensive process, where different assessors sometimes obtain different results, our team at KU Leuven have developed an artificial-intelligent (AI) algorithm trained to identify FOG episodes based on wearable inertial measurement unit (IMU) sensor data. The AI algorithm has already undergone initial validation during laboratory testing, yielding promising results. The aim of this study is to investigate whether the AI algorithm can accurately detect FOG episodes in a less controlled environment, namely the home environment. In a second phase, the investigators will also use the collected data to improve the AI algorithm for automated FOG detection in the home. Finally, the investigators want to explore whether the AI algorithm can detect FOG in real-time.

研究设计

研究类型
Observational
观察模型
Cohort
时间视角
Prospective

入排标准

年龄范围
18 Years 至 —(Adult, Older Adult)
性别
All
接受健康志愿者

入选标准

  • For all participants
  • Voluntary written informed consent of the participant has been obtained prior to any study-related procedures, except the non-recorded pre-screening questions;
  • At least 18 years of age at the time of signing the Informed Consent Form (ICF);
  • Person is cognitively able to follow and understand instructions and provide voluntary written informed consent;
  • Person is able to walk for short distances (± 10 meters) independently, with- or without use of a walking aid;
  • Person does not live in a temporary or permanent care facility.
  • For participants with PD:
  • Clinical diagnosis of Parkinson's disease (PD) made by a neurologist according to the Movement Disorders Society guidelines;
  • Person self-reports to experience daily FOG (for recruitment of freezers only);
  • Person is willing to temporarily delay the morning anti-Parkinsonian medication during the standardized assessment visit.

排除标准

  • Occurrence of any of the following within 3 months prior to informed consent: myocardial infarction, hospitalization for unstable angina, stroke, coronary artery bypass graft (CABG), percutaneous coronary intervention (PCI), implantation of a cardiac resynchronization therapy device (CRTD), active treatment for cancer or other malignant disease, uncontrolled congestive heart disease (NYHA class >3), acute psychosis or major psychiatric disorders or continued substance abuse, other neurological (than PD) or orthopaedic impairment that significantly impacts on gait;
  • Participant self-reports daily falls;
  • Participation in another interventional study, with or without an investigational medicinal product (IMP) or device (IMD)

研究者

发起方
KU Leuven
申办方类型
Other
责任方
Principal Investigator
主要研究者

Moran Gilat

Prof

KU Leuven

研究点 (3)

Loading locations...

相似试验

AID-FOG: Artificial Intelligence-Driven Freezing of... | 临床试验