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AID-FOG: Artificial Intelligence-Driven Freezing of Gait Detection in the Home (AID-FOG)

2026년 5월 5일 업데이트: Moran Gilat, KU Leuven

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

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.

연구 개요

상태

모병

정황

연구 유형

관찰

등록 (추정된)

126

연락처 및 위치

이 섹션에서는 연구를 수행하는 사람들의 연락처 정보와 이 연구가 수행되는 장소에 대한 정보를 제공합니다.

연구 장소

  • 독일
  • 벨기에
      • Leuven, 벨기에, 3001
        • 모병
        • Department of Rehabilitation Sciences
        • 연락하다:
        • 연락하다:
        • 수석 연구원:
          • Moran Gilat
  • 이스라엘
      • Tel Aviv, 이스라엘, 64
        • 아직 모집하지 않음
        • Center for the study of movement, cognition and mobility
        • 연락하다:

참여기준

연구원은 적격성 기준이라는 특정 설명에 맞는 사람을 찾습니다. 이러한 기준의 몇 가지 예는 개인의 일반적인 건강 상태 또는 이전 치료입니다.

자격 기준

공부할 수 있는 나이

  • 성인
  • 고령자

건강한 자원 봉사자를 받아들입니다

예

샘플링 방법

비확률 샘플

연구 인구

People with PD and healthy age-matched controls will be recruited from three primary sites, namely KU Leuven, Hamburg Medical Center, and Tel-Aviv Sourasky Medical Center.

설명

Inclusion Criteria:

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.

Exclusion criteria:

  • 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)

공부 계획

이 섹션에서는 연구 설계 방법과 연구가 측정하는 내용을 포함하여 연구 계획에 대한 세부 정보를 제공합니다.

연구는 어떻게 설계됩니까?

디자인 세부사항

코호트 및 개입

그룹/코호트
건강한 통제
건강한 노인
Freezers
Patients with Parkinson's disease who self-report to experience Freezing of Gait daily.
Non-freezers
Patients with Parkinson's disease who do not experience Freezing of Gait.

연구는 무엇을 측정합니까?

주요 결과 측정

결과 측정
측정값 설명
기간
Comparing the agreement between AID-FOG and gold-standard expert annotation to detect the percentage of time spent with freezing of gait (FOG) in relation to total time duration (%TF).
기간: T0=test day 1: free-living gait assessment (5 hours), T1=test day 2: free-living gait (5 hours) and T2= test day 3: standardized gait (4 hours)
The primary outcome (percentage of time spent with FOG in relation to total task duration = %TF) will be established by manual annotations of video footage by an experienced assessor (=gold-standard reference) and by the automated AID-FOG algorithm v1.0 applied post-hoc (i.e. offline) to IMU data collected during the same walking tasks. This will be calculated for standardized walking tasks on which the AID-FOG algorithm has been trained, standardized walking tasks on which the AID-FOG algorithm was not trained, and a free-living walking condition on which the AID-FOG algorithm was not trained.
T0=test day 1: free-living gait assessment (5 hours), T1=test day 2: free-living gait (5 hours) and T2= test day 3: standardized gait (4 hours)

2차 결과 측정

결과 측정
측정값 설명
기간
F1-score
기간: T0=test day 1: free-living gait assessment (5 hours), T1=test day 2: free-living gait (5 hours) and T2= test day 3: standardized gait (4 hours)
Same as primary outcome, but now for the F1-score (rather than percent TF). F1 scores range between 0 and 1, the higher the score the better.
T0=test day 1: free-living gait assessment (5 hours), T1=test day 2: free-living gait (5 hours) and T2= test day 3: standardized gait (4 hours)
Number of FOG episodes
기간: T0: free-living gait (5 hours), T1: free-living gait (5 hours) and T2: standardized gait (4 hours)
Same as primary outcome, but now for the absolute number of FOG episodes.
T0: free-living gait (5 hours), T1: free-living gait (5 hours) and T2: standardized gait (4 hours)
The performance of the AID-FOG algorithm to differentiate between the FOG manifestations.
기간: T0=test day 1: free-living gait assessment (5 hours), T1=test day 2: free-living gait (5 hours) and T2= test day 3: standardized gait (4 hours)
Freezing of gait (FOG) manifests in multiple forms, including akinetic and kinetic subtypes, which may be associated with trembling or occur without it. This study investigates the performance of AID-FOG in discriminating between these manifestations, using expert annotations as the reference standard.
T0=test day 1: free-living gait assessment (5 hours), T1=test day 2: free-living gait (5 hours) and T2= test day 3: standardized gait (4 hours)
Comparing performance of AID-FOG to detect freezing in OFF and ON medication states.
기간: T0=test day 1: free-living gait assessment (5 hours), T1=test day 2: free-living gait (5 hours) and T2= test day 3: standardized gait (4 hours)
The FOG outcomes as obtained by the human expert and the offline AID-FOG algorithm v1.0 will be calculated for both the OFF and ON medication states. These scores will be compared to evaluate the change in algorithm performance depending on medication status. The FOG outcomes will be the percentage TF which ranges between 0-100 percent. The higher the percentage the more freezing the patient has. But also the F1-score which ranges between 0-1. The higher the score the more overlap there is between the expert and the algorithm.
T0=test day 1: free-living gait assessment (5 hours), T1=test day 2: free-living gait (5 hours) and T2= test day 3: standardized gait (4 hours)
Consistency of FOG detection with AID-FOG compared between two free-living assessments
기간: T0= test day 1: free-living gait (5 hours) and T1= test day 2: free-living gait (5 hours)
The agreement in FOG detection (%TF, F1-score) between the AID-FOG algorithm and the gold-standard human annotations will be compared between the two free-living test days.
T0= test day 1: free-living gait (5 hours) and T1= test day 2: free-living gait (5 hours)
The number of false detections of FOG episodes during free-living
기간: T0=test day 1: free-living gait assessment (5 hours), T1=test day 2: free-living gait (5 hours) and T2= test day 3: standardized gait (4 hours)
The absolute sum of false detections made by the algorithm.
T0=test day 1: free-living gait assessment (5 hours), T1=test day 2: free-living gait (5 hours) and T2= test day 3: standardized gait (4 hours)
Comparing AID-FOG with subjective FOG
기간: T0=test day 1: free-living gait assessment (5 hours), T1=test day 2: free-living gait (5 hours) and T2= test day 3: standardized gait (4 hours)
The FOG outcomes obtained with AID-FOG will be correlated to the total score of the New Freezing of Gait Questionnaire (NFOGQ) and Patient Reported Outcomes of FOG (PRO).
T0=test day 1: free-living gait assessment (5 hours), T1=test day 2: free-living gait (5 hours) and T2= test day 3: standardized gait (4 hours)
Performance of automated FOG detection during free-living mobility
기간: 1 week of free-living mobility with IMU
The FOG outcomes obtained with AID-FOG offline will be calculated from multiple days of free-living mobility IMU data. These outcomes will be correlated to FOG severity as determined during the observed walking tasks of the project and self-reported FOG severity.
1 week of free-living mobility with IMU

기타 결과 측정

결과 측정
측정값 설명
기간
AID-FOG version 2.0 (percentage TF)
기간: T0=test day 1: free-living gait assessment (5 hours), T1=test day 2: free-living gait (5 hours) and T2= test day 3: standardized gait (4 hours)

The data obtained in the study will be used to train the AID-FOG algorithm v1.0. This trained AID-FOG algorithm v2.0 will be evaluated using the same listed outcome measures, using a leave-one-subject-out approach.

Percentage of time spent with FOG in relation to total task duration (= %TF) will be established by manual annotations of video footage by an experienced assessor (=gold-standard reference) and by the automated AID-FOG algorithm v2.0 applied post-hoc (i.e. offline) to IMU data collected during the same walking tasks. This will be calculated for standardized walking tasks on which the AID-FOG algorithm has been trained, standardized walking tasks on which the AID-FOG algorithm was not trained, and a free-living walking condition on which the AID-FOG algorithm was not trained.
T0=test day 1: free-living gait assessment (5 hours), T1=test day 2: free-living gait (5 hours) and T2= test day 3: standardized gait (4 hours)
AID-FOG version 2.0 (F1-score)
기간: T0=test day 1: free-living gait assessment (5 hours), T1=test day 2: free-living gait (5 hours) and T2= test day 3: standardized gait (4 hours)
The data obtained in the study will be used to train the AID-FOG algorithm v1.0. This trained AID-FOG algorithm v2.0 will be evaluated using the same listed outcome measures, using a leave-one-subject-out approach. Same as percentage TF, but now for the F1-score (rather than percent TF). F1 scores range between 0 and 1, the higher the score the better.
T0=test day 1: free-living gait assessment (5 hours), T1=test day 2: free-living gait (5 hours) and T2= test day 3: standardized gait (4 hours)
AID-FOG version 2.0 (Number of FOG episodes)
기간: T0=test day 1: free-living gait assessment (5 hours), T1=test day 2: free-living gait (5 hours) and T2= test day 3: standardized gait (4 hours)
The data obtained in the study will be used to train the AID-FOG algorithm v1.0. This trained AID-FOG algorithm v2.0 will be evaluated using the same listed outcome measures, using a leave-one-subject-out approach. Same as percentage TF, but now for the absolute number of FOG episodes.
T0=test day 1: free-living gait assessment (5 hours), T1=test day 2: free-living gait (5 hours) and T2= test day 3: standardized gait (4 hours)
AID-FOG version 2.0 (FOG manifestations)
기간: T0=test day 1: free-living gait assessment (5 hours), T1=test day 2: free-living gait (5 hours) and T2= test day 3: standardized gait (4 hours)
The data obtained in the study will be used to train the AID-FOG algorithm v1.0. This trained AID-FOG algorithm v2.0 will be evaluated using the same listed outcome measures, using a leave-one-subject-out approach. The performance of the AID-FOG algorithm v2.0 to discriminate between the FOG manifestations. Freezing of gait (FOG) manifests in multiple forms, including akinetic and kinetic subtypes, which may be associated with trembling or occur without it. This study investigates the performance of AID-FOG in discriminating between these manifestations, using expert annotations as the reference standard.
T0=test day 1: free-living gait assessment (5 hours), T1=test day 2: free-living gait (5 hours) and T2= test day 3: standardized gait (4 hours)
AID-FOG version 2.0 (OFF/ON medication)
기간: T0=test day 1: free-living gait assessment (5 hours), T1=test day 2: free-living gait (5 hours) and T2= test day 3: standardized gait (4 hours)
The data obtained in the study will be used to train the AID-FOG algorithm v1.0. This trained AID-FOG algorithm v2.0 will be evaluated using the same listed outcome measures, using a leave-one-subject-out approach. Comparing performance of AID-FOG v2.0 to detect freezing in OFF and ON medication states. The FOG outcomes as obtained by the human expert and the offline AID-FOG algorithm v2.0 will be calculated for both the OFF and ON medication states. These scores will be compared to evaluate the change in algorithm performance depending on medication status. The FOG outcomes will be the percentage TF which ranges between 0-100 percent. The higher the percentage the more freezing the patient has. But also the F1-score which ranges between 0-1. The higher the score the more overlap there is between the expert and the algorithm.
T0=test day 1: free-living gait assessment (5 hours), T1=test day 2: free-living gait (5 hours) and T2= test day 3: standardized gait (4 hours)
AID-FOG version 2.0 (consistency of detection during two free-living assessments)
기간: T0=test day 1: free-living gait assessment (5 hours), T1=test day 2: free-living gait (5 hours) and T2= test day 3: standardized gait (4 hours)
The data obtained in the study will be used to train the AID-FOG algorithm v1.0. This trained AID-FOG algorithm v2.0 will be evaluated using the same listed outcome measures, using a leave-one-subject-out approach. Consistency of FOG detection with AID-FOG v2.0 compared between two free-living assessments. The agreement in FOG detection (%TF, F1-score) between the AID-FOG algorithm v2.0 and the gold-standard human annotations will be compared between the two free-living test days.
T0=test day 1: free-living gait assessment (5 hours), T1=test day 2: free-living gait (5 hours) and T2= test day 3: standardized gait (4 hours)
AID-FOG version 2.0 (number of false positives)
기간: T0=test day 1: free-living gait assessment (5 hours), T1=test day 2: free-living gait (5 hours) and T2= test day 3: standardized gait (4 hours)
The data obtained in the study will be used to train the AID-FOG algorithm v1.0. This trained AID-FOG algorithm v2.0 will be evaluated using the same listed outcome measures, using a leave-one-subject-out approach. The number of false detections (AID-FOG v2.0) of FOG episodes during free-living
T0=test day 1: free-living gait assessment (5 hours), T1=test day 2: free-living gait (5 hours) and T2= test day 3: standardized gait (4 hours)
AID-FOG version 2.0 (subjective FOG)
기간: T0=test day 1: free-living gait assessment (5 hours), T1=test day 2: free-living gait (5 hours) and T2= test day 3: standardized gait (4 hours)
The data obtained in the study will be used to train the AID-FOG algorithm v1.0. This trained AID-FOG algorithm v2.0 will be evaluated using the same listed outcome measures, using a leave-one-subject-out approach. Comparing AID-FOG v2.0 with subjective FOG. The FOG outcomes obtained with AID-FOG v2.0 will be correlated to the total score of the New Freezing of Gait Questionnaire (NFOGQ) and Patient Reported Outcomes of FOG (PRO).
T0=test day 1: free-living gait assessment (5 hours), T1=test day 2: free-living gait (5 hours) and T2= test day 3: standardized gait (4 hours)
AID-FOG online (percentage TF)
기간: T0=test day 1: free-living gait assessment (5 hours), T1=test day 2: free-living gait (5 hours) and T2= test day 3: standardized gait (4 hours)
The AID-FOG algorithm will be modified for real-time FOG detection. Performance of this AID-FOG online algorithm will be compared with AID-FOG offline versions, using the same listed outcomes. Percentage of time spent with FOG in relation to total task duration (= %TF) will be established by manual annotations of video footage by an experienced assessor (=gold-standard reference) and by the automated AID-FOG online to IMU data collected during the same walking tasks. This will be calculated for standardized walking tasks on which the AID-FOG algorithm has been trained, standardized walking tasks on which the AID-FOG algorithm was not trained, and a free-living walking condition on which the AID-FOG algorithm was not trained.
T0=test day 1: free-living gait assessment (5 hours), T1=test day 2: free-living gait (5 hours) and T2= test day 3: standardized gait (4 hours)
AID-FOG online (F1-score)
기간: T0=test day 1: free-living gait assessment (5 hours), T1=test day 2: free-living gait (5 hours) and T2= test day 3: standardized gait (4 hours)
The AID-FOG algorithm will be modified for real-time FOG detection. Performance of this AID-FOG online algorithm will be compared with AID-FOG offline versions, using the same listed outcomes. Same as percentage TF, but now for the F1-score (rather than percent TF). F1 scores range between 0 and 1, the higher the score the better.
T0=test day 1: free-living gait assessment (5 hours), T1=test day 2: free-living gait (5 hours) and T2= test day 3: standardized gait (4 hours)
AID-FOG online (number of FOG episodes)
기간: T0=test day 1: free-living gait assessment (5 hours), T1=test day 2: free-living gait (5 hours) and T2= test day 3: standardized gait (4 hours)
The AID-FOG algorithm will be modified for real-time FOG detection. Performance of this AID-FOG online algorithm will be compared with AID-FOG offline versions, using the same listed outcomes. Same as percentage TF, but now for the absolute number of FOG episodes.
T0=test day 1: free-living gait assessment (5 hours), T1=test day 2: free-living gait (5 hours) and T2= test day 3: standardized gait (4 hours)
AID-FOG online (FOG manifestations)
기간: T0=test day 1: free-living gait assessment (5 hours), T1=test day 2: free-living gait (5 hours) and T2= test day 3: standardized gait (4 hours)
The AID-FOG algorithm will be modified for real-time FOG detection. Performance of this AID-FOG online algorithm will be compared with AID-FOG offline versions, using the same listed outcomes. The performance of the AID-FOG online algorithm to discriminate between the FOG manifestations.
T0=test day 1: free-living gait assessment (5 hours), T1=test day 2: free-living gait (5 hours) and T2= test day 3: standardized gait (4 hours)
AID-FOG online (OFF/ON medication)
기간: T0=test day 1: free-living gait assessment (5 hours), T1=test day 2: free-living gait (5 hours) and T2= test day 3: standardized gait (4 hours)
The AID-FOG algorithm will be modified for real-time FOG detection. Performance of this AID-FOG online algorithm will be compared with AID-FOG offline versions, using the same listed outcomes. The FOG outcomes as obtained by the human expert and the offline AID-FOG online algorithm will be calculated for both the OFF and ON medication states. These scores will be compared to evaluate the change in algorithm performance depending on medication status. The FOG outcomes will be the percentage TF which ranges between 0-100 percent. The higher the percentage the more freezing the patient has. But also the F1-score which ranges between 0-1. The higher the score the more overlap there is between the expert and the algorithm.
T0=test day 1: free-living gait assessment (5 hours), T1=test day 2: free-living gait (5 hours) and T2= test day 3: standardized gait (4 hours)
AID-FOG online (agreement of the detection between two free-living test days)
기간: T0=test day 1: free-living gait assessment (5 hours), T1=test day 2: free-living gait (5 hours) and T2= test day 3: standardized gait (4 hours)
The AID-FOG algorithm will be modified for real-time FOG detection. Performance of this AID-FOG online algorithm will be compared with AID-FOG offline versions, using the same listed outcomes. The agreement in FOG detection (%TF, F1-score) between the AID-FOG online algorithm and the gold-standard human annotations will be compared between the two free-living test days.
T0=test day 1: free-living gait assessment (5 hours), T1=test day 2: free-living gait (5 hours) and T2= test day 3: standardized gait (4 hours)
AID-FOG online (number false positives)
기간: T0=test day 1: free-living gait assessment (5 hours), T1=test day 2: free-living gait (5 hours) and T2= test day 3: standardized gait (4 hours)
The AID-FOG algorithm will be modified for real-time FOG detection. Performance of this AID-FOG online algorithm will be compared with AID-FOG offline versions, using the same listed outcomes. The absolute sum of false detections made by the online algorithm.
T0=test day 1: free-living gait assessment (5 hours), T1=test day 2: free-living gait (5 hours) and T2= test day 3: standardized gait (4 hours)
AID-FOG online (subjective FOG)
기간: T0=test day 1: free-living gait assessment (5 hours), T1=test day 2: free-living gait (5 hours) and T2= test day 3: standardized gait (4 hours)
The AID-FOG algorithm will be modified for real-time FOG detection. Performance of this AID-FOG online algorithm will be compared with AID-FOG offline versions, using the same listed outcomes. Comparing AID-FOG online with subjective FOG. The FOG outcomes obtained with AID-FOG online will be correlated to the total score of the New Freezing of Gait Questionnaire (NFOGQ) and Patient Reported Outcomes of FOG (PRO).
T0=test day 1: free-living gait assessment (5 hours), T1=test day 2: free-living gait (5 hours) and T2= test day 3: standardized gait (4 hours)

공동 작업자 및 조사자

여기에서 이 연구와 관련된 사람과 조직을 찾을 수 있습니다.

스폰서

KU Leuven

협력자

Michael J. Fox Foundation for Parkinson's Research
Tel Aviv Medical Center
Medical School Hamburg

간행물 및 유용한 링크

연구에 대한 정보 입력을 담당하는 사람이 자발적으로 이러한 간행물을 제공합니다. 이것은 연구와 관련된 모든 것에 관한 것일 수 있습니다.

일반 간행물

유용한 링크

연구 기록 날짜

이 날짜는 ClinicalTrials.gov에 대한 연구 기록 및 요약 결과 제출의 진행 상황을 추적합니다. 연구 기록 및 보고된 결과는 공개 웹사이트에 게시되기 전에 특정 품질 관리 기준을 충족하는지 확인하기 위해 국립 의학 도서관(NLM)에서 검토합니다.

연구 주요 날짜

연구 시작 (실제)

2025년 9월 22일

기본 완료 (추정된)

2027년 6월 1일

연구 완료 (추정된)

2027년 6월 1일

연구 등록 날짜

최초 제출

2026년 4월 2일

QC 기준을 충족하는 최초 제출

2026년 5월 5일

처음 게시됨 (실제)

2026년 5월 12일

연구 기록 업데이트

마지막 업데이트 게시됨 (실제)

2026년 5월 12일

QC 기준을 충족하는 마지막 업데이트 제출

2026년 5월 5일

마지막으로 확인됨

2026년 5월 1일

추가 정보

이 연구와 관련된 용어

추가 관련 MeSH 약관

기타 연구 ID 번호

  • S70220
  • MJFF-024628 (기타 보조금/기금 번호: Micheal J. Fox)

개별 참가자 데이터(IPD) 계획

개별 참가자 데이터(IPD)를 공유할 계획입니까?

미정

IPD 계획 설명

The datasets could be made available under restricted access after publication of the results, following ethical approval and a data-transfer agreement. GDPR and privacy regulations will be adhered to.

약물 및 장치 정보, 연구 문서

미국 FDA 규제 의약품 연구

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미국 FDA 규제 기기 제품 연구

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이 정보는 변경 없이 clinicaltrials.gov 웹사이트에서 직접 가져온 것입니다. 귀하의 연구 세부 정보를 변경, 제거 또는 업데이트하도록 요청하는 경우 register@clinicaltrials.gov. 문의하십시오. 변경 사항이 clinicaltrials.gov에 구현되는 즉시 저희 웹사이트에도 자동으로 업데이트됩니다. .

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