AI in gait for patients with Alzheimer’s Disease
Research type
Research Study
Full title
The application of artificial intelligence in the assessment of balance and gait for patients with Alzheimer’s Disease and the implications for diagnosis and rehabilitation
IRAS ID
332651
Contact name
Weijie Wang
Contact email
Sponsor organisation
TASC offices
Clinicaltrials.gov Identifier
ISRCTN, There is not an ISRCTN number here. Because there is no available funding due to student project.
Duration of Study in the UK
1 years, 10 months, 31 days
Research summary
Alzheimer’s Disease (AD) is a degenerative disease of the nervous system with insidious onset. It has become one of the leading causes of death and disability in the elderly population and has been identified as a major global health problem in the 21st century. AD accounts for 70% of dementia cases and has a preclinical period of 10-20 years. Mild cognitive impairment (MCI) is a prodromal stage of AD, and its early detection is considered crucial as it can help slow the progression of AD. Clinical research has recognised changes in the motor system in many participants with early AD. The balance and gait patterns of people with AD, people with MCI and people without cognitive impairment are quite different. The early diagnosis of AD remains difficult, and little research has been conducted to investigate the direct diagnosis of AD patients using motion analysis. This research project intends to investigate whether AD patients, MCI patients and people without cognitive impairment have different balance and gait and which biomechanical parameters could be used to assess the degree of AD and MCI. Also, it would design and develop a useful method or tool to diagnose patients potentially at an elevated risk of AD, allowing clinicians to make good protective means for those before AD. \n\nThere will be three groups of participants for the research: A) participants diagnosed with Alzheimer’s Disease; B) participants diagnosed with mild cognitive impairment (MCI); C) the healthy elderly group. Participants will be recruited through various sources, including volunteer recruitment posters displayed at the University of Dundee and Ninewells Hospital, recommendations from neurology doctors, and recruitment through Join Dementia Research (JDR) and the Neuroprogressive and Dementia Network of NHS. Participants will attend to the Motion Analysis Lab in the University Department of Orthopaedic and Trauma Surgery, TORT Centre, Ninewells Hospital for the data collection. In the lab, each participant will first complete both Free-Cog and the Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE) tests. The two tests are used to test Cognitive and functional assessments. Secondly, the participants will perform five basic movements used in daily life, i.e. different walking ways: 1) walking normally; 2) walking while counting a random number in a loud voice, 3) walking up and down the slight slope (15 deg), 4) walking over a road bump, and 5) sit-stand and walking will be performed. Participants will be allowed to rest for 10 minutes between the tasks.
REC name
North of Scotland Research Ethics Committee 2
REC reference
23/NS/0099
Date of REC Opinion
21 Sep 2023
REC opinion
Unfavourable Opinion