Human Activity Analysis In Smart Environments
Human Activity Analysis In Smart Environments
批准号:
2747358
负责人:
金额:
$0.0万
依托单位:
依托单位国家:
英国
项目类别:
Studentship
财政年份:
2022
资助国家:
英国
项目状态:
未结题
起止时间:
2022 至 --
中文摘要
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英文摘要
"(AI)-Driven Virtual Training BuddyRemote virtual fitness training has recently seen a massive boom. This trend is verywelcome not only because more people are engaging in physical activity, but also becauseof the sustainability of remote training.However, the interaction with coaches and training buddies still heavily relies on directhuman intervention limiting the affordability and customisability of the fitness training. Withrecent developments in computer vision and natural language processing new tools such asreliable markerless pose tracking and realistic language generation, the performance of thetrainee can be reliably tracked and realistic feedback can be given.The proposed project is about the creation of an artificially intelligent, autonomousvirtual training buddy that has the ability to communicate verbally and non-verbally with theuser effectively as well as to demonstrate exercises to the user. The aim of the personalisedhuman-like agent is to increase training motivation and ultimately training adherence.Thevirtual training buddy will establish initial rapport with the user, set goals and motivation inpre-training, guide the user during the training session, and provide post-training feedback.The investigation will be centred around what communication method and style(verbally and non-verbally) is the most effective to maximise the users' intrinsic and extrinsictraining motivation. The applicability of artificial intelligence techniques including machinelearning and computational intelligence methods for the optimal intervention timing andmethod will be studied. By establishing performance metrics for the set exercises, the agentwill try to estimate fatigue, and by adjusting rest times and exercise set length to keep thetrainee enged. Additionally, to achieve personalisation, we envisage building in mechanismsfor self-improvement of the autonomous virtual training buddy based on interactions with theuser. This project is in collaboration with the global, world-leading industrial partner"
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