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NeuralGait: Assessing Brain Health Using Your Smartphone by Huining Li; Huan Chen; Chenhan Xu; Zhengxiong Li; Hanbin Zhang; Xiaoye Qian; Dongmei Li; Ming-chun Huang; Wenyao Xu is a Computer Science article available to read on EtoBox.
What is NeuralGait: Assessing Brain Health Using Your Smartphone about?
Brain health attracts more recent attention as the population ages. Smartphone-based gait sensing and analysis can help identify the risks of brain diseases in daily life for prevention. Existing gait analysis approaches mainly hand-craft temporal gait features or developing CNN-based feature extractors, but they are either prone to lose some inconspicuous pathological information or are only dedicated to a single brain disease screening. We discover that the relationship between gait segments can be used as a principle and generic indicator to quantify multiple pathological patterns. In this paper, we propose NeuralGait, a pervasive smartphone-cloud system that passively captures and analyzes principle gait segments relationship for brain health assessment. On the smartphone end, inertial gait data are collected while putting the smartphone in the pants pocket. We then craft local temporal-frequent gait domain features and develop a self-attention-based gait segment relationship encoder. Afterward, the domain features and relation features are fed to a scalable RiskNet in the cloud for brain health assessment. We also design a pathological hot update protocol to efficiently add ne
Who reads NeuralGait: Assessing Brain Health Using Your Smartphone?
It is typically read by researchers, students, and practitioners in Computer Science.
- Author
- Huining Li; Huan Chen; Chenhan Xu; Zhengxiong Li; Hanbin Zhang; Xiaoye Qian; Dongmei Li; Ming-chun Huang; Wenyao Xu
- Publisher
- ACM
- Published
- 2022
- Language
- EN
- Field
- Computer Science (Physical Sciences)