论文标题
从时空环境中预测主导的手段变化的生理数据
Predicting dominant hand from spatiotemporal context varying physiological data
论文作者
论文摘要
来自腕上的设备的健康指标要求自动主导预测以保持准确的操作。该预测将提高可靠性，增强消费者的体验，并鼓励进一步发展医疗保健应用。本文旨在评估双手实验中生理和时空上下文信息的使用，以预测商业智能手表的手腕。主要贡献是一种方法，以获取有效的模型和低样本速率生理传感器的特征和自我报告的上下文调查。结果表明，使用来自现实生活中的单个受试者的数据，有效的主导性预测。
Health metrics from wrist-worn devices demand an automatic dominant hand prediction to keep an accurate operation. The prediction would improve reliability, enhance the consumer experience, and encourage further development of healthcare applications. This paper aims to evaluate the use of physiological and spatiotemporal context information from a two-hand experiment to predict the wrist placement of a commercial smartwatch. The main contribution is a methodology to obtain an effective model and features from low sample rate physiological sensors and a self-reported context survey. Results show an effective dominant hand prediction using data from a single subject under real-life conditions.
