Ahmadi Amin, Richter Chris, O'Connor Noel E, Moran Kieran
Annu Int Conf IEEE Eng Med Biol Soc. 2015;2015:2034-7. doi: 10.1109/EMBC.2015.7318786.
Within this paper we demonstrate the effectiveness of a novel body-worn gait monitoring and analysis framework to both accurately and automatically assess gait during `free-living' conditions. Key features of the system include the ability to automatically identify individual steps within specific gait conditions, and the implementation of continuous waveform analysis within an automated system for the generation of temporally normalized data and their statistical comparison across subjects.
在本文中,我们展示了一种新型的可穿戴式步态监测与分析框架在“自由生活”条件下准确、自动评估步态的有效性。该系统的关键特性包括能够在特定步态条件下自动识别单个步幅,以及在自动化系统中实施连续波形分析以生成时间归一化数据并对不同受试者的数据进行统计比较。