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老年人日常锻炼期间使用的人体运动检测系统分析。

An analysis of human motion detection systems use during elder exercise routines.

作者信息

Alexander Gregory L, Havens Timothy C, Rantz Marilyn, Keller James, Casanova Abbott Carmen

机构信息

Sinclair School of Nursing, University of Missouri, S415, Columbia, MO 65211, USA.

出版信息

West J Nurs Res. 2010 Mar;32(2):233-49. doi: 10.1177/0193945909349947.

Abstract

Human motion analysis provides motion pattern and body pose estimations. This study integrates computer-vision techniques and explores a markerless human motion analysis system. Using human-computer interaction (HCI) methods and goals, researchers use a computer interface to provide feedback about range of motion to users. A total of 35 adults aged 65 and older perform three exercises in a public gym while human motion capture methods are used. Following exercises, participants are shown processed human motion images captured during exercises on a customized interface. Standardized questionnaires are used to elicit responses from users during interactions with the interface. A matrix of HCI goals (effectiveness, efficiency, and user satisfaction) and emerging themes are used to describe interactions. Sixteen users state the interface would be useful, but not necessarily for safety purposes. Users want better image quality, when expectations are matched satisfaction increases, and unclear meaning of motion measures decreases satisfaction.

摘要

人体运动分析可提供运动模式和身体姿势估计。本研究整合了计算机视觉技术,并探索了一种无标记人体运动分析系统。研究人员利用人机交互(HCI)方法和目标,通过计算机界面向用户提供关于运动范围的反馈。35名65岁及以上的成年人在公共健身房进行三项运动,同时使用人体运动捕捉方法。运动结束后,在定制界面上向参与者展示运动期间捕捉到的经过处理的人体运动图像。在与界面交互过程中,使用标准化问卷来获取用户的反馈。使用HCI目标矩阵(有效性、效率和用户满意度)以及新出现的主题来描述交互情况。16名用户表示该界面会有用,但不一定用于安全目的。用户希望图像质量更好,当期望得到满足时满意度会提高,而运动测量的含义不明确会降低满意度。

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