Moufawad El Achkar Christopher, Lenoble-Hoskovec Constanze, Major Kristof, Paraschiv-Ionescu Anisoara, Büla Christophe, Aminian Kamiar
Laboratory of Movement Analysis and Measurement, Ecole Polytechnique Fédérale de Lausanne (EPFL), 1015 Lausanne, Switzerland.
Centre Hospitalier Universitaire Vaudois (CHUV), Service de gériatrie et réadaptation gériatrique, 1011 Lausanne, Switzerland.
Stud Health Technol Inform. 2016;225:663-7.
Activity monitoring in daily life is gaining momentum as a health assessment tool, especially in older adults and at-risk populations. Several research-based and commercial systems have been proposed with varying performances in classification accuracy. Configurations with many sensors are generally accurate but cumbersome, whereas single sensors tend to have lower accuracies. To this end, we propose an instrumented shoes system capable of accurate activity classification and gait analysis that contains sensors located entirely at the level of the shoes. One challenge in daily activity monitoring is providing punctual and subject-tailored feedback to improve mobility. Therefore, the instrumented shoe system was equipped with a Bluetooth® module to transmit data to a smartphone and perform detailed activity profiling of the monitored subjects. The potential applications of such a system are numerous in mobility and fall risk-assessment as well as in fall prevention.
作为一种健康评估工具，日常生活活动监测正日益受到关注，尤其是在老年人和高危人群中。已经提出了几种基于研究和商业的系统，其分类准确率各不相同。配备许多传感器的配置通常很准确，但很笨重，而单个传感器的准确率往往较低。为此，我们提出了一种能够进行准确活动分类和步态分析的智能鞋系统，该系统的传感器完全位于鞋子的层面。日常活动监测中的一个挑战是提供及时且针对个体的反馈以改善行动能力。因此，该智能鞋系统配备了蓝牙模块，用于将数据传输到智能手机，并对被监测对象进行详细的活动分析。这种系统在行动能力和跌倒风险评估以及跌倒预防方面有许多潜在应用。
