OU-ISIR Wearable Sensor-based Gait Challenge: Age and Gender
OU-ISIR Wearable Sensor-based Gait Challenge: Age and Gender
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DOI：
10.1109/icb45273.2019.8987235
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发表时间：
2019-06
期刊：
影响因子：
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通讯作者：
T. N. Thanh;Yuichi Hattori;Md. Atiqur Rahman Ahad;Anindya Das Antar;Masud Ahmed;D. Muramatsu;Yasushi Makihara;Y. Yagi;Sozo Inoue;Tahera Hossain
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文献类型：
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作者：
T. N. Thanh;Yuichi Hattori;Md. Atiqur Rahman Ahad;Anindya Das Antar;Masud Ahmed;D. Muramatsu;Yasushi Makihara;Y. Yagi;Sozo Inoue;Tahera Hossain
近年来，以智能手机为代表的可穿戴计算资源由于技术的进步和对人类生活的巨大支持而得到了快速发展。人们正在使用智能手机进行通信、工作、娱乐、商务、旅游和浏览信息。然而，由于许多挑战，医疗保健应用非常有限。我们希望打破限制，加强研究，以支持人类健康。健康护理系统的重要步骤之一是通过佩戴传感器的步态来了解用户的年龄和性别。选择步态是因为它是最主要的日常活动，被认为不仅包含身份，而且还包含身体，医疗条件。为此，我们组织了一场关于使用可穿戴传感器进行性别和年龄预测的挑战性比赛。该评估主要基于已发布的OU-ISIR惯性数据集，该数据集是目前世界上最大的惯性步态数据集 *。
Recently, wearable computing resources, such as smart-phones, are developing fast due to the advancements of technology and their great supports to human life. People are using smartphone for communication, work, entertainment, business, traveling, and browsing information. However, the health-care application is very limited due to many challenges. We would like to break the limitation and boost up the research to support human health. One of the important steps for a health-care system is to understand age and gender of the user through gait, who is wearing the sensor. Gait is chosen because it is the most dominant daily activity, which is considered to contain not only identity but also physical, medical conditions. To this end, we organize a challenging competition on gender and age prediction using wearable sensors. The evaluation is mainly based on the published OU-ISIR inertial dataset which is currently the world largest inertial gait dataset*.