ActivityAware:护身符腕带设备上的实时日常活动水平监测应用程序。

George Boateng, John A Batsis, Ryan Halter, David Kotz
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引用次数: 21

摘要

体育活动有助于降低患心血管疾病、高血压和肥胖的风险。监测一个人日常活动水平的能力可以为身体活动的自我管理和相关干预提供信息。对于患有肥胖症的老年人来说,定期进行体育锻炼对于降低长期残疾的风险至关重要。在这项工作中,我们提出了ActivityAware,这是一个在护身符腕带设备上的应用程序,可以连续实时地测量个人的日常活动水平(久坐,中等和剧烈)。该应用程序实现了一个活动级别检测模型,持续收集Amulet上的加速数据,对当前的活动级别进行分类,更新当天在该活动级别上花费的累积时间,记录数据以供以后分析,并在屏幕上显示结果。我们开发了一个使用支持向量机(SVM)的活动级检测模型。我们使用来自用户研究的数据来训练我们的分类器,其中受试者进行以下身体活动:坐、站、躺、走和跑。通过10倍交叉验证和留一受试者(LOSO)交叉验证,我们获得了n=14受试者的初步结果,表明准确率高达98%。对ActivityAware应用程序的测试显示,在需要充电之前,预计电池寿命可达4周。结果很有希望,表明该应用程序可能用于活动水平监测,并最终用于开发可以改善个人健康的干预措施。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

<i>ActivityAware</i>: An App for Real-Time Daily Activity Level Monitoring on the Amulet Wrist-Worn Device.

<i>ActivityAware</i>: An App for Real-Time Daily Activity Level Monitoring on the Amulet Wrist-Worn Device.

<i>ActivityAware</i>: An App for Real-Time Daily Activity Level Monitoring on the Amulet Wrist-Worn Device.

ActivityAware: An App for Real-Time Daily Activity Level Monitoring on the Amulet Wrist-Worn Device.
Physical activity helps reduce the risk of cardiovascular disease, hypertension and obesity. The ability to monitor a person's daily activity level can inform self-management of physical activity and related interventions. For older adults with obesity, the importance of regular, physical activity is critical to reduce the risk of long-term disability. In this work, we present ActivityAware, an application on the Amulet wrist-worn device that measures daily activity levels (sedentary, moderate and vigorous) of individuals, continuously and in real-time. The app implements an activity-level detection model, continuously collects acceleration data on the Amulet, classifies the current activity level, updates the day's accumulated time spent at that activity level, logs the data for later analysis, and displays the results on the screen. We developed an activity-level detection model using a Support Vector Machine (SVM). We trained our classifiers using data from a user study, where subjects performed the following physical activities: sit, stand, lay down, walk and run. With 10-fold cross validation and leave-one-subject-out (LOSO) cross validation, we obtained preliminary results that suggest accuracies up to 98%, for n=14 subjects. Testing the ActivityAware app revealed a projected battery life of up to 4 weeks before needing to recharge. The results are promising, indicating that the app may be used for activity-level monitoring, and eventually for the development of interventions that could improve the health of individuals.
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