Novel human computer interaction principles for cardiac feedback using google glass and Android wear

R. Richer, Tim Maiwald, C. Pasluosta, B. Hensel, B. Eskofier
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引用次数: 13

Abstract

This work presents a system for unobtrusive cardiac feedback in daily life. It addresses the whole pipeline from data acquisition over data processing to data visualization including wearable integration. ECG signals are recorded with a novel ECG sensor supporting Bluetooth Low Energy, which is able to transmit raw ECG data as well as estimated heart rate. ECG signals are processed in real-time on a mobile device to automatically classify the user's heart beats. A novel application for Android-based mobile devices was developed for data visualization. It offers several modes for cardiac feedback, from measuring the current heart rate to continuously monitoring the user's heart status. It also allows to store acquired data in an internal database as well as in the Google Fit platform. Further, the application provides extensions for wearables like Google Glass and smartwatches running on Android Wear. Hardware performance evaluation was performed by comparing the course of heart rate between the novel ECG sensor and a commercial ECG sensor. The mean absolute error between the two sensors was 4.83 bpm with a standard deviation of 4.46 bpm, and a Pearson correlation of 0.922. A qualitative evaluation was performed for the Android application with special emphasis on the daily usability and the wearable integration. When the Google Glass was integrated, the subjects rated the application as 2.8/5 (0 = Bad, 5 = Excellent), whereas when the application was integrated with a smartwatch the rating increased to 4.2/5.
使用谷歌眼镜和Android wear进行心脏反馈的新型人机交互原理
这项工作提出了一个日常生活中不显眼的心脏反馈系统。它解决了从数据采集到数据处理到数据可视化的整个流程,包括可穿戴集成。采用支持低功耗蓝牙的新型心电传感器记录心电信号,该传感器能够传输原始心电数据以及估计的心率。在移动设备上实时处理心电信号,自动对用户的心跳进行分类。开发了一种新的基于android的移动设备的数据可视化应用程序。它提供了几种心脏反馈模式,从测量当前心率到持续监测用户的心脏状态。它还允许将获取的数据存储在内部数据库和Google Fit平台中。此外,该应用程序还为运行在Android Wear上的谷歌眼镜和智能手表等可穿戴设备提供扩展。通过比较新型心电传感器与商用心电传感器的心率变化过程,对其硬件性能进行了评价。两种传感器的平均绝对误差为4.83 bpm,标准差为4.46 bpm, Pearson相关系数为0.922。对Android应用程序进行了定性评估,特别强调日常可用性和可穿戴集成。当集成谷歌眼镜时,受试者对应用程序的评分为2.8/5(0 =差,5 =优秀),而当应用程序与智能手表集成时,评分增加到4.2/5。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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