DII-Dipartimento di Ingegneria dell'Informazione, Università Politecnica delle Marche, Via Brecce Bianche 12, 60131, Ancona, Italy.
Biomed Eng Online. 2018 Nov 20;17(Suppl 1):132. doi: 10.1186/s12938-018-0567-4.
The human activity monitoring technology is one of the most important technologies for ambient assisted living, surveillance-based security, sport and fitness activities, healthcare of elderly people. The activity monitoring is performed in two steps: the acquisition of body signals and the classification of activities being performed. This paper presents a low-cost wearable wireless system specifically designed to acquire surface electromyography (sEMG) and accelerometer signals for monitoring the human activity when performing sport and fitness activities, as well as in healthcare applications.
The proposed system consists of several ultralight wireless sensing nodes that are able to acquire, process and efficiently transmit the motion-related (biological and accelerometer) body signals to one or more base stations through a 2.4 GHz radio link using an ad-hoc communication protocol designed on top of the IEEE 802.15.4 physical layer. A user interface software for viewing, recording, and analysing the data was implemented on a control personal computer that is connected through a USB link to the base stations. To demonstrate the capability of the system of detecting the user's activity, data recorded from a few subjects were used to train and test an automatic classifier for recognizing the type of exercise being performed. The system was tested on four different exercises performed by three people, the automatic classifier achieved an overall accuracy of 85.7% combining the features extracted from acceleration and sEMG signals.
A low cost wireless system for the acquisition of sEMG and accelerometer signals has been presented for healthcare and fitness applications. The system consists of wearable sensing nodes that wirelessly transmit the biological and accelerometer signals to one or more base stations. The signals so acquired will be combined and processed in order to detect, monitor and recognize human activities.
人体活动监测技术是安闲辅助生活、基于监控的安全、运动和健身活动、老年人保健中最重要的技术之一。活动监测分为两步进行：获取身体信号和对正在进行的活动进行分类。本文介绍了一种低成本的可穿戴无线系统，专门用于采集表面肌电图（sEMG）和加速度计信号，以监测运动和健身活动以及医疗保健应用中的人体活动。
所提出的系统由几个超轻无线传感节点组成，这些节点能够通过 2.4GHz 无线电链路使用基于 IEEE 802.15.4 物理层的自组织通信协议，将与运动相关的（生物和加速度计）身体信号高效地传输到一个或多个基站。在连接到基站的控制个人计算机上实现了用于查看、记录和分析数据的用户界面软件。为了演示系统检测用户活动的能力，使用从几个对象记录的数据来训练和测试用于识别正在进行的运动类型的自动分类器。该系统在三个人进行的四项不同运动中进行了测试，自动分类器结合从加速度和 sEMG 信号中提取的特征，实现了 85.7%的整体准确性。
提出了一种用于医疗保健和健身应用的低成本无线 sEMG 和加速度计信号采集系统。该系统由可穿戴式传感节点组成，这些节点通过无线方式将生物和加速度计信号传输到一个或多个基站。如此获取的信号将被组合和处理，以检测、监测和识别人体活动。
