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PLHI-MC10:一个通过三重同步医学认可传感器捕获的运动活动数据集。

PLHI-MC10: A dataset of exercise activities captured through a triple synchronous medically-approved sensor.

作者信息

Mahajan Yohan, Bhimireddy Ananth, Abid Areeba, Gichoya Judy W, Purkayastha Saptarshi

机构信息

Indiana University Purdue University Indianapolis, Indianapolis, IN 46202, USA.

Emory University School of Medicine, 100 Woodruff Circle, Atlanta, GA 30322, USA.

出版信息

Data Brief. 2021 Aug 20;38:107287. doi: 10.1016/j.dib.2021.107287. eCollection 2021 Oct.

DOI:10.1016/j.dib.2021.107287
PMID:34485637
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8397882/
Abstract

Most human activity recognition datasets that are publicly available have data captured by using either smartphones or smartwatches, which are usually placed on the waist or the wrist, respectively. These devices obtain one set of acceleration and angular velocity in the -, -, and -axis from the accelerometer and the gyroscope planted in these devices. The PLHI-MC10 dataset contains data obtained by using 3 BioStamp nPoint® sensors from 7 physically healthy adult test subjects performing different exercise activities. These sensors are the state-of-the-art biomedical sensors manufactured by MC10. Each of the three sensors was attached to the subject externally on three muscles-Extensor Digitorum (Posterior Forearm), Gastrocnemius (Calf), and Pectoralis (Chest)-giving us three sets of 3 axial acceleration, two sets of 3 axial angular velocities, and 1 set of voltage values from the heart. Using three different sensors instead of a single sensor improves precision. It helps distinguish between human activities as it simultaneously captures the movement and contractions of various muscles from separate parts of the human body. Each test subject performed five activities (stairs, jogging, skipping, lifting kettlebell, basketball throws) in a supervised environment. The data is cleaned, filtered, and synced.

摘要

大多数公开可用的人类活动识别数据集的数据是通过智能手机或智能手表采集的,这些设备通常分别佩戴在腰部或手腕上。这些设备从内置的加速度计和陀螺仪获取一组在x、y和z轴上的加速度和角速度数据。PLHI-MC10数据集包含7名身体健康的成年测试对象使用3个BioStamp nPoint®传感器进行不同运动活动时获得的数据。这些传感器是MC10生产的最先进的生物医学传感器。三个传感器分别外部附着在受试者的三块肌肉上,即指伸肌(前臂后部)、腓肠肌(小腿)和胸大肌(胸部),从而为我们提供了三组三维轴向加速度数据、两组三维轴向角速度数据以及一组来自心脏的电压值。使用三个不同的传感器而非单个传感器可提高精度。它有助于区分人类活动,因为它能同时捕捉人体不同部位各种肌肉的运动和收缩情况。每个测试对象在受监督的环境中进行了五项活动(爬楼梯、慢跑、跳绳、举哑铃、投篮)。数据经过了清理、过滤和同步处理。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6478/8397882/fb2791ab90eb/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6478/8397882/fb2791ab90eb/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6478/8397882/fb2791ab90eb/gr1.jpg

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本文引用的文献

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Real-Time Digital Biometric Monitoring during Elite Athletic Competition: System Feasibility with a Wearable Medical-Grade Sensor.精英体育比赛中的实时数字生物特征监测:可穿戴医疗级传感器的系统可行性
Digit Biomark. 2021 Feb 3;5(1):37-43. doi: 10.1159/000513222. eCollection 2021 Jan-Apr.
2
A Pivotal Study to Validate the Performance of a Novel Wearable Sensor and System for Biometric Monitoring in Clinical and Remote Environments.一项验证新型可穿戴传感器及系统在临床和远程环境中进行生物特征监测性能的关键研究。
Digit Biomark. 2019 Mar 1;3(1):1-13. doi: 10.1159/000493642. eCollection 2019 Jan-Apr.