Lower Limb Movement during 10-Meter Walk Test: A Dataset with Inertial, Magnetic, and Temperature Sensors.

IF 6.9 2区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES
Maykol Santos, Andrés Caro Lindo, Carlos Albuquerque, Paulo Jorge Coelho, Ivan Miguel Pires
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Abstract

This paper presents a dataset from a study analyzing lower limb movement during a 10-meter walk test. The study utilized SensorTileBox sensors integrated into shin pads to capture detailed movement and environmental data from participants. The sensors recorded 3D accelerometer data (in milligravities), 3D gyroscope data (degrees per second), magnetometer readings (milligauss), and temperature (°C). The dataset was collected through a custom-made application that initiated the sensor readings while the patient performed the walk test. Alongside sensor data, additional demographic and health information, including age, gender, physical exercise habits, diet, and health conditions, were collected via a form stored in a YML file. This information provides context for the sensor measurements and allows for comprehensive analysis. All sensor measurements are time-stamped and stored in CSV format, with participant-specific data anonymized and organized in folders by numeric identifiers. This dataset offers a valuable resource for studying movement patterns in relation to physiological and lifestyle factors, particularly for elderly individuals. It could support research in biomechanics, rehabilitation, and sensor-based health monitoring.

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10米行走测试中的下肢运动:包含惯性、磁性和温度传感器的数据集。
本文介绍了一项研究的数据集,该研究分析了10米步行测试期间的下肢运动。该研究利用集成在胫骨衬垫中的SensorTileBox传感器来捕捉参与者的详细运动和环境数据。传感器记录3D加速度计数据(单位为毫克)、3D陀螺仪数据(每秒度)、磁力计读数(毫克)和温度(°C)。数据集是通过定制的应用程序收集的,该应用程序在患者进行步行测试时启动传感器读数。除了传感器数据外,还通过存储在YML文件中的表格收集了其他人口统计和健康信息,包括年龄、性别、体育锻炼习惯、饮食和健康状况。该信息为传感器测量提供了上下文,并允许进行全面分析。所有传感器测量都有时间戳,并以CSV格式存储,参与者特定的数据匿名化,并按数字标识符组织在文件夹中。该数据集为研究与生理和生活方式因素相关的运动模式提供了宝贵的资源,特别是对于老年人。它可以支持生物力学、康复和基于传感器的健康监测方面的研究。
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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来源期刊
Scientific Data
Scientific Data Social Sciences-Education
CiteScore
11.20
自引率
4.10%
发文量
689
审稿时长
16 weeks
期刊介绍: Scientific Data is an open-access journal focused on data, publishing descriptions of research datasets and articles on data sharing across natural sciences, medicine, engineering, and social sciences. Its goal is to enhance the sharing and reuse of scientific data, encourage broader data sharing, and acknowledge those who share their data. The journal primarily publishes Data Descriptors, which offer detailed descriptions of research datasets, including data collection methods and technical analyses validating data quality. These descriptors aim to facilitate data reuse rather than testing hypotheses or presenting new interpretations, methods, or in-depth analyses.
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