Biomedical Engineering Section, University of Reading, RG6 6DH, Reading, UK.
Sci Data. 2023 Oct 17;10(1):709. doi: 10.1038/s41597-023-02567-4.
Embedding sensors into clothing is promising as a way for people to wear multiple sensors easily, for applications such as long-term activity monitoring. To our knowledge, this is the first published dataset collected from sensors in loose clothing. 6 Inertial Measurement Units (IMUs) were configured as a 'sensor string' and attached to casual trousers such that there were three sensors on each leg near the waist, thigh, and ankle/lower-shank. Participants also wore an Actigraph accelerometer on their dominant wrist. The dataset consists of 15 participant-days worth of data collected from 5 healthy adults (age range: 28-48 years, 3 males and 2 females). Each participant wore the clothes with sensors for between 1 and 4 days for 5-8 hours per day. Each day, data were collected while participants completed a fixed circuit of activities (with a video ground truth) as well as during free day-to-day activities (with a diary). This dataset can be used to analyse human movements, transitional movements, and postural changes based on a range of features.
将传感器嵌入衣物中是一种很有前途的方法，可以让人们轻松地佩戴多个传感器，适用于长期活动监测等应用。据我们所知，这是第一个从宽松衣物中的传感器收集的公开数据集。6 个惯性测量单元（IMU）被配置为一个“传感器串”，并附着在休闲裤上，使得每条腿在腰部、大腿和脚踝/小腿附近都有三个传感器。参与者还在优势手腕上佩戴了一个 Actigraph 加速度计。该数据集包含来自 5 名健康成年人（年龄范围：28-48 岁，3 名男性和 2 名女性）的 15 天数据。每位参与者穿着带有传感器的衣服，每天佩戴 1 到 4 天，每天佩戴 5-8 小时。每天，参与者在完成一系列固定活动（有视频地面实况）以及日常自由活动（有日记）时，都会收集数据。该数据集可用于基于多种特征分析人体运动、过渡运动和姿势变化。
