Apollo Smart Walker Dataset

APOLLO SMART WALKER DATASET Gait monitoring of elderly people who use walkers. This dataset collects data from the accelerometer, gyroscope and magnetometer sensors of the smartphone positioned in the center of a walker. ADL 1 Forward: Starting the walk on the sidewalk, passing through the grass to the end point. Backward: Starting the walk on the grass, going to the sidewalk. ADL 2 Forward: Starting the walk from an internal environment of the house and going to the external environment. Backward: Starting the walk from an external environment of the house and going to the internal environment. ADL 3 Forward: Starting the walk in the living room, going through the hallway and entering the bathroom. Backward: Starting the walk in the bathroom, going through the hallway and entering the living room. See the records of this dataset: ADL 1 https://www.youtube.com/playlist?list=PLRHcq8YHj4-aHt03LLV-tvM9IP90869dU ADL 2 https://www.youtube.com/playlist?list=PLRHcq8YHj4-YaOt1KNg5KhCxcO1wuF_F_ ADL 3 https://www.youtube.com/playlist?list=PLRHcq8YHj4-YEc2PifRcFp0Aw1AJFIuXC Number of samples: 180 Number of Instance: 482031 Data Set Characteristics: Sequential Data, Time Series Data, Multivariate Data, Correlation Area: Elderly Health, Applied Computing Attribute Characteristics: Integer, Double Number of Attributes: 5 The coordinate-system is defined relative to the screen of the phone in its default orientation. The axes are not swapped when the device's screen orientation changes. The X axis is horizontal and points to the right, the Y axis is vertical and points up and the Z axis points towards the outside of the front face of the screen. In this system, coordinates behind the screen have negative Z values. Source: https://developer.android.com/reference/android/hardware/SensorEvent Apollo Smart Walker Collector github repository: https://github.com/hartmannjean/Apollo-Smart-Walker-Collector Relevant Information: 1. The dataset collects data from an Android smartphone which is positioned in the center of the walker; 2. The data sensors collected are accelerometer, gyroscope and magnetometer; 3. The sampling frequency of the sensors is DELAY_FASTEST - 20 milliseconds; 4. Data format: CSV. Dataset information: 1. Dataset was recorded in video; 2. The dataset was recorded in three different scenarios. Each scenario has two turns, going forward and coming back. 3. Each scenario was recorded 20 times. 4. Each recording generated three files: i. Accelerometer; ii. Gyroscope; iii. And magnetometer; 5. Each file contains the following information; i. Timestamp, Id, x axis, y axis, z axis. This dataset is part of this article paper: Hartmann, Jean; Tavares, João (2022). Apollo Smart Walker: A Model Based on IoT and Artificial Intelligence for Monitoring the Gait of Elderly People Using Walkers. Universidade do Vale do Rio dos Sinos.

APOLLO智能助行器数据集（APOLLO SMART WALKER DATASET）：面向使用助行器老年人的步态监测数据集。本数据集采集安装于助行器中央的智能手机的加速度计、陀螺仪与磁力计传感器数据。

ADL 1 正向：从人行道起步行走，途经草坪抵达终点；反向：从草坪起步行走，前往人行道。
ADL 2 正向：从住宅内部环境起步，前往外部环境；反向：从住宅外部环境起步，前往内部环境。
ADL 3 正向：从客厅起步，途经走廊进入浴室；反向：从浴室起步，途经走廊进入客厅。

该数据集的记录详情如下：
ADL 1：https://www.youtube.com/playlist?list=PLRHcq8YHj4-aHt03LLV-tvM9IP90869dU
ADL 2：https://www.youtube.com/playlist?list=PLRHcq8YHj4-YaOt1KNg5KhCxcO1wuF_F_
ADL 3：https://www.youtube.com/playlist?list=PLRHcq8YHj4-YEc2PifRcFp0Aw1AJFIuXC

样本量：180
实例数：482031

数据集特征：序列数据、时间序列数据、多变量数据；关联研究领域：老年健康、应用计算
属性特征：整数型、双精度浮点型；属性数量：5

本坐标系基于手机默认竖屏状态下的屏幕定义，当设备屏幕方向改变时，坐标轴不会发生交换。X轴为水平方向并指向右侧，Y轴为垂直方向并指向上方，Z轴指向屏幕正面外侧。在此坐标系中，屏幕后方的坐标Z值为负。

数据来源：https://developer.android.com/reference/android/hardware/SensorEvent

Apollo智能助行器采集器GitHub仓库：https://github.com/hartmannjean/Apollo-Smart-Walker-Collector

相关说明：
1. 本数据集采集自安装于助行器中央的安卓智能手机；
2. 采集的传感器数据包括加速度计、陀螺仪与磁力计；
3. 传感器采样频率为DELAY_FASTEST——20毫秒；
4. 数据格式：CSV（逗号分隔值）文件。

数据集详细信息：
1. 本数据集附带录制视频；
2. 数据集在三种不同场景下录制，每种场景包含正向行走与折返两个环节；
3. 每种场景录制20次；
4. 每次录制生成三个文件：i. 加速度计数据文件；ii. 陀螺仪数据文件；iii. 磁力计数据文件；
5. 每个文件包含以下信息：i. 时间戳、ID、X轴数据、Y轴数据、Z轴数据。

本数据集隶属于以下学术论文：Hartmann, Jean; Tavares, João (2022). 《Apollo智能助行器（Apollo Smart Walker）：基于物联网（IoT）与人工智能的助行器老年人步态监测模型》，南里奥格兰德河谷大学（Universidade do Vale do Rio dos Sinos）。