DiFronzo/Human_Activity_Recognition

Human Activity Recognition (HAR) using smartphones dataset. Classifying the type of movement amongst five categories:
- WALKING,
- WALKING_UPSTAIRS,
- WALKING_DOWNSTAIRS,
- SITTING,
- STANDING

The experiments have been carried out with a group of 16 volunteers within an age bracket of 19-26 years. Each person performed five activities (WALKING, WALKING_UPSTAIRS, WALKING_DOWNSTAIRS, SITTING, STANDING) wearing a smartphone (Samsung Galaxy S8) in the pucket. Using its embedded accelerometer and gyroscope, we captured 3-axial linear acceleration and 3-axial angular velocity at a constant rate of 50Hz. The experiments have been video-recorded to label the data manually.

```bash
'raw_data/labels.txt': include all the activity labels available for the dataset (1 per row).
Column 1: experiment number ID,
Column 2: user number ID,
Column 3: activity number ID
Column 4: Label start point (in number of signal log samples (recorded at 50Hz))
Column 5: Label end point (in number of signal log samples)

activity_type:
1 WALKING
2 WALKING_UPSTAIRS
3 WALKING_DOWNSTAIRS
4 SITTING
5 STANDING
```
Repository: [DiFronzo/LSTM-for-Human-Activity-Recognition-classification](https://github.com/DiFronzo/LSTM-for-Human-Activity-Recognition-classification)

This dataset is a human activity recognition (HAR) dataset collected using smartphones, covering five activity types: walking, walking upstairs, walking downstairs, sitting, and standing. The experiments were conducted by 16 volunteers aged between 19 and 26 years old, who wore Samsung Galaxy S8 smartphones and utilized their built-in accelerometer and gyroscope to capture 3-axis linear acceleration and 3-axis angular velocity at a sampling frequency of 50 Hz. The data was manually annotated via video recordings. The file raw_data/labels.txt contains all available activity labels in the dataset, with one label per line. The columns include experiment ID, user ID, activity ID, label start point, and label end point.

原始信息汇总

数据集概述

数据集名称

Human Activity Recognition (HAR) using smartphones dataset

数据集内容

• 活动分类：数据集包含五种活动类型，分别是：

  • WALKING
  • WALKING_UPSTAIRS
  • WALKING_DOWNSTAIRS
  • SITTING
  • STANDING

• 实验对象：16名年龄在19至26岁之间的志愿者。

• 设备：志愿者佩戴的智能手机为Samsung Galaxy S8，使用其内置的加速度计和陀螺仪进行数据采集。

• 数据采集频率：数据以50Hz的频率记录。

• 数据文件：

  • raw_data/labels.txt：包含所有活动标签，每行一个标签，具体信息如下：
    • 列1：实验编号ID
    • 列2：用户编号ID
    • 列3：活动编号ID
    • 列4：标签开始点（信号日志样本数）
    • 列5：标签结束点（信号日志样本数）

活动类型编码

• 1: WALKING
• 2: WALKING_UPSTAIRS
• 3: WALKING_DOWNSTAIRS
• 4: SITTING
• 5: STANDING