# HuGaDB: Human Gait Database for Activity Recognition from Wearable Inertial Sensor Networks

## TL;DR

HuGaDB is a comprehensive, freely available human gait dataset collected from wearable sensors, designed for activity recognition, health studies, virtual reality, and robotics, offering detailed gait analysis data.

## Contribution

This paper introduces the first detailed human gait database from wearable sensors, enabling diverse applications in health, VR, and robotics.

## Key findings

- Dataset includes continuous recordings of various activities.
- Sensors capture detailed leg movement and muscle activity.
- Data supports multiple research and application domains.

## Abstract

This paper presents a human gait data collection for analysis and activity recognition consisting of continues recordings of combined activities, such as walking, running, taking stairs up and down, sitting down, and so on; and the data recorded are segmented and annotated. Data were collected from a body sensor network consisting of six wearable inertial sensors (accelerometer and gyroscope) located on the right and left thighs, shins, and feet. Additionally, two electromyography sensors were used on the quadriceps (front thigh) to measure muscle activity. This database can be used not only for activity recognition but also for studying how activities are performed and how the parts of the legs move relative to each other. Therefore, the data can be used (a) to perform health-care-related studies, such as in walking rehabilitation or Parkinson's disease recognition, (b) in virtual reality and gaming for simulating humanoid motion, or (c) for humanoid robotics to model humanoid walking. This dataset is the first of its kind which provides data about human gait in great detail. The database is available free of charge https://github.com/romanchereshnev/HuGaDB.