Human Gait Database for Normal Walk Collected by Smart Phone Accelerometer

Amir Vajdi, Mohammad Reza Zaghian, Saman Farahmand, Elham Rastegar, Kian Maroofi, Shaohua Jia, Marc Pomplun, Nurit Haspel, Akram Bayat

February 18, 2020

The goal of this study is to introduce a comprehensive gait database of 93 human subjects who walked between two endpoints during two different sessions and record their gait data using two smartphones, one was attached to the right thigh and another one on the left side of the waist. This data is collected with the intention to be utilized by a deep learning-based method which requires enough time points. The metadata including age, gender, smoking, daily exercise time, height, and weight of an individual is recorded, and this data set is publicly available: Human_Gait_Data.

Featured Fellows

Akram Bayat

Data Science Health Innovation Fellow