Earable & IoT Sample Dataset from the publication--ERICA: Enabling Real-time Mistake Detection & Corrective Feedback for Free-Weights Exercises
We appreciate you citing our work if you use the dataset:
Meera Radhakrishnan, Darshana Rathnayake, Koon Han Ong, Inseok Hwang, and Archan Misra. Erica: Enabling real-time mistake detection & corrective feedback for free-weights exercises. In Proceedings of the 18th Conference on Embedded Networked Sensor Systems (ACM SenSys 2020). DOI: https://doi.org/10.1145/3384419.3430732
Summary:
Wearable or infrastructure sensors have been widely proposed for automated tracking and analysis of individual-level exercise activities. This dataset is collected as part of building a pervasive, low-cost digital personal trainer system, that supports fine-grained tracking of an individual’s free-weights exercises via a combination of (a) sensors on personal wireless ear-worn devices (‘earables’) and (b) inexpensive IoT sensors attached to exercise equipment (e.g., dumbbells). This sample dataset is comprised of sensor signals acquired from two 6-axis IMUs and contains data for 3 different free-weight exercises performed by 15 individuals.