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Earable & IoT Dataset from: ERICA - Enabling real-time mistake detection & corrective feedback for free-weights exercises
datasetposted on 23.10.2020, 06:05 by Meeralakshmi RADHAKRISHNAN, Ramesh Darshana Rathnayake KANATTA GAMAGE, ONG KOON HAN (SMU), Inseok Hwang, Archan MISRA
Wearables 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). The dataset is comprised of sensor signals acquired from two 6-axis IMUs and contains a total of 324 samples for 3 different free-weight exercises performed by 27 individuals.