WEEE: A Multi-Device and Multi-Modal Dataset for Wearable Energy Expenditure Estimation

We present a multi-device and multi-modal dataset, called WEEE, collected from 17 participants under different physical activities. The WEEE 1) contains sensor data collected using 7 wearable devices placed on 4 body locations - head, ear, chest, and wrist, 2) respiratory data collected with an indirect calorimeter serving as ground-truth information, 3) demographics and body composition data, 4) activity type, and their corresponding metabolic equivalent of task (MET) values, and intensity level, and 5) answers to questionnaires related to physical activity level, diet, stress and sleep. Thanks to the diversity of sensors and body locations, we envision that this dataset will enable the development of novel human energy expenditure estimation techniques for a diverse set of application scenarios. Energy expenditure (EE) refers to the amount of energy an individual uses to maintain body functions and as a result of physical activity. The ability to estimate EE allows computing systems obtaining valuable insights regarding people's physical activity and promoting a healthier and more active lifestyle.