Human energy expenditure (EE) refers to the amount of energy an individual uses to maintain essential body
functions (respiration, circulation, digestion) and as a result of physical activity. EE measurement can
provide valuable insights into people’s health status and help promoting a more healthy and active lifestyle. The cost and practical limitations of gold-standard EE measurement methods, led to the exploration of unobtrusive wearable sensors to estimate EE in
everyday activities. However, the majority of the existing data sets used to develop such methods are not publicly available or are
highly limited in terms of the type and location of sensors, which makes it difficult for the community to build on existing
work and validate new methods for EE modeling.
We present WEEE, a data set collected from 17 participants to enable multimodal modeling of EE with wearable sensors.
WEEE is a rich data set containing five categories of data: 1) sensor data collected using 8 wearable devices placed on 4 body positions – head, ear, chest, and wrist –, 2) respiratory gases data collected with an indirect calorimeter, which serves as ground-truth information, 3) demographics and body composition data measured using Qardio, 4) activity type – and their corresponding metabolic equivalent of task (MET) from compendium of physical activities – and intensity level, and 5) answers to questionnaires related to physical activity level, diet, stress and sleep.
| Device | Position | Sensors |
|---|---|---|
| VO2 Master Analyzer Face Mask | Mouth | Oxygen consumption |
| Fraction of oxygen in expired breath | ||
| Air moved by the lungs | ||
| Volume breathed in a breath | ||
| Breaths per minute | ||
| Humidity | ||
| Temperature | ||
| Pressure | ||
| Nokia Bell Labs Earbuds | Ear | Accelerometer |
| Gyroscope | ||
| Photoplethysmography | ||
| Muse S Headband | Head | Electroencephalography |
| Accelerometer | ||
| Gyroscope | ||
| Zephyr BioHarness 3.0 Chest band | Chest | Electrocardiography |
| Breathing sensor | ||
| Accelerometer | ||
| Posture sensor | ||
| Wahoo Tickr Chest-strap | Chest | Heart rate |
| Breathing sensor | ||
| Empatica E4 Wristband | Wrist | Accelerometer |
| Blood volume pulse | ||
| Electrodermal activity | ||
| Skin temperature | ||
| Apple Watch Series 6 | Wrist | Heart Rate |
| Fitbit Sense Smartwatch | Wrist | Heart Rate |
The structure of the data is as follows:
| [participant_id]/ |
| ━┗ [device_id]/ |
| ━━┗ <data files> |
| Demographics.csv |
| Study_information.csv |
| Questionnaires |
File Demographics.csv contains both demographics and body composition data.
| Data Type | Data | Tool |
|---|---|---|
| Demographics and Body Composition | Age | Qardio Scale |
| Gender | ||
| Height | ||
| Weight | ||
| Fat (%) | ||
| Musle (%) | ||
| Water (%) | ||
| Bone (%) | ||
| BMI | ||
| Activity | Type | Pen-and-paper |
| Intensity Level | ||
| Questionnaires | Fitness | International Fitness Scale (IFIS) and Physical Activity Readiness (PAR-Q) |
| Sleep | Pittsburgh Sleep Quality Index (PSQI) and Stanford Sleepiness Scale (SSS) | |
| Stress | Perceived Stress Scale (PSS) | |
| Diet | How healthy is your diet? |