TY  - JOUR
A1  - Chromik, Jonas
A1  - Kirsten, Kristina
A1  - Herdick, Arne
A1  - Kappattanavar, Arpita Mallikarjuna
A1  - Arnrich, Bert
T1  - SensorHub
T2  - Sensors
N2  - Observational studies are an important tool for determining whether the findings from controlled experiments can be transferred into scenarios that are closer to subjects' real-life circumstances. A rigorous approach to observational studies involves collecting data from different sensors to comprehensively capture the situation of the subject. However, this leads to technical difficulties especially if the sensors are from different manufacturers, as multiple data collection tools have to run simultaneously. We present SensorHub, a system that can collect data from various wearable devices from different manufacturers, such as inertial measurement units, portable electrocardiographs, portable electroencephalographs, portable photoplethysmographs, and sensors for electrodermal activity. Additionally, our tool offers the possibility to include ecological momentary assessments (EMAs) in studies. Hence, SensorHub enables multimodal sensor data collection under real-world conditions and allows direct user feedback to be collected through questionnaires, enabling studies at home. In a first study with 11 participants, we successfully used SensorHub to record multiple signals with different devices and collected additional information with the help of EMAs. In addition, we evaluated SensorHub's technical capabilities in several trials with up to 21 participants recording simultaneously using multiple sensors with sampling frequencies as high as 1000 Hz. We could show that although there is a theoretical limitation to the transmissible data rate, in practice this limitation is not an issue and data loss is rare. We conclude that with modern communication protocols and with the increasingly powerful smartphones and wearables, a system like our SensorHub establishes an interoperability framework to adequately combine consumer-grade sensing hardware which enables observational studies in real life.
KW  - multimodal sensing
KW  - home-based studies
KW  - activity recognition
KW  - sensor
KW  - systems
KW  - ecological momentary assessment
KW  - digital health
Y1  - 2022
UR  - https://publishup.uni-potsdam.de/frontdoor/index/index/docId/57638
SN  - 1424-8220
VL  - 22
IS  - 1
PB  - MDPI
CY  - Basel
ER  -