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2020 – today
- 2023
[j4]Justin Amadeus Albert
, Arne Herdick, Clemens Markus Brahms, Urs Granacher, Bert Arnrich:
PERSIST: A Multimodal Dataset for the Prediction of Perceived Exertion during Resistance Training. Data 8(1): 9 (2023)- 2022
- [c3]Lin Zhou, Eric Fischer, Clemens Markus Brahms, Urs Granacher, Bert Arnrich:
Using Transparent Neural Networks and Wearable Inertial Sensors to Generate Physiologically-Relevant Insights for Gait. ICMLA 2022: 1274-1280 - 2021
- [j3]Justin Trautmann, Lin Zhou, Clemens Markus Brahms, Can Tunca, Cem Ersoy, Urs Granacher, Bert Arnrich:
TRIPOD - A Treadmill Walking Dataset with IMU, Pressure-Distribution and Photoelectric Data for Gait Analysis. Data 6(9): 95 (2021) - [c2]Justin Amadeus Albert, Arne Herdick, Clemens Markus Brahms, Urs Granacher, Bert Arnrich:
Using Machine Learning to Predict Perceived Exertion During Resistance Training With Wearable Heart Rate and Movement Sensors. BIBM 2021: 801-808 - 2020
- [j2]Lin Zhou, Eric Fischer, Can Tunca, Clemens Markus Brahms, Cem Ersoy, Urs Granacher, Bert Arnrich:
How We Found Our IMU: Guidelines to IMU Selection and a Comparison of Seven IMUs for Pervasive Healthcare Applications. Sensors 20(15): 4090 (2020) - [j1]Justin Amadeus Albert, Victor Owolabi, Arnd Gebel, Clemens Markus Brahms, Urs Granacher, Bert Arnrich:
Evaluation of the Pose Tracking Performance of the Azure Kinect and Kinect v2 for Gait Analysis in Comparison with a Gold Standard: A Pilot Study. Sensors 20(18): 5104 (2020) - [c1]Lin Zhou, Can Tunca, Eric Fischer, Clemens Markus Brahms, Cem Ersoy, Urs Granacher, Bert Arnrich:
Validation of an IMU Gait Analysis Algorithm for Gait Monitoring in Daily Life Situations. EMBC 2020: 4229-4232
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