Machine Learning and Data Analytics Lab

Optimal Control and Machine Learning in Biomechanics: Hybrid Models for Inertial Sensor-based Gait Analysis and Virtual Footwear Testing (2023) Dorschky E Thesis Mobile digital gait analysis objectively measures progression in hereditary spastic paraplegia (2023) Loris E, Ollenschläger M, Greinwalder T, Eskofier B, Winkler J, Gaßner H, Regensburger M Journal article Listening to the patients' voice: a conceptual framework of the walking experience (2023) Delgado-Ortiz L, Polhemus A, Keogh A, Sutton N, Remmele W, Hansen C, Kluge F, et al. Journal article Breathe your stress away. Preliminary results of a randomized controlled study investigating a breath-based approach-avoidance modification training in individuals with elevated stress (2023) Keinert M, Böhme S, Eskofier B, Schuller BW, Berking M Conference contribution, Conference Contribution Discussion and recommendations from the 2023 ”Gaze Meets ML” workshop breakout session (2023) Karargyris A, Ahmed S, de Belen RA, Banerjee B, Ibrayev T, Kashyap S, Krupinski E, et al. Conference contribution Improving the Robustness of IMU-based Sit-To-Stand Detection during Simulated Real-World Activities for Different Sensor Positions (2023) Seifer AK, Popp F, Richer R, Gaßner H, Eskofier B Conference contribution, Conference Contribution Efficacy of a smartphone-based reappraisal training against depression and benefits of enhancing it with facial expression (2023) Rupp L, Capito K, Gmelch LM, Böhme S, Richer R, Sadeghi M, Rahimi F, et al. Conference contribution, Abstract of lecture Stroop, Stress, and VR: Developing the Virtual Reality Stroop Room (2023) Ringgold V, Mehringer W, Eskofier B, Rohleder N Conference contribution, Conference Contribution WebPPG: Feasibility and Usability of Self-Performed, Browser-Based Smartphone Photoplethysmography (2023) Nissen M, Flaucher M, Jäger K, Hübner H, Danzberger N, Titzmann A, Pontones C, et al. Conference contribution Fetal Re-Identification in Multiple Pregnancy Ultrasound Images Using Deep Learning (2023) Gabler E, Nissen M, Altstidl T, Titzmann A, Packhäuser K, Maier A, Fasching P, et al. Conference contribution, Conference Contribution