Kirk, C., Küderle, A., Micó-Amigo, M. E., Bonci, T., Paraschiv-Ionescu, A., Ullrich, M., Soltani, A., Gazit, E., Salis, F., Alcock, L., Aminian, K., Becker, C., Bertuletti, S., Brown, P., Buckley, E., Cantu, A., Carsin, A.-E., Caruso, M., Caulfield, B., … Van Gelder, L. (2024). Mobilise-D insights to estimate real-world walking speed in multiple conditions with a wearable device. Scientific Reports, 14(1), 1754. https://doi.org/10.1038/s41598-024-51766-5
Tag: MobiliseD
Mobilizing patient and public involvement in the development of real-world digital technology solutions: Tutorial
Keogh, A., Mc Ardle, R., Diaconu, M. G., Ammour, N., Arnera, V., Balzani, F., Brittain, G., Buckley, E., Buttery, S., Cantu, A., Corriol-Rohou, S., Delgado-Ortiz, L., Duysens, J., Forman-Hardy, T., Gur-Arieh, T., Hamerlijnck, D., Linnell, J., Leocani, L., McQuillan, T., … Mobilise-D consortium. (2023). Mobilizing patient and public involvement in the development of real-world digital technology solutions: Tutorial. Journal of Medical Internet Research, 25, e44206. https://doi.org/10.2196/44206
Estimating real-world walking speed from a single wearable device: Analytical pipeline, results and lessons learnt from the Mobilise-D technical validation study
Kirk, C., Kuederle, A., Mico-Amigo, M. E., Bonci, T., Paraschiv-Ionescu, A., Ullrich, M., Soltani, A., Gazit, E., Salis, F., Alcock, L., Aminian, K., Becker, C., Bertuletti, S., Brown, P., Buckley, E., Cantu, A., Carsin, A.-E., Caruso, M., Caulfield, B., … Din, S. D. (2023). Estimating real-world walking speed from a single wearable device: Analytical pipeline, results and lessons learnt from the Mobilise-D technical validation study. https://doi.org/10.21203/rs.3.rs-2965670/v1
Ecological validity of a deep learning algorithm to detect gait events from real-life walking bouts in mobility-limiting diseases
Romijnders, R., Salis, F., Hansen, C., Küderle, A., Paraschiv-Ionescu, A., Cereatti, A., Alcock, L., Aminian, K., Becker, C., Bertuletti, S., Bonci, T., Brown, P., Buckley, E., Cantu, A., Carsin, A.-E., Caruso, M., Caulfield, B., Chiari, L., D’Ascanio, I., … Maetzler, W. (2023). Ecological validity of a deep learning algorithm to detect gait events from real-life walking bouts in mobility-limiting diseases. Frontiers in Neurology, 14, 1247532. https://doi.org/10.3389/fneur.2023.1247532
Parallel Assemblies Plot, a visualization tool to explore categorical and quantitative data: Application to digital mobility outcomes
Cantu, A., Micó-Amigo, M. E., Del Din, S., & Fernstad, S. J. (2023). Parallel Assemblies Plot, a visualization tool to explore categorical and quantitative data: Application to digital mobility outcomes. 2023 IEEE 16th Pacific Visualization Symposium (PacificVis), 21–30. https://doi.org/10.1109/PacificVis56936.2023.00010
Assessing real-world gait with digital technology? Validation, insights and recommendations from the Mobilise-D consortium
Micó-Amigo, M. E., Bonci, T., Paraschiv-Ionescu, A., Ullrich, M., Kirk, C., Soltani, A., Küderle, A., Gazit, E., Salis, F., Alcock, L., Aminian, K., Becker, C., Bertuletti, S., Brown, P., Buckley, E., Cantu, A., Carsin, A.-E., Caruso, M., Caulfield, B., … for the Mobilise-D consortium. (2023). Assessing real-world gait with digital technology? Validation, insights and recommendations from the Mobilise-D consortium. Journal of NeuroEngineering and Rehabilitation, 20(1), 78. https://doi.org/10.1186/s12984-023-01198-5