Access Mobilise-D Research Data on GitHub and Zenodo

Comprehensive quantitative and qualitative data from our studies, including the cross-sectional technical validation study (TVS, 2020-2022) and the longitudinal clinical validation study (CVS, 2021-2024), are available on GitHub and Zenodo. These datasets, along with associated algorithms and code, have undergone rigorous quality assurance and are shared in accordance with data privacy laws and participant rights. Researchers can access these resources for their work, with future data releases to be announced. Visit our GitHub and Zenodo pages for more information and to explore the available data.

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2024

  • Delgado-Ortiz L, Ranciati S, Arbillaga-Etxarri A, Balcells E, Buekers J, Demeyer H, et al. Real-world walking cadence in people with COPD. ERJ Open Research. 2024;10(2):00673-2023.DOI: 10.1183/23120541.00673-2023
  • Kirk C, Küderle A, Micó-Amigo ME, Bonci T, Paraschiv-Ionescu A, Ullrich M, et al. Mobilise-D insights to estimate real-world walking speed in multiple conditions with a wearable device. Sci Rep. 2024;14(1):1754.DOI: 10.1038/s41598-024-51766-5
  • Kluge F, Brand YE, Micó-Amigo ME, Bertuletti S, D’Ascanio I, Gazit E, et al. Real-World Gait Detection Using a Wrist-Worn Inertial Sensor: Validation Study. JMIR Form Res. 2024;8:e50035.DOI: 10.2196/50035

2023

  • Abdullahi IY, Raab R, Küderle A, Eskofier B. Aligning Federated Learning with Existing Trust Structures in Health Care Systems. Int J Environ Res Public Health. 2023;20(7). DOI: 10.3390/ijerph20075378
  • Brem AK, Kuruppu S, de Boer C, Muurling M, Diaz-Ponce A, Gove D … Aarsland D. Digital endpoints in clinical trials of Alzheimer’s disease and other neurodegenerative diseases: challenges and opportunities. Frontiers in Neurology. 2023;14.DOI: 10.3389/fneur.2023.1210974
  • Buekers J, Megaritis D, Koch S, Alcock L, Ammour N, Becker C … Garcia-Aymerich J. Laboratory and free-living gait performance in adults with COPD and healthy controls. ERJ Open Research. 2023 Aug 17.DOI: 10.1183/23120541.00159-2023
  • Buttery SC, Williams PJ, Alghamdi SM, Philip KEJ, Perkins A, Kallis C … Hopkins NS. Investigating the prognostic value of digital mobility outcomes in patients with chronic obstructive pulmonary disease: a systematic literature review and meta-analysis. European Respiratory Review. 2023 Nov 22; 32(170).DOI: 10.1183/16000617.0134-2023
  • Cantu A, Micó-Amigo ME, Del Din S, Fernstad SJ. Parallel Assemblies Plot, a visualization tool to explore categorical and quantitative data: application to digital mobility outcomes. In: 2023 IEEE 16th Pacific Visualization Symposium (PacificVis). 2023. p. 21–30.DOI: 10.5281/zenodo.8095058
  • Clay I, Peerenboom N, Connors DE, Bourke S, Keogh A, Wac K … Hoffmann SC. Reverse engineering of digital measures: Inviting patients to the conversation. Digital Biomarkers. 2023 May 12;7(1):28–44.DOI: 10.1159/000530413
  • Cohen M, Herman T, Ganz N, Badichi I, Gurevich T, Hausdorff JM. Multidisciplinary intensive rehabilitation program for people with Parkinson’s disease: Gaps between the clinic and real-world mobility. International Journal of Environmental Research and Public Health. 2023 Jan;20(5):3806.DOI: 10.3390/ijerph20053806
  • da Rosa Tavares JE, Ullrich M, Roth N, Kluge F, Eskofier BM, Gaßner H … Barbosa JLV. uTUG: An unsupervised Timed Up and Go test for Parkinson’s disease. Biomedical Signal Processing and Control. 2023 Mar 1;81:104394.DOI: 10.1016/j.bspc.2022.104394
  • Davico G, Bottin F, Di Martino A, Castafaro V, Baruffaldi F, Faldini C, Viceconti M. Intra-operator repeatability of manual segmentations of the hip muscles on clinical magnetic resonance images. Journal of Digital Imaging. 2023 Feb 1;36(1):143–52.DOI: 10.1007/s10278-022-00700-0
  • Debelle H, Packer E, Beales E, Bailey HGB, Mc Ardle R, Brown P … Del Din S. Feasibility and usability of a digital health technology system to monitor mobility and assess medication adherence in mild-to-moderate Parkinson’s disease. Frontiers in Neurology. 2023;14.DOI: 10.3389/fneur.2023.1111260
  • Delgado-Ortiz L, Polhemus A, Keogh A, Sutton N, Remmele W, Hansen C … Garcia-Aymerich J. Listening to the patients’ voice: a conceptual framework of the walking experience. Age and Ageing. 2023 Jan 1;52(1):afac233.DOI: 10.1093/ageing/afac233
  • Keogh A, Alcock L, Brown P, Buckley E, Brozgol M, Gazit E … Caulfield B. Acceptability of wearable devices for measuring mobility remotely: Observations from the Mobilise-D technical validation study. DIGITAL HEALTH. 2023 Feb 1;9.DOI: 10.1177/20552076221150745
  • Keogh A, Ardle RM, Diaconu MG, Ammour N, Arnera V, Balzani F … Rochester L. Mobilizing Patient and Public Involvement in the Development of Real-World Digital Technology Solutions: Tutorial. Journal of Medical Internet Research. 2023 Oct 27;25(1):e44206.DOI: 10.2196/44206
  • Kirk C, Zia Ur Rehman R, Galna B, Alcock L, Ranciati S, Palmerini L … Yarnall AJ. Can Digital Mobility Assessment Enhance the Clinical Assessment of Disease Severity in Parkinson’s Disease? Journal of Parkinson’s Disease. 2023 Jan 1; 1–11.DOI: 10.3233/JPD-230044
  • Küderle A, Richer R, Sîmpetru RC, Eskofier BM. tpcp: Tiny Pipelines for Complex Problems – A set of framework independent helpers for algorithms development and evaluation. Journal of Open Source Software. 2023;8(82). DOI: 10.21105/joss.04953
  • Megaritis D, Hume E, Chynkiamis N, Buckley C, Polhemus AM, Watz H … Vogiatzis I. Effects of pharmacological and non-pharmacological interventions on physical activity outcomes in COPD: a systematic review and meta-analysis. ERJ Open Research. 2023 Sep 7.DOI: 10.1183/23120541.00409-2023
  • Micó-Amigo ME, Bonci T, Paraschiv-Ionescu A, Ullrich M, Kirk C, Soltani A … Fernstad S. Assessing real-world gait with digital technology? Validation, insights and recommendations from the Mobilise-D consortium. Journal of NeuroEngineering and Rehabilitation. 2023 Jun 14;20(1):78.DOI: 10.1186/s12984-023-01198-5
  • Packer E, Debelle H, Bailey HGB, Ciravegna F, Ireson N, Evers J … Del Din S. Translating digital healthcare to enhance clinical management: a protocol for an observational study using a digital health technology system to monitor medication adherence and its effect on mobility in people with Parkinson’s. BMJ Open. 2023 Sep 1;13(9).DOI: 10.1136/bmjopen-2023-073388
  • Palmerini L, Reggi L, Bonci T, Del Din S, Micó-Amigo ME, Salis F … Chiari L. Mobility recorded by wearable devices and gold standards: the Mobilise-D procedure for data standardization. Scientific Data. 2023 Jan 19;10(1):38.DOI: 10.1038/s41597-023-01930-9
  • Romijnders R, Salis F, Hansen C, Küderle A, Paraschiv-Ionescu A, Cereatti A, et al. Ecological validity of a deep learning algorithm to detect gait events from real-life walking bouts in mobility-limiting diseases. Front Neurol. 2023;14. DOI: 10.3389/fneur.2023.1247532
  • Salis F, Bertuletti S, Bonci T, Caruso M, Scott K, Alcock L … Cereatti A. A multi-sensor wearable system for the assessment of diseased gait in real-world conditions. Frontiers in Bioengineering and Biotechnology. 2023;11.DOI: 10.3389/fbioe.2023.1143248
  • Seifer A-K, Dorschky E, Küderle A, Moradi H, Hannemann R, Eskofier BM. EarGait: Estimation of Temporal Gait Parameters from Hearing Aid Integrated Inertial Sensors. Sensors. 2023; 23(14). DOI: 10.3390/s23146565
  • Taraldsen K, Polhemus A, Engdal M, Jansen CP, Becker C, Brenner N … Vereijken B. Evaluation of mobility recovery after hip fracture: a scoping review of randomized controlled studies. Osteoporosis International. 2023 Oct 6.DOI: 10.1007/s00198-023-06922-4
  • Ullrich M, Roth N, Küderle A, Richer R, Gladow T, Gaßner H … Kluge F. Fall risk prediction in Parkinson’s disease using real-world inertial sensor gait data. IEEE Journal of Biomedical and Health Informatics. 2023 Jan;27(1):319–28.DOI: 10.1109/JBHI.2022.3215921
  • van Gelder LMA, Bonci T, Buckley EE, Price K, Salis F, Hadjivassiliou M, et al. A Single-Sensor Approach to Quantify Gait in Patients with Hereditary Spastic Paraplegia. Sensors. 2023;23(14):6563. DOI: 10.3390/s23146563
  • Quinn G. IMI Mobilise-D: The Next Generation of Mobility Research. 50 International Pharmaceutical Industry. 2023;15(3).DOI: 10.5281/zenodo.12684333
  • Zahn A, Koch V, Schreff L, Oschmann P, Winkler J, Gaßner H, et al. Validity of an inertial sensor-based system for the assessment of spatio-temporal parameters in people with multiple sclerosis. Front Neurol. 2023;14:1164001. DOI: 10.3389/fneur.2023.1164001

2022

  • Bonci T, Salis F, Scott K, Alcock L, Becker C, Bertuletti S … Mazzà C. An algorithm for accurate marker-based gait event detection in healthy and pathological populations during complex motor tasks. Frontiers in Bioengineering and Biotechnology. 2022;10.DOI: 10.3389/fbioe.2022.868928
  • Brand YE, Schwartz D, Gazit E, Buchman AS, Gilad-Bachrach R, Hausdorff JM. Gait detection from a wrist-worn sensor using machine learning methods: A daily living study in older adults and people with Parkinson’s disease. Sensors. 2022 Jan;22(18):7094.DOI: 10.3390/s22187094
  • Davico G, Lloyd DG, Carty CP, Killen BA, Devaprakash D, Pizzolato C. Multi-level personalization of neuromusculoskeletal models to estimate physiologically plausible knee joint contact forces in children. Biomechanics and Modeling in Mechanobiology. 2022 Dec 1;21(6):1873–86.DOI: 10.1007/s10237-022-01626-w
  • Gaßner H, Trutt E, Seifferth S, Friedrich J, Zucker D, Salhani Z … Jost WH. Treadmill training and physiotherapy similarly improve dual task gait performance: a randomized-controlled trial in Parkinson’s disease. Journal of Neural Transmission. 2022 Sep 1;129(9):1189–1200.DOI: 10.1007/s00702-022-02514-4
  • Gaßner H, Friedrich J, Masuch A, Jukic J, Stallforth S, Regensburger M … Klucken J. The effects of an individualized smartphone-based exercise program on self-defined motor tasks in Parkinson disease: Pilot interventional study. JMIR Rehabilitation and Assistive Technologies. 2022 Nov 15;9(4):e38994.DOI: 10.2196/38994
  • Ibrahim AA, Flachenecker F, Gaßner H, Rothhammer V, Klucken J, Eskofier BM, et al. Short inertial sensor-based gait tests reflect perceived state fatigue in multiple sclerosis. Mult Scler Relat Disord. 2022;58:103519. DOI: 10.1016/j.msard.2022.103519
  • Jaeger SU, Wohlrab M, Schoene D, Tremmel R, Chambers M, Leocani L … Becker C. Mobility endpoints in marketing authorisation of drugs: what gets the European medicines agency moving? Age and Ageing. 2022 Jan 1;51(1):afab242.DOI: 10.1093/ageing/afab242
  • Marcianò V, Bertuletti S, Bonci T, Mazzà C, Ireson N, Ciravegna F … Cereatti A. A deep learning model to discern indoor from outdoor environments based on data recorded by a tri-axial digital magnetic sensor. Gait & Posture. 2022 Oct 1;97:5.DOI: 10.1016/j.gaitpost.2022.09.015
  • Megaritis D, Hume E, Chynkiamis N, Buckley C, Polhemus AM, Watz H … Vogiatzis I. P171 Effects of pharmacological and non-pharmacological interventions on physical activity outcomes in chronic respiratory diseases: a systematic review and meta-analysis. Thorax. 2022 Nov 1;77(Suppl 1):A174–A174.DOI: 10.1136/thorax-2022-btsabstracts.305
  • Mikolaizak AS, Rochester L, Maetzler W, Sharrack B, Demeyer H, Mazzà C … Jansen CP. Connecting real-world digital mobility assessment to clinical outcomes for regulatory and clinical endorsement–the Mobilise-D study protocol. PLoS ONE. 2022 Oct 6;17(10):e0269615.DOI: 10.1371/journal.pone.0269615
  • Ollenschläger M, Küderle A, Mehringer W, Seifer AK, Winkler J, Gaßner H … Eskofier BM. MaD GUI: An open-source python package for annotation and analysis of time-series data. Sensors. 2022 Jan;22(15):5849.DOI: 10.3390/s22155849
  • Reggi L, Palmerini L, Chiari L, Mellone S. Real-world walking speed assessment using a mass-market RTK-GNSS receiver. Frontiers in Bioengineering and Biotechnology. 2022;10.DOI: 10.3389/fbioe.2022.873202
  • Rehman RZU, Guan Y, Shi JQ, Alcock L, Yarnall AJ, Rochester L, Del Din S. Investigating the impact of environment and data aggregation by walking bout duration on Parkinson’s disease classification using machine learning. Frontiers in Aging Neuroscience. 2022;14.DOI: 10.3389/fnagi.2022.808518
  • Roth N, Ullrich M, Küderle A, Gladow T, Marxreiter F, Gassner H … Eskofier BM. Real-world stair ambulation characteristics differ between prospective fallers and non-fallers in Parkinson’s disease. IEEE Journal of Biomedical and Health Informatics. 2022 Sep;26(9):4733–42.DOI: 10.1109/JBHI.2022.3186766
  • Salis F, Bonci T, Bertuletti S, Caruso M, Scott K, Buckley E … Cereatti A. Performance of a multi-sensor wearable system for validating gait assessment: preliminary results on patients and healthy. Gait & Posture. 2022 Oct 1;97:13.DOI: 10.1016/j.gaitpost.2022.09.027
  • Salomon A, Galperin I, Buzaglo D, Mirelman A, Regev K, Karni A … Hausdorff JM. Fragmentation, circadian amplitude, and fractal pattern of daily-living physical activity in people with multiple sclerosis: Is there relevant information beyond the total amount of physical activity? Multiple Sclerosis and Related Disorders. 2022 Dec 1;68:104108.DOI: 10.1016/j.msard.2022.104108
  • Scott K, Bonci T, Salis F, Alcock L, Buckley E, Gazit E … Mazzà C. Design and validation of a multi-task, multi-context protocol for real-world gait simulation. Journal of NeuroEngineering and Rehabilitation. 2022 Dec 16;19(1):141.DOI: 10.1186/s12984-022-01116-1
  • Vereijken B, Rochester L. Next-generation digital tools for mobility in research & health. Open Access Government. 2022 Mar 17.DOI: 10.5281/zenodo.6531977
  • Viceconti M, Tome M, Dartee W, Knezevic I, Hernandez Penna S, Mazzà C … Rochester L. On the use of wearable sensors as mobility biomarkers in the marketing authorization of new drugs: A regulatory perspective. Frontiers in Medicine. 2022;9.DOI: 10.3389/fmed.2022.996903
  • Watson P, Hiden H. The e-Science Central study data platform. In: 2022 IEEE 18th International Conference on e-Science (e-Science). 2022. p. 55–64.DOI: 10.1109/escience55777.2022.00020
  • Wohlrab M, Klenk J, Delgado-Ortiz L, Chambers M, Rochester L, Zuchowski M … Jaeger SU. The value of walking: a systematic review on mobility and healthcare costs. European Review of Aging and Physical Activity. 2022 Dec 29;19(1):31.DOI: 10.1186/s11556-022-00310-3

2021

  • Aminian K, Soltani AS, Paraschiv-Ionescu A. Real-world speed estimation using single IMU: A conceptual framework.  International Symposium of 3D-Analysis of Human Movement . (3D-AHM); 2021 May 25.DOI: 10.5281/zenodo.5561262
  • Angelini L, Buckley E, Bonci T, Radford A, Sharrack B, Paling D … Mazzà C. A multifactorial model of multiple sclerosis gait and its changes across different disability levels. IEEE Transactions on Biomedical Engineering. 2021 Nov;68(11):3196–204.DOI: 10.1109/TBME.2021.3061998
  • Awais M, Chiari L, Ihlen EAF, Helbostad JL, Palmerini L. Classical machine learning versus deep learning for the older adults free-living activity classification. Sensors. 2021 Jan;21(14):4669.DOI: 10.3390/s21144669
  • Caruso M, Sabatini AM, Knaflitz M, Della Croce U, Cereatti A. Extension of the rigid-constraint method for the heuristic suboptimal parameter tuning to ten sensor fusion algorithms using inertial and magnetic sensing. Sensors. 2021 Jan;21(18):6307.DOI: 10.3390/s21186307
  • Caruso M, Sabatini AM, Laidig D, Seel T, Knaflitz M, Della Croce U, Cereatti A. Analysis of the accuracy of ten algorithms for orientation estimation using inertial and magnetic sensing under optimal conditions: One size does not fit all. Sensors. 2021 Jan;21(7):2543.DOI: 10.3390/s21072543
  • Curreli C, Di Puccio F, Davico G, Modenese L, Viceconti M. Using musculoskeletal models to estimate in vivo total knee replacement kinematics and loads: Effect of differences between models. Frontiers in Bioengineering and Biotechnology. 2021;9.DOI: 10.3389/fbioe.2021.703508
  • Del Din S, Kirk C, Yarnall AJ, Rochester L, Hausdorff JM. Body-worn sensors for remote monitoring of Parkinson’s disease motor symptoms: Vision, state of the art, and challenges ahead. Journal of Parkinson’s Disease. 2021 Jan 1;11(s1):S35–47.DOI: 10.3233/JPD-202471
  • Gould SL, Cristofolini L, Davico G, Viceconti M. Computational modelling of the scoliotic spine: A literature review. International Journal for Numerical Methods in Biomedical Engineering. 2021;37(10):e3503.DOI: 10.1002/cnm.3503
  • Jakob V, Küderle A, Kluge F, Klucken J, Eskofier BM, Winkler J … Gaßner H. Validation of a sensor-based gait analysis system with a gold-standard motion capture system in patients with Parkinson’s disease. Sensors. 2021 Jan;21(22):7680.DOI: 10.3390/s21227680
  • Keogh A, Argent R, Anderson A, Caulfield B, Johnston W. Assessing the usability of wearable devices to measure gait and physical activity in chronic conditions: a systematic review. Journal of NeuroEngineering and Rehabilitation. 2021 Sep 15;18(1):138.DOI: 10.1186/s12984-021-00931-2
  • Keogh A, Taraldsen K, Caulfield B, Vereijken B. It’s not about the capture, it’s about what we can learn”: a qualitative study of experts’ opinions and experiences regarding the use of wearable sensors to measure gait and physical activity. Journal of NeuroEngineering and Rehabilitation. 2021 May 11;18(1):78.DOI: 10.1186/s12984-021-00874-8
  • Kluge F, Din SD, Cereatti A, Gaßner H, Hansen C, Helbostad JL … Mazzà C. Consensus based framework for digital mobility monitoring. PLoS ONE. 2021 Aug 20;16(8):e0256541.DOI: 10.1371/journal.pone.0256541
  • Mazzà C, Alcock L, Aminian K, Becker C, Bertuletti S, Bonci T … Rochester L. Technical validation of real-world monitoring of gait: a multicentric observational study. BMJ Open. 2021 Dec 1;11(12):e050785.DOI: 10.1136/bmjopen-2021-050785
  • Polhemus A, Ortiz LD, Brittain G, Chynkiamis N, Salis F, Gaßner H … Puhan M. Walking on common ground: a cross-disciplinary scoping review on the clinical utility of digital mobility outcomes. npj Digital Medicine. 2021 Oct 14;4(1):1–14.DOI: 10.1038/s41746-021-00513-5
  • Rossanigo R, Caruso M, Salis F, Bertuletti S, Croce UD, Cereatti A, editors. An Optimal Procedure for Stride Length Estimation Using Foot-Mounted Magneto-Inertial Measurement Units. 2021 IEEE International Symposium on Medical Measurements and Applications (MeMeA); 2021 23-25 June 2021. DOI: 10.1109/MeMeA52024.2021.9478604
  • Roth N, Küderle A, Prossel D, Gassner H, Eskofier BM, Kluge F. An inertial sensor-based gait analysis pipeline for the assessment of real-world stair ambulation parameters. Sensors. 2021 Jan;21(19):6559.DOI: 10.3390/s21196559
  • Salis F, Bertuletti S, Bonci T, Della Croce U, Mazzà C, Cereatti A. A method for gait events detection based on low spatial resolution pressure insoles data. Journal of Biomechanics. 2021 Oct 11;127:110687.DOI: 10.1016/j.jbiomech.2021.110687
  • Salis F, Bertuletti S, Scott K, Caruso M, Bonci T, Buckley E … Cereatti A. A wearable multi-sensor system for real world gait analysis. In: 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC). 2021. p. 7020–3.DOI: 10.1109/embc46164.2021.9630392
  • Salis F, Bertuletti S, Scott K, Caruso M, Bonci T, Buckley E, et al. Accuracy of a multi-sensor system in stride parameters estimation: comparison of straight and curvilinear portions. Proceedings XXI Congresso SIAMOC 2021. Bologna; p. 95; 2021 .DOI: 10.6092/unibo/amsacta/6846
  • Scott K, Bonci T, Alcock L, Buckley E, Hansen C, Gazit E … Mazzà C. A quality control check to ensure comparability of stereophotogrammetric data between sessions and systems. Sensors. 2021 Jan;21(24):8223.DOI: 10.3390/s21248223
  • Sidoroff V, Raccagni C, Kaindlstorfer C, Eschlboeck S, Fanciulli A, Granata R, et al. Characterization of gait variability in multiple system atrophy and Parkinson’s disease. J Neurol. 2021;268(5):1770-9. DOI: 10.1007/s00415-020-10355-y
  • Soltani A, Aminian K, Mazza C, Cereatti A, Palmerini L, Bonci T … Paraschiv-Ionescu A. Algorithms for walking speed estimation using a lower-back-worn inertial sensor: A cross-validation on speed ranges. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 2021;29:1955–64.DOI: 10.1109/tnsre.2021.3111681
  • Taraldsen K, Helbostad JL, Johnsen LG, Saltvedt I, Vereijken B. Mobilise-D: Evaluering av gange og mobilitet på en innovativ måte. Fysioterapeuten. 2021;88(4):70-72.DOI: 10.5281/zenodo.6832443
  • Ullrich M, Küderle A, Reggi L, Cereatti A, Eskofier BM, Kluge F. Machine learning-based distinction of left and right foot contacts in lower back inertial sensor gait data. In: 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC). 2021. p. 5958–61.DOI: 10.1109/embc46164.2021.9630653
  • Ullrich M, Mücke A, Küderle A, Roth N, Gladow T, Gaßner H … Kluge F. Detection of unsupervised standardized gait tests from real-world inertial sensor data in Parkinson’s disease. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 2021;29:2103–11.DOI: 10.1109/tnsre.2021.3119390
  • van Gelder LMA, Angelini L, Buckley EE, Mazzà C. A proposal for a linear calculation of gait asymmetry. Symmetry. 2021 Sep;13(9):1560.DOI: 10.3390/sym13091560

2020

  • Angelini L, Carpinella I, Cattaneo D, Ferrarin M, Gervasoni E, Sharrack B … Mazzà C. Is a wearable sensor-based characterisation of gait robust enough to overcome differences between measurement protocols? A multi-centric pragmatic study in patients with Multiple Sclerosis. Sensors. 2020 Jan;20(1):79.DOI: 10.3390/s20010079
  • Angelini L, Hodgkinson W, Smith C, Dodd JM, Sharrack B, Mazzà C … Paling D. Wearable sensors can reliably quantify gait alterations associated with disability in people with progressive multiple sclerosis in a clinical setting. Journal of Neurology. 2020 Oct 1;267(10):2897–909.DOI: 10.1007/s00415-020-09928-8
  • Bonci T, Keogh A, Del Din S, Scott K, Mazzà C, on behalf of the Mobilise-D consortium. An objective methodology for the selection of a device for continuous mobility assessment. Sensors. 2020 Jan;20(22):6509.DOI: 10.3390/s20226509
  • Bonci T, Keogh A, Del Din S, Scott K, Mazzà C. Continuous mobility monitoring: what is currently missing for a widespread deployment in clinical and research settings? Virtual Physiological Human Conference 2020 (VPH2020), Paris; 2020 Aug 26.DOI: 10.5281/zenodo.4463250
  • Caruso M, Sabatini AM, Knaflitz M, Gazzoni M, Croce UD, Cereatti A. Orientation estimation through magneto-inertial sensor fusion: A heuristic approach for suboptimal parameters tuning. IEEE Sensors Journal. 2020 Sep 21;21(3):3408–19.DOI: 10.1109/JSEN.2020.3024806
  • Galperin I, Herman T, Assad M, Ganz N, Mirelman A, Giladi N … Hausdorff JM. Sensor-based and patient-based assessment of daily-living physical activity in people with Parkinson’s disease: Do motor subtypes play a role? Sensors. 2020 Jan;20(24):7015.DOI: 10.3390/s20247015
  • Gaßner H, Sanders P, Dietrich A, Marxreiter F, Eskofier B, Winkler J, Klucken J. Clinical relevance of standardized mobile gait tests – reliability analysis between gait recordings at hospital and home in Parkinson’s disease: A pilot study. Journal of Parkinson’s disease. 2020 Oct 27;10(4):1763–73.DOI: 10.3233/JPD-202129
  • Gaßner H, Jensen D, Marxreiter F, Kletsch A, Bohlen S, Schubert R … Kohl Z. Gait variability as digital biomarker of disease severity in Huntington’s disease. Journal of Neurology. 2020 Jun 1;267(6):1594–601.DOI: 10.1007/s00415-020-09725-3
  • Ibrahim AA, Küderle A, Gaßner H, Klucken J, Eskofier BM, Kluge F. Inertial sensor-based gait parameters reflect patient-reported fatigue in multiple sclerosis. Journal of NeuroEngineering and Rehabilitation. 2020 Dec 18;17(1):165.DOI: 10.1186/s12984-020-00798-9
  • Paraschiv-Ionescu A, Soltani A, Aminian K. Real-world speed estimation using single trunk IMU: methodological challenges for impaired gait patterns. In: 2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC). 2020. p. 4596–9.DOI: 10.1109/EMBC44109.2020.9176281
  • Polhemus AM, Bergquist R, Basea MB de, Brittain G, Buttery SC, Chynkiamis N … Frei A. Walking-related digital mobility outcomes as clinical trial endpoint measures: protocol for a scoping review. BMJ Open. 2020 Jul 1;10(7):e038704.DOI: 10.1136/bmjopen-2020-038704
  • Randerath W, Dreher M, Gompelmann D, Held M, Koczulla R, Köhnlein T … Steinkamp G. Technological innovations in pulmonology – Examples from diagnostics and therapy. Pneumologie. 2020 Jul 14;74(9):585–600.DOI: 10.5281/zenodo.4468658
  • Rehman RZU, Buckley C, Micó-Amigo ME, Kirk C, Dunne-Willows M, Mazzà C … Del Din S. Accelerometry-based digital gait characteristics for classification of Parkinson’s Disease: What counts? IEEE Open Journal of Engineering in Medicine and Biology. 2020;1:65–73.DOI: 10.1109/ojemb.2020.2966295
  • Rochester L, Mazzà C, Mueller A, Caulfield B, McCarthy M, Becker C …Roubenoff R. A roadmap to inform development, validation and approval of digital mobility outcomes: The Mobilise-D approach. Digital Biomarkers. 2020 Nov 26;4(Suppl. 1):13–27.DOI: 10.1159/000512513
  • Shema-Shiratzky S, Hillel I, Mirelman A, Regev K, Hsieh KL, Karni A … Hausdorff JM. A wearable sensor identifies alterations in community ambulation in multiple sclerosis: contributors to real-world gait quality and physical activity. Journal of Neurology. 2020 Jul 1;267(7):1912–21.DOI: 10.1007/s00415-020-09759-7
  • Soltani A. Gait in real world: validated algorithms for gait periods and speed estimation using a single wearable sensor. Infoscience, Lausanne: EPFL; 2020.DOI: 10.5075/epfl-thesis-8099
  • Ullrich M, Küderle A, Hannink J, Del Din S, Gaßner H, Marxreiter F … Kluge F. Detection of gait from continuous inertial sensor data using harmonic frequencies. IEEE Journal of Biomedical and Health Informatics. 2020 Jul;24(7):1869–78.DOI: 10.1109/JBHI.2020.2975361
  • Viceconti M, Hernandez Penna S, Dartee W, Mazzà C, Caulfield B, Becker C … Rochester L. Toward a regulatory qualification of real-world mobility performance biomarkers in Parkinson’s patients using digital mobility outcomes. Sensors. 2020 Jan;20(20):5920.DOI: 10.3390/s20205920
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2019

  • Caruso M, Sabatini AM, Knaflitz M, Gazzoni M, Croce UD, Cereatti A. Accuracy of the orientation estimate obtained using four sensor fusion filters applied to recordings of magneto-inertial sensors moving at three rotation rates. In: 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). 2019. p. 2053–8.DOI: 10.1109/EMBC.2019.8857655
  • Caruso M, Rossanigo R, Sabatini AM, M K, Gazzoni M, Della Croce U, Cereatti A. Towards an automatic parameter setting for MIMU sensor fusion algorithms. Gait & Posture, 74; 2019 Sep 30; p. 8.DOI: 10.5281/zenodo.4461502
  • Cereatti A, Bertuletti S, Caruso M, Salis F. Multi-sensor integration and data fusion for enriching gait assessment In and Out of the laboratory. International Society of Biomechanics (ISB) 2019, (ISB); 2019 Aug 29; Calgary, Canada.DOI: 10.5281/zenodo.4469142
  • Salis F, Bertuletti S, Caruso M, Della Croce U, Mazzà C, Cereatti A. Multi-sensor integration and data fusion for enhancing gait assessment In and Out of the laboratory. Gait & Posture, 74; 2019 Sep 30; Bologna, Italy p. 34.DOI: 10.5281/zenodo.4471297