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Access to Mobilise-D Zenodo and GitHub:

Mobilise-D Zenodo
GitHub

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

2023

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

 

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

 

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

 

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

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

 

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

 

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

 

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 isease: 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

 

Viceconti M, Juárez MA, Curreli C, Pennisi M, Russo G, Pappalardo F. Credibility of in silico trial technologies—A theoretical framing. IEEE Journal of Biomedical and Health Informatics. 2020 Jan;24(1):4–13.

DOI: 10.1109/JBHI.2019.2949888

 

Warmerdam E, Hausdorff JM, Atrsaei A, Zhou Y, Mirelman A, Aminian K … Maetzler W. Long-term unsupervised mobility assessment in movement disorders. The Lancet Neurology. 2020 May 1;19(5):462–70.

DOI: 10.1016/s1474-4422(19)30397-7

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