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Publications

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Del Din et al. (2021). 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

Ibrahim et al. (2020). Inertial sensor-based gait parameters reflect patient-reported fatigue in multiple sclerosis

Journal of NeuroEngineering and Rehabilitation

Bonci et al. (2020). An objective methodology for the selection of a device for continuous mobility assessment

Sensors

Galperin et al. (2020). Sensor-Based and Patient-Based Assessment of Daily-Living Physical Activity in People with Parkinson’s Disease: Do Motor Subtypes Play a Role?

Sensors

Rochester et al. (2020). A roadmap to inform development, validation and approval of digital mobility outcomes: the Mobilise-D approach

Digital Biomarkers

Viceconti et al. (2020). Toward a Regulatory Qualification of Real-World Mobility Performance Biomarkers in Parkinson’s patients Using Digital Mobility Outcomes 

Sensors

Caruso et al. (2020). Orientation Estimation Through Magneto-Inertial Sensor Fusion: A Heuristic Approach for Suboptimal Parameters Tuning

IEEE Sensors Journal

Gaßner et al. (2020). 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

Polhemus et al. (2020). Walking-related digital mobility outcomes as clinical trial endpoint measures: protocol for a scoping review

BMJ Open

Angelini et al. (2020). Wearable sensors can reliably quantify gait alterations associated with disability in people with progressive multiple sclerosis in a clinical setting

Journal of Neurology

Shema-Shiratzky et al. (2020). A wearable sensor identifies alterations in community ambulation in multiple sclerosis: contributors to real-world gait quality and physical activity

Journal of Neurology

Ullrich et al. (2020). Detection of gait from continuous inertial sensor data using harmonic frequencies

IEEE Journal of Biomedical and Health Informatics

Gaßner et al. (2020). Gait variability as digital biomarker of disease severity in Huntington’s disease

Journal of Neurology

Warmerdam et al. (2020). Long-term unsupervised mobility assessment in movement disorders

The Lancet Neurology

Rehman et al. (2020). Accelerometry-based digital gait characteristics for classification of Parkinson’s disease: what counts?

IEEE Open Journal of Engineering in Medicine and Biology

Angelini et al. (2019). 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

Viceconti et al. (2019). Credibility of in silico trial technologies—A theoretical framing

IEEE Journal of Biomedical and Health Informatics

Caruso et al. (2019). Accuracy of the orientation estimate obtained using four sensor fusion filters applied to recordings of magneto-inertial sensors moving at three rotation rates

2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
This project has received funding from the Innovative Medicines Initiative 2 Joint Undertaking under grant agreement No 820820. This Joint Undertaking receives support from the European Union’s Horizon 2020 research and innovation programme and EFPIA.
www.imi.europa.eu
Contact us: info@mobilise-d.eu
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