Publications

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Bonci et al. (2022). An algorithm for accurate marker-based gait event detection in healthy and pathological populations during complex motor tasks

Reggi et al. (2022). Real-World Walking Speed Assessment Using a Mass-Market RTK-GNSS Receiver

Vereijken & Rochester (2022). Next-generation digital tools for mobility in research & health

Open Access Government

Rehman et al. (2022). Investigating the Impact of Environment and Data Aggregation by Walking Bout Duration on Parkinson’s Disease Classification Using Machine Learning.

Ibrahim et al. (2022). Short inertial sensor-based gait tests reflect perceived state fatigue in multiple sclerosis

Multiple Sclerosis and Related Disorders

Jaeger et al. (2022). Mobility endpoints in marketing authorisation of drugs: what gets the European medicines agency moving?

Scott et al. (2021). A Quality Control Check to Ensure Comparability of Stereophotogrammetric Data between Sessions and Systems

Mazzà et al. (2021). Technical validation of real-world monitoring of gait: a multicentric observational study

Jakob et al. (2021). Validation of a Sensor-Based Gait Analysis System with a Gold-Standard Motion Capture System in Patients with Parkinson’s Disease

Salis et al. (2021). A wearable multi-sensor system for real world gait analysis

43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society

Ullrich et al. (2021). Machine learning based distinction of left and right foot contacts in lower back inertial sensor gait data

43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society

Polhemus et al. (2021). Walking on common ground: a cross-disciplinary scoping review on the clinical utility of digital mobility outcomes

npj Digital Medicine

Ullrich et al. (2021). Detection of Unsupervised Standardized Gait Tests From Real-World Inertial Sensor Data in Parkinson’s Disease

IEEE Trans Neural Syst Rehabil Eng

Caruso et al. (2021). Extension of the Rigid-Constraint Method for the Heuristic Suboptimal Parameter Tuning to Ten Sensor Fusion Algorithms Using Inertial and Magnetic Sensing

Keogh et al. (2021). Assessing the usability of wearable devices to measure gait and physical activity in chronic conditions: a systematic review

Journal of NeuroEngineering and Rehabilitation

Soltani et al. (2021). 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

Gelder et al. (2021). A Proposal for a Linear Calculation of Gait Asymmetry

Kluge et al. (2021). Consensus based framework for digital mobility monitoring

Salis et al. (2021). A Method for Gait Events Detection based on Low Spatial Resolution Pressure Insoles data

Journal of Biomechanics

Curreli et al. (2021). Using musculoskeletal models to estimate in vivo total knee replacement kinematics and loads: effect of differences between models

Frontiers in Bioengineering and Biotechnology

Awais et al. (2021). Classical Machine Learning Versus Deep Learning for the Older Adults Free-Living Activity Classification

Rossanigo et al. (2021). An Optimal Procedure for Stride Length Estimation Using Foot-Mounted Magneto-Inertial Measurement Units

Gould et al. (2021). Computational modelling of the scoliotic spine: A literature review

Numerical Methods in Biomedical Engineering

Taraldsen et al. (2021). Mobilise-D: Evaluering av gange og mobilitet på en innovativ måte

Fysioterapeuten

Aminian et al. (2021). Real-world speed estimation using single IMU: A conceptual framework

3D-AHM Abstract Book

Keogh et al. (2021). “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

Caruso et al. (2021). Analysis of the Accuracy of Ten Algorithms for Orientation Estimation Using Inertial and Magnetic Sensing under Optimal Conditions: One Size Does Not Fit All

Angelini et al. (2021). A Multifactorial Model of Multiple Sclerosis Gait and its Changes Across Different Disability Levels

IEEE Transactions on Biomedical Engineering

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

Soltani (2020). Gait in real world: validated algorithms for gait periods and speed estimation using a single wearable sensor.

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?

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

Sidoroff et al. (2020). Characterization of gait variability in multiple system atrophy and Parkinson’s disease

Journal of Neurology

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

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

IEEE Sensors Journal

Bonci et al. (2020). Continuous mobility monitoring: what is currently missing for a widespread deployment in clinical and research settings?

Virtual Physiological Human

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

Paraschiv-Ionescu et al. (2020). Real-world speed estimation using single trunk IMU: methodological challenges for impaired gait patterns

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

Randerath et al. (2020). Technological Innovations in Pulmonology – Examples from Diagnostic and Therapy

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

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)