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Characterizing gait in people with multiple sclerosis using digital data from smartphone sensors: A proposed framework
Multiple Sclerosis Journal. 2025;0(0). doi:10.1177/13524585251316242
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CoGames: Development of an adaptive smartphone-based and gamified monitoring tool for cognitive function in Multiple Sclerosis.
J Neurol. 2025, 272: 119.
Discriminating Between Indoor and Outdoor Environments During Daily Living Activities Using Local Magnetic Field Characteristics and Machine Learning Techniques.
IEEE Sensors Journal, 2025, 25: 1507-1515.
Sensor-Derived Measures of Motor and Cognitive Functions in People With Multiple Sclerosis Using Unsupervised Smartphone-Based Assessments: Proof-of-Concept Study.
JMIR Form Res 2024, 8:e60673.
ActiGraph and Indivi Announce Partnership to Advance Precision Neuroscience Trials
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Elevating the bar by demonstrating cross-device reliability to advance future-proof and hardware-agnostic digital endpoints in multiple sclerosis
ECTRIMS 2024, ePoster P1854, Copenhagen, Denmark, 17-20 September 2024.
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Smartphone-based cognitive games provide features that are related to the volume of key brain structures for cognitive function.
ECTRIMS 2024, Poster P397, Copenhagen, Denmark, 17-20 September 2024.
Digital monitoring of motor function in people with MS correlates with measures of cervical spinal cord volume.
ECTRIMS 2024, Poster P277, Copenhagen, Denmark, 17-20 September 2024.
CoGames – Development of a smartphone-based gamified monitoring tool for cognitive functions in Multiple Sclerosis.
ECTRIMS 2024, Poster P285, Copenhagen, Denmark, 17-20 September 2024.
Classification of MS-severity-subgroups using smartphone-based motor tasks and machine learning.
ECTRIMS 2024, ePoster P1561, Copenhagen, Denmark, 17-20 September 2024.
Konectom™ cognitive processing speed test enables reliable remote, unsupervised cognitive assessment in people with multiple sclerosis: Exploring the use of substitution time as a novel digital outcome measure.
Mult Scler . 2024 Aug;30(9):1193-1204.
Reliability and acceptance of dreaMSᴹᴰ, a software application for people with multiple sclerosis: a feasibility study.
J Neurol. 2023 270:262-271.
DISPEL: a Python Framework for Developing Measures from Digital Health Technologies.
IEEE Open J Eng Med Biol . 2024 May 17:5:494-497.
Real-World Gait Detection Using a Wrist-Worn Inertial Sensor: Validation Study.
JMIR Form Res_ 2024, 8:e50035.
Indivi to Collaborate with Biogen to Advance Digital Health Technology and Digital Biomarkers for Parkinson’s Disease
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Mobilise-D insights to estimate real-world walking speed in multiple conditions with a wearable device.
NPJ Sci Rep. 2024, 14:1754.
Digital Mobility Measures: A Window into Real-World Severity and Progression of Parkinson's Disease.
Mirelman et al. Movement Disorders. 2024, 39:328-338.
Smartwatch-derived sleep and heart rate measures complement step counts in explaining established metrics of MS severity.
Mult Scler Relat Disord. 2023, 80:105104.
Assessing real-world gait with digital technology? Validation, insights and recommendations from the Mobilise-D consortium.
J Neuroeng Rehabil. 2023, 20:78.
Evolving regulatory perspectives on digital health technologies for medicinal product development.
NPJ Digit Med. 2023, 6:56.
Assessment of cognitive performance in multiple sclerosis using smartphone-based training games: a feasibility study
J Neurol. 2023, 270: 3451-3463.
Healios AG Named as a Finalist For The Coveted 2022 Swiss Medtech Award
Digital Devices for Assessing Motor Functions in Mobility-Impaired and Healthy Populations: Systematic Literature Review.
Guo et al., Journal of Medical Internet Research, Vol 24, No 11 (2022)
