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Simulating the impact of noise on gait features extracted from smartphone sensor-data for the remote assessment of movement disorders.

, , , , , , and . EMBC, page 6905-6910. IEEE, (2021)

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Gait Characteristics Harvested during a Smartphone-Based Self-Administered 2-Minute Walk Test in People with Multiple Sclerosis: Test-Retest Reliability and Minimum Detectable Change., , , , and . Sensors, 20 (20): 5906 (2020)Human Activity Recognition from Sensor-Based Large-Scale Continuous Monitoring of Parkinson's Disease Patients., , , , , , , , , and 14 other author(s). CHASE, page 249-250. IEEE Computer Society / ACM, (2017)Smartphone- and Smartwatch-Based Remote Characterisation of Ambulation in Multiple Sclerosis During the Two-Minute Walk Test., , , , , , , , , and 1 other author(s). IEEE J. Biomed. Health Informatics, 25 (3): 838-849 (2021)Outcome measures based on digital health technology sensor data: data- and patient-centric approaches., , , , and . npj Digit. Medicine, (2020)Beacon-Based Remote Measurement of Social Behavior in ASD Clinical Trials: A Technical Feasibility Assessment., , , , , , and . Sensors, 21 (14): 4664 (2021)A quality metric for heart rate variability from photoplethysmogram sensor data., , , , , , and . EMBC, page 706-709. IEEE, (2020)Personalized Longitudinal Assessment of Multiple Sclerosis Using Smartphones., , , , , , , and . IEEE J. Biomed. Health Informatics, 27 (7): 3633-3644 (July 2023)Simulating the impact of noise on gait features extracted from smartphone sensor-data for the remote assessment of movement disorders., , , , , , and . EMBC, page 6905-6910. IEEE, (2021)Interpretable Deep Learning for the Remote Characterisation of Ambulation in Multiple Sclerosis using Smartphones., , , and . CoRR, (2021)Building a Machine-Learning Framework to Remotely Assess Parkinson's Disease Using Smartphones., , , , , , , and . IEEE Trans. Biomed. Eng., 67 (12): 3491-3500 (2020)