Mariangela Pinnelli
Orcid: 0009-0004-3357-8615
According to our database1,
Mariangela Pinnelli
authored at least 11 papers
between 2022 and 2025.
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Bibliography
2025
Design, Development and Characterization of a Single-Layer 3D-Printed Strain CB-TPU Sensor.
Proceedings of the IEEE International Workshop on Metrology for Industry 4.0 & IoT, 2025
Towards Non-Invasive Hemodynamic Monitoring: A Feasibility Analysis of Left Ventricular Ejection Time (LVET) Measurement with Wearable Inertial Sensors in Aortic Stenosis Patients.
Proceedings of the IEEE International Workshop on Metrology for Industry 4.0 & IoT, 2025
Flexible Dual-Material 3D-Printed Capacitive Force Sensors: Design, Fabrication, and Metrological Characterization.
Proceedings of the IEEE International Workshop on Metrology for Industry 4.0 & IoT, 2025
Preliminary Assessment of a Low-Sampling-Rate Wearable Head-Mounted Inertial Sensor System for Human Activity Recognition.
Proceedings of the IEEE International Workshop on Metrology for Industry 4.0 & IoT, 2025
Influence of Sampling Frequency on the Symmetric Projection Attractor Reconstruction.
Proceedings of the IEEE International Workshop on Metrology for Industry 4.0 & IoT, 2025
2024
Towards the Instrumentation of Facemasks Used as Personal Protective Equipment for Unobtrusive Breathing Monitoring of Workers.
Sensors, September, 2024
A Wearable Platform as a First Step towards Enabling Collective Intelligence in Alzheimer's Disease Management: Feasibility Assessment on Healthy Volunteers.
Proceedings of the IEEE International Workshop on Metrology for Industry 4.0 and IoT, 2024
A Technological Platform for Quantifying Alzheimer's Patient-Caregiver Interactions in the Walk and Talk Program.
Proceedings of the IEEE International Workshop on Metrology for Industry 4.0 and IoT, 2024
2023
Sensors, December, 2023
2022
A Wearable System for Detecting Lumbar Hyperlordosis in Ballet Dancers: Design, Development and Feasibility Assessment.
Proceedings of the IEEE International Workshop on Metrology for Industry 4.0 & IoT, 2022
A quantitative assessment of team members physiological traits and interactions for the development of Collective Intelligence in a clinical scenario.
Proceedings of the IEEE Intl. Conf. on Dependable, 2022