Soft Transducer for Patient’s Vitals Telemonitoring with Deep Learning-Based Personalized Anomaly Detection

Soft Transducer for Patient’s Vitals Telemonitoring with Deep Learning-Based Personalized Anomaly Detection

This work addresses the design, development and implementation of a 4.0-based wearable soft transducer for patient-centered vitals telemonitoring. In particular, first, the soft transducer measures hypertension-related vitals (heart rate, oxygen saturation and systolic/diastolic pressure) and sends...

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Autori principali: Pasquale Arpaia, Federica Crauso, Egidio De Benedetto, Luigi Duraccio, Giovanni Improta, Francesco Serino
Natura: Articolo
Lingua:English
Pubblicazione: MDPI AG 2022-01-01
Serie:Sensors
Soggetti:
wearable systems
wearable sensors
deep learning
LSTM
machine learning
remote health monitoring
Accesso online:https://www.mdpi.com/1424-8220/22/2/536

Accesso online

https://www.mdpi.com/1424-8220/22/2/536

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