Machine learning to detect, stage and classify diseases and their symptoms based on inertial sensor data: a mapping review.

Bibbo, Daniele; De Marchis, Cristiano; Schmid, Maurizio; Ranaldi, Simone

Bibbo, Daniele; De Marchis, Cristiano; Schmid, Maurizio; Ranaldi, Simone.

Affiliation

Bibbo D; Department of Industrial, Electronic and Mechanical Engineering, Roma Tre University, Rome, Italy.
De Marchis C; Department of Engineering, University of Messina, Messina, Italy.
Schmid M; Department of Industrial, Electronic and Mechanical Engineering, Roma Tre University, Rome, Italy.
Ranaldi S; Department of Industrial, Electronic and Mechanical Engineering, Roma Tre University, Rome, Italy.

Physiol Meas ; 44(12)2023 Dec 26.

Article in En | MEDLINE | ID: mdl-38061062

Subject(s)

Wearable Electronic Devices; Humans; Machine Learning

Key words

artificial intelligence; clinical decision support system; inertial measurement unit; wearable technology

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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Wearable Electronic Devices Limits: Humans Language: En Journal: Physiol Meas Journal subject: BIOFISICA / ENGENHARIA BIOMEDICA / FISIOLOGIA Year: 2023 Document type: Article Affiliation country: Italy

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