Recognition of human activities through eSteps insoles

Ursino, Zarmina (2023) Recognition of human activities through eSteps insoles. [Laurea magistrale], Università di Bologna, Corso di Studio in Artificial intelligence [LM-DM270], Documento full-text non disponibile
Il full-text non è disponibile per scelta dell'autore. (Contatta l'autore)

Abstract

Recognition of everyday human activity through mobile personal sensing technology plays a central role in the field of pervasive healthcare. The Bologna-based American company eSteps Inc. addresses the growing motor disability of the lower limbs by offering pre-, during and post-hospitalisation monitoring solutions with biomechanics and telerehabilitation protocol. It has developed a smart, customised and sustainable device to monitor motor activity, fatigue and injury risk for patients and a special app to share data with caregivers and medical specialists. The objective of this study is the development of an Artificial Intelligence model to recognize the activity performed by a person with Multiple Sclerosis or a healthy person through eSteps devices.

Abstract
Tipologia del documento
Tesi di laurea (Laurea magistrale)
Autore della tesi
Ursino, Zarmina
Relatore della tesi
Correlatore della tesi
Scuola
Corso di studio
Ordinamento Cds
DM270
Parole chiave
HAR, Human activity recognition, DL,ML,NB,GNB,DT,RF,SVM,LSTM, BiLSTM,Attention Mechanism,BiLSTM+Attention Layer,micro averaging, macro averaging,time windows,time sliding windows,PGM,Multiple Sclerosis, RNN,accelerometer,gyroscope,acquisition protocol, IMU,PGMPY,pgmpy
Data di discussione della Tesi
3 Febbraio 2023
URI

Altri metadati

Gestione del documento: Visualizza il documento

^