Alberto Marchesa
Development of a wearable actigraph with Bluetooth Low Energy link and implementation of a dedicated Android App.
Rel. Marco Knaflitz, Daniele Fortunato. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Biomedica, 2019
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Abstract: |
Until early 2000’s, actigraphy has been used mainly as a method to assess insomnia, circadian rhythm disorders or excessive sleepiness. Since then, progresses made on sensor’s dimension and consumption, as well as data analysis algorithms, increased the number of application fields. Human Activity Recognition (HAR) is an active research area that classifies user activities from inertial data; it finds application in medicine, athletics, lifestyle monitoring and human/computer interaction. All modern consumer electronics, such as smartphone, smartwatch and personal activity trackers represent a good platform for HAR application, as they use most advanced technology and IMUs. Nevertheless, devices available nowadays on the market have some important limitations. First, they classify only a small subset of user activities, mostly outdoor sport activities, while a considerable amount of our life is lived indoor, executing simple activities. This is true especially for the elderly and subjects who need cardiac or neuromuscolar rehabilitation, given the importance of physical activity monitoring. Secondly, devices just acquire signals: to process data and classify activities an external software is needed. With this background, in 2017, Politecnico di Torino, in collaboration with Medical Technology s.r.l., developed an actigraph with an on-board software for daily activities recognition. Afterwards, in 2018, this device has been modified by Fabio Bolognesi’s thesis project, in order to improve computing skills, data storage and power consumption. The aim of this thesis now, is to take a step forward on this project by installing a Bluetooth Low Energy module in the device’s hardware and developing a dedicated Android App to control acquisition and display data on a smartphone. The high power computing and portability and the low cost make this device a good candidate for many others application fields. To better understand how this novel wireless actigraph with on board activities classifier works, Bluetooth Low Energy technology and Android App main principles are introduced and firmware’s modification and implemented algorithms are explained. |
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Relators: | Marco Knaflitz, Daniele Fortunato |
Academic year: | 2019/20 |
Publication type: | Electronic |
Number of Pages: | 48 |
Subjects: | |
Corso di laurea: | Corso di laurea magistrale in Ingegneria Biomedica |
Classe di laurea: | New organization > Master science > LM-21 - BIOMEDICAL ENGINEERING |
Aziende collaboratrici: | UNSPECIFIED |
URI: | http://webthesis.biblio.polito.it/id/eprint/12285 |
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