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Wearable Assistant For Monitoring Solitary People
Blekinge Institute of Technology, Faculty of Engineering, Department of Applied Signal Processing.
2016 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Master Thesis presents the system consisting of software and components of Arduinoplatform along with modules compatible with it, intended for use indoor. The device fulfils thefollowing requirements which are: to ensure privacy preservation, low energy consumptionand the wireless nature.

This thesis reports the development of a prototype that would ensure step detection,posture detection, indoor localization, tumble detection and heart rate detection using themicrocontroller, AltIMU-10 v4 module, heart rate monitor, WiFi module and battery. Veryimportant part of the thesis is algorithm, which uses comparison function. Thanks to thewireless nature of a prototype, the system collects data regardless of an environment and sendthem directly to every device supported by Microsoft Windows platform, Linux platform orOS X platform, which are monitored by the supervisor, who takes care of the solitary person.

The main contributions of the prototype are: indoor localization, identification andclassification of occurring situations and monitoring vital signs of the solitary person.

To ensure indoor localization the prototype must collect data from accelerometer. Ofcourse data from AltIMU-10 v4 module in basic form are useless for the supervisor, so thealgorithm, using by the prototype, is programmed to processing and filtering it.

Algorithm is also used to identification and classification occurring situations. Datafrom accelerometer are processed by it and compared with the created pattern.

Monitoring vital signs of the solitary person are more complicated function, because itrequires not only data from accelerometer, but also from heart rate monitor. This sensor isusing to the analyzing condition of the patient when dangerous situation occurs.

Place, publisher, year, edition, pages
2016. , 73 p.
Keyword [en]
Accelerometer, Arduino, Healthcare, Heart rate monitoring, Indoor localization, Tumble detection, Wireless sensor network.
National Category
Signal Processing Other Electrical Engineering, Electronic Engineering, Information Engineering Embedded Systems
Identifiers
URN: urn:nbn:se:bth-14592OAI: oai:DiVA.org:bth-14592DiVA: diva2:1112063
External cooperation
Robert Dega
Subject / course
ET2566 Master's Thesis (120 credits) in Electrical Engineering with emphasis on Signal processing
Educational program
Double Diploma program
Presentation
2016-01-11, Department of Electrical Engineering and Automatics; Room: E9, Gdansk University of Technology; street: Gabriela Narutowicza 11/12, 80-233, Gdańsk, 16:00 (English)
Supervisors
Examiners
Available from: 2017-06-20 Created: 2017-06-19 Last updated: 2017-06-20Bibliographically approved

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fulltext(4795 kB)29 downloads
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Citation style
  • apa
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Output format
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